Argo Magazine
Argo Collection
Research Paper Series
Just in Time
Market View
Iason Pills
Argo Magazine
Argo Magazine N.22 2022
Issue N. 22-2022
Climate Stress Test
ESG Climate Scenarios: a Dedicated Framework
Advancements in Bank Stress Tests: from Bayesian Averaging to Causal AI
Market Risk
Real-time CCR Exposures and xVAs: a Neural Network Approach
FinTech
CBDC - Exploring a New Digital World
Argo Magazine N.21 2022
Issue N. 21-2022
Insurance Risk
Risk Sharing Insurance Schemes for Invoice Discounting Platforms
Credit Risk
Credit Risk: Basel IV Regulatory Framework and New Frontiers
Market Risk
Risk Attribution
AML/CFT Risk
New Challenges on Money Laundering and Financial Terrorism Risks
Argo Magazine N.20 2021
Issue N. 20-2021
Market Risk
A Quantization Overview to Credit Counterparty Risk
AML/CFT Risk
Introduction on Money Laundering and Financial Terrorism Risks
Pandemic Effects on Financial System
Impact of Covid-19 Announcements on Financial Markets
Vulnerability Analysis on Italian Bank during the Covid-19 Pandemic
Argo Magazine N.19 2020
Issue N. 19-2020
Systemic Risk
The Propagation of Liquidity Shocks in the Interbank Market: an Analysis on Systemic Risk
New Market Standards
The LIBOR Reform and the Revolution of the New Benchmark Rates: Overnight Rates and New Conventions on Contracts and Instruments
Climate Change Risk
Climate Change Risk: Overview of the Current Landscape and Next Steps for Financial Institutions
Argo Magazine N.18 2020
Issue N. 18-2020
New Ways of Working
Remote Working: Advices to Reduce Risks and Boost Productivity
New Market Standards
The LIBOR Reform and the New Reference Rates Revolution: Origin and Guidelines
Trading Book
New Challenge on SA-CCR: an Overview on Implementation Process
Argo Magazine N.17 2019
Issue N. 17-2019
Credit Risk
2020 EU-wide EBA Stress Test: A Methodological Analysis on the Credit Risk Perspective
NPL Classification a Random Forest Approach
FinTech
FinTechs and Challenger Banks: Old Business, Brand New Approach
Market Risk
Security Market: an Overview of Repo and Security Lending Transactions
Argo Magazine N.16 2019
Issue N. 16-2019
FinTech
BigTech and New Banking Landscape - Evolution, Benefits, Risks and Oversights
Stress Test
Are EBA Stress-Test Driving Banks into Different Business Models?
Market Risk
2019 FRTB Review: Main Interventions
Argo Magazine N.15 2019
Issue N. 15-2019
Credit Risk
A Benchmark Framework for IFRS9 Multiyear-PD Curves Estimation and Stress Testing Exercise: an Application
Portfolio Management
Maximizing Cumulative Prospect Utility for Target Annuity Investment Strategies
Incremental Valutation Frameworks
Advances in Incremental Valuation of Financial Contracts and Definition of the Economic Meaning of the Capital Value Adjustment (KVA)
Argo Magazine N.14 Fall 2018
Issue N. 14-2018
New Market Standards
Interest Rate Benchmarks Reform: Time to Transition is Now
An overview of BREXIT effects on the Banking System
Banking Book
Analysis of the New Standards to Measure and Manage the Interest Rate Risk of the Banking Book Issued By BIS Committee
Argo Magazine N.13 Summer 2018
Issue N. 13-2018
Trading Book
Synergies and challenges in the implementation of Basel IV regulations
SA-CCR: Implications and Challenges of the New Regulation
Stress Test
Modelling Banking Commissions: An Application to the Italian Banking System
Argo Magazine N.12 Winter 2018
Issue N. 12-2018
Alm & Irrbb
A Benchmark Framework for Non Maturing Deposits: An Application to Public Data Available from Banca d'Italia
Trading Book
The Effects of FRTB in the CVA Risk Framework
Argo Magazine N.11 Winter 2016
Issue N. 11-2016
Banking & Finance
Risk and Profitability of Sight Deposits in the Italian Banking Industry
The Fundamental Review of the Trading Book Standardised Approach for Market Risk: Revision and Challenges
Argo Magazine N.10 Spring 2016
Issue N. 10-2016
Banking & Finance
Pricing and Hedging Multi-Asset Options with High-Dimensional Quasi Monte Carlo: FD vs AAD Greeks
Energy & Commodity Finance
The Energy Storage Systems
What Are the Consequences Arising from MIFID II for Energy Operators?
Argo Magazine N.09 Winter 2016
Issue N. 09-2016
Energy & Commodity Finance
To Combine or not to Combine? Recent Trends in Electricity Price Forecasting
Banking & Finance
Complexity and the Mistakable Law of One Price
Argo Magazine N.08 Fall 2015
Issue N. 08-2015
Banking & Finance
The Revision of the CVA Capital Charge by the Basel Commitee
Energy & Commodity Finance
When has OPEC Spare Capacity Mattered for Oil Prices
Argo Magazine N.07 Summer 2015
Issue N. 07-2015
Energy & Commodity Finance
Off-shore Wind Investment under Uncertainty: Part II
OW Bunker : from IPO to Bankruptcy
Banking & Finance
Modelling of Libor-Ois Basis
Argo Magazine N.06 Spring 2015
Issue N. 06-2015
Banking & Finance
Pricing and Risk Management with High-Dimensional Quasi Monte Carlo and Global Sensitivity Analysis
Efficient Computation of the Counterparty Credit Risk Exposure
Energy & Commodity Finance
Off-shore Wind Investment under Uncertainty: Optimal Timing, Size and Leverage
Structural Positions in Oil Futures Contracts
Argo Magazine N.05 Winter 2015
Issue N. 05-2015
Energy & Commodity Finance
Order-Flow and Liquidity Provision
Monetary Measurement of Risk: A Critical Overview - Part IV: Coherent Portfolio Risk Measures
Banking & Finance
Market Instruments for Collateral Management
A Critical Review of Central Banks Satellite Models for Probbilities of Default
Argo Magazine N.04 Fall 2014
Issue N. 04-2014
banking & finance
Collateral Management
Bond Settlement Migration
energy & commodity finance
Natural Gas Statistical Arbitrage
Monetary Measurement of Risk: A Critical Overview - Part III: Convex Measures of Risk
Argo Magazine N.03 Summer 2014
Issue N. 03-2014
energy & commodity Finance
Security of Supply and the Cost of Storing Gas
Monetary Measurement of Risk: A Critical Overview - Part II: Coherent Measure of Risk
banking & finance
Towards a Theory of Internal Valuation and Transfer Pricing of Products in a Bank
special interview
Alessandro Mauro
Argo Magazine N.02 Spring 2014
Issue N. 02-2014
banking & finance
Fast Monte Carlo princing of Nth-to-default swaps
Analytical Credit VaR Stress Tests
energy & commodity finance
Stochastic Optimization for the Princing of Structured Contracts in Energy Markets
Pricing Spark Spread Option with Co-Dependent Threshold Dynamics
special interview
Marco Bianchetti
Argo Magazine N.01 Winter 2014
Issue N. 01-2014
banking & finance
Sight Deposit and Non-Maturing Liability Modelling
Dividen Risk and Dividen-based Instruments
Analytical Credit VaR under Different Scenarios for Probabilities of Default and Recoveries
Optimal Quantization Methods
special interview
A talk with Fabio Mercurio
energy & commodity finance
Asian Options with Jumps
A General Approach to Modelling and Pricing in Energy and Weather Markets
Trading Oil spreads: Statistical Arbitrage
crash course
Monetary Measurament of Risk: A Critical Overview
Argo Collection
Argo Collection N.04 2022 - ESG
Issue N. 04-2022
EU Taxonomies on ESG Regulation
Bank of Italy: Supervisory Expectations on Climate and Environmental Risks
Lessons Learnt on 2022 Climate Stress Test
Argo Collection N.03 2021 - FinTech
Issue N. 03-2021
EU Regulation on Artificial Intelligence
AI Fairness Addressing Ethical and Reliability Concerns in AI Adoption
A Random Forest Approach to Evaluating NPL Porfolios
Argo Collection N.02 2021 - The Benchmark Reform
Issue N. 02-2021
The LIBOR Reform and the New Reference Rates Revolution: Origin and Guidelines
The LIBOR Reform and the Revolution of the New Benchmark Rates: Overnight Rates and New Conventions on Contracts and Instruments
New Standard Conventions for Cash Products and Impacts on Banking Processes and Procedures
Fallback Rate: Cash and Derivatives Products
Argo Collection N.01 2020 - Basel IV Revision and Challenges on Market Risk
Issue N. 01-2020
Basel IV Overview
Synergies and Challenges in the Implementation of Basel IV Regulations
2019 FRTB Review: Main Interventions
New Challenges on SA-CCR: an Overview on Implementation Process
The Effects of FRTB in the CVA Risk Framework
Research Paper Series
Real-Time Exposures and xVAs: a Neural Network Approach
Executive Summary
Machine Learning (ML) techniques have been studied in the very recent years as challenger or complementary models in Finance, respectively opposite to or in support to the best practices. In this article the authors, leveraging also on the industry literature, present an application of a ML model that can predict, almost real-time, Counterparty Credit Risk exposure profiles, XVAs and the corresponding sensitivities for a "toy" netting set of Interest Rate Swaps. The goal is explaining how a fairly simple Artificial Neural Network (ANN), alongside an existing risk infrastructure, can approximate accurately a Monte Carlo Risk engine. Such an approach can be used as a useful monitoring and stress testing tool to complement an existing Monte Carlo Risk framework, with faster speeds of execution with respect to the usual risk pipelines. It is worth to account that this article reflects the first step of a broader research, it is meant to be introductory, and therefore it is not deemed complete nor final.
Advancements in Bank Stress Tests: from Bayesian Averaging to Causal AI
Executive Summary
Banks all over the world are required to perform stress tests for different types of risks to comply with regulatory guidelines. The purpose of stress tests is to estimate the financial impact arising from changes in macroeconomic factors. In turn, the impact estimate provides an indication of the amount of capital necessary to maintain in order to withstand the hypothetical adverse scenarios considered. However, such an estimation process is peculiar and cannot be adequately addressed with statistical tools commonly used for regression tasks. The present work focuses on climate-related risk stress testing, specifically on the technical challenges involved in inference of the impact of macroeconomic changes on credit default risk. Financial institutions, academics and international organizations have proposed several approaches to model climate-related impacts, but estimates remain far from an acceptable degree of confidence. In fact, some peculiar statistical points need to be addressed to produce sensible predictions. It should be noted that stress tests consist of examining the effect of historical variations in macroeconomic variables to forecast the future impact (3-5 years) of hypothetical and unprecedented macroeconomic scenarios. The risk scenarios vary in baseline and adverse risk outline. Commonly, statistical and Machine Learning (ML) models, such as General Linear Model (GLM) and Tree Ensebles are frequently leveraged to accomplish the prediction task, by using the available historical records for optimization purposes. Such a procedure is likely to introduce biases, as does not guarantee the model to be able to generalize from historical (baseline) records, to unrealized adverse scenarios. As such a crucial generalization problem cannot be entirely addressed from a statistical perspective, we stress the importance that predictive models should be highly consistent with available theoretical knowledge on the modelled dynamics. The present work investigates the application of three different methodologies to forecast credit defaults that occur as a consequence of climate shocks in the energy sector. All proposed predictive architectures integrate, to some extent, a general top-down macroanalysis conducted by credit risk experts, which ensures that the models are consistent with theoretical expectations. The first proposed architecture, G-RiskPar, is an automatic, iterative and theory-driven approach, based on Bayesian Averaging of Classical Estimates (BACE). The second approach, MLRisk, combines statistical techniques, such as GLM, and computational methods drawn from ML. Finally, the third architecture, Causal AI, is a Structural Causal Model, which uncovers causal connections in data and use them to upgrade the confidence around the prediction, according to Bayesian inference.
Model Risk Management Principles and the Impact of Machine Learning Models
Executive Summary
The increasing use of models to inform key business decisions and the increasing complexity of models invariably increases firms’ potential exposure to model risk. This RPS suggests some principles - proposed by Regulatory and/or Supervisory - which are considered key in establishing an effective model risk management (MRM) framework. The principles are intended to complement existing requirements and supervisory expectations in force on MRM and include different proposals for identifying and managing the risks associated with the use of Artificial Intelligence (AI) technology in modelling techniques such as Machine Learning (ML), with particular focus on the validation of these models.
ESG Climate Scenarios: a Dedicated Framework
Executive Summary
The ECB’s Thematic Review on Climate-related and Environmental Risk provides a cross-sectional analysis conducted on supervised banks and aims to identify the strategy, governance and management framework for Climate-related and Environmental Risks. This analysis lead to much evidence, including the soundness of practices. In this respect, the ECB requires banks to provide risk metrics based on climate-related and environmental risks that include measures such as VaR or Stress Test. This paper aims a proposal for the structuring of a Climate Scenario’s framework from input variables that take into account environmental impacts and translating them into macroeconomic and financial variables in order to obtain shocks that can be applied to market data. This consists on: I) an analysis of short-term Transition Climate Risk; II) an analysis of the requirements shared during the ECB’s Thematic Review; III) a study of the existing models and their implementation; IV) a methodological proposal for scenarios climate-related. The authors present a methodology for a financial institution to estimate the ESG Risk: the high degree of flexibility and discretion in management choices represent the main advantages of the approach described.
Bank of Italy: Supervisory Expectations on Climate and Environmental Risks
Executive Summary
The Bank of Italy, in line with similar ECB initiatives, has drawn up an initial set of supervisory expectations regarding the integration of climate and environmental risks into the business strategies, governance and control systems, risk management frameworks and disclosures of supervised banking and financial intermediaries. Expectations provide general non-binding information. Their implementation at an operational level is left to the individual intermediary. The document is addressed to all entities whose activities are subject to authorization and supervision by the Bank of Italy according to the "Testo Unico Bancario - TUB" and "Testo Unico della Finanza - TUF": banks, SIMs, SGRs, self-managed SICAVs/SICAFs, financial intermediaries under Article 106 TUB and their parent companies, payment institutions, IMELs. During 2022, the Bank of Italy will initiate a discussion with the intermediaries on the degree of compliance with expectations and plans for adaptation. This assessment will be included in the supervisory analysis paths, with the aim of ensuring the progressive alignment of business practices with expectations.
Lessons Learnt on 2022 Climate Stress Test
Executive Summary
This Research Paper analyzes the key aspects of the European Central Bank's first Climate Stress Test exercise held in early 2022. This work looks at the experience from the Credit Risk and the Market Risk perspective, focusing on the issues that rose both in data preparation and modelling activities as well as in the interpretation of the scenario provided by the regulator. We analyse the results of the stress test from this stance. Climate Stress Test exercise has highlighted some critical issues in the process of defining and including climate risk in the current stress test framework of banking institutions. Given the current political and economic climate, all banks are expected to have a considerable impact in terms of reviewing both the modelling approach and the IT process and infrastructure. In this paper we take a look at how these processes were reviewed and improved in the Credit Risk and Market Risk areas, suggesting some further refinements that could be brought forward in the next future. In conclusion, banking institutions must necessarily improve their ESG data collection processes and the regulator should aim at achieving a greater degree of homogeneity in the classification methodologies of climate metrics at European and international level.
Risk Attribution
Executive Summary
The well-known Value at Risk (VaR) is the standard market risk quantification for financial institutions. Despite its wide and consolidated usage, evaluating VaR and its decomposition along the desired risk components in a portfolio is still a complex exercise. Commonly, banks do not have automatic risk decomposition frameworks: drill-downs are performed through P&Ls analysis and proxies with sensitivities. Risk controllers and management lack then of a fast and easily readable attribution of VaR (or other risk metrics) to marginal components at both position and risk factor levels. Leveraging on the last two decades of literature on the topic, our approach seeks to provide with a risk decomposition framework which is able to spot (additive) risk and diversification sources within the portfolio(s) at hand that can be beneficial for many goals: risk analysis, uncovering of new (risk-adjusted) business opportunities, improved capital allocation and increased soundness for auditing and supervisory purposes.
Credit Risk: Basel IV Regulatory Framework and New Frontiers
Executive Summary
In December 2017 the Basel Committee finalized and released the 4th iteration of reforms on Banking Supervision. This new set or reforms takes the official name of “Basel III: Finalizing post-crisis reforms”, but in the financial industry is also known as “Basel IV”. Basel IV is the natural step, with the same objective of improving the resilience of the banking system, along with continuous support to the real economy. Among the principal revisions of Basel IV there is the excessive variability of Risk-weighted assets (RWAs), with a particular focus on Credit Risk reforms. This paper will generally introduce the main changes proposed to the Basel framework and a detailed drill-down will be made on the Standardized Approach and IRB Approach of Credit Risk. Furthermore, the topic of new frontiers on credit risk models will be deepened, in particular the use of ML techniques for IRB credit models.
EU Taxonomies on ESG Regulation
Executive Summary
The importance of ESG is subject to increasing attention from regulator, supervisor and institution and there is a growing awareness of the need to integrate all the ESG factors into bank’ strategies, process, and disclosures to the public. In one hand, Corporates are subject to a growing number of disclosure requirements related to ESG factors, which have an impact on financial institutions. In the other, financial institution must act now on the assessment of ESG risks opportunities of their activities and on the development of correct ESG information, to be prepared for changing needs arising from both the market and the regulator. In this sense, regulatory obligations (i.e., Sustainable Finance Disclosure Regulation (SFDR), Non-Financial Reporting Directives (NFRD), the integration of the Corporate Sustainability Disclosure Directive (CSRD) and the EU Taxonomy) can play an important role in scaling up sustainable finance and, in turn, in supporting the achievement of high-level goals such as the Paris Agreement and the UN sustainable development goals.
AI Fairness Addressing Ethical and Reliability Concerns in AI Adoption
Executive Summary
During the last 15 years there has been considerable advancements in AI algorithms, leading AI to achieve comparable - and sometimes superior - performance to human expert judgment. Not surprisingly, AI is now ubiquitous in financial industry: financial firms apply AI to select investments, banks to score creditworthiness, insurances to identify frauds - just to mention a few examples. However, AI algorithms do not resemble (human) logic, but leverage subtle statistical associations in data to make point estimate predictions. This results in black-box architectures, which lack of transparency and do not ensure that predictions generalize to changes in data distribution induced by exogenous factors. Therefore, increasing concerns have risen on AI reliability, resiliency along with several ethical threads, which extend well beyond AI failure or malicious use. In the present document, AI-related risks and their technical origins are discussed. Furthermore, a summary of the regulatory framework for AI, recently proposed by the European Commission, is provided, accompanied by methodologies to address the mentioned issues. Finally, while most AI applications are built on top of data-driven pattern recognition algorithms, which enforce agnostic models on data, the authors advocate the reversed approach. Probabilistic graphs, which can integrate theory-driven models with high-level information, allow to generate predictions in the form of posterior probability distributions. Probabilistic graphs bring multiple technical and epistemological benefits, as exposing their functioning principle, allowing risk assessment, counterfactual reasoning and increasing knowledge of the phenomenon being studied.
EU Regulation on Artificial Intelligence
Executive Summary
Artificial Intelligence (AI) is a fast-evolving family of technologies that can bring a wide array of economic and societal benefits across the entire spectrum of industries and social activities. However, the same elements and techniques that drive the socio-economic benefits of AI can also bring new risks or negative consequences for individuals or for the society. In particular, these risks for the financial sector could be related to unintended bias or discrimination against, i.e. certain groups of consumers, underpricing of financial products or systematic errors in underwriting new financial consumers. Benefits and risks are the main reasons that lead the supervisors and regulators to set some initial principles and guidelines, in order to manage risks, without excluding any firms from the use of such technology. In this paper there will be a drill-down of some European-level initiatives on AI. In particular, the European Commission’s proposal for regulation on Artificial Intelligence published in April 2021 will be analyzed in Part I. Subsequently, the principles for the use of big data algorithms and artificial intelligence in decision-making processes published by BaFin in June 2021 will be proposed in Part II. Finally, the analysis of the European Banking Authority published in June 2021 on the benefits and challenges for financial institutions and supervisors on RegTech solutions will be proposed in the last Part of this paper.
A Random Forest Approach to Evaluating NPL Porfolios
Executive Summary
Artificial Intelligence has quickly entered in the financial services industry covering a wide range of applications. Its use is not new in Financial Institutions, to reach better predicting power, specifically for default forecast and classification purposes but it has grown significantly of recent years, thanks to the exponential increase in data availability and storing capacity, coupled with the improvements in computing power. Models based on Machine Learning approaches are often quite effective in classifying NPL and estimating debtors default probabilities, due to the ability in catching complex connections existing among variables, however, this often occurs at the expenses of clarity and interpretation as the connections among inputs and results are often obscured by the complexity of the process. This is one of the main reasons why, though ML models provide an opportunity to interpret massive and unstructured data sources, they have not been rapidly adopted into institutions' IRB models without an adequate understanding by the management and supervisors who see them more like a black box[6]. This work proposes a structured framework for the classification and evaluation of unsecured commercial NPLs according to their potential recovery level. The first part of the work introduces the methodology used to create homogeneous clusters through decision trees, i.e. by recursively splitting the variable space. Following, the most relevant performance indicators, necessary to select and validate models estimated, are presented. Beside standard single variable indicators, providing a rapid overview of performances, the ’Confusion Matrix’ is explained and extended. Finally, the definition of the threshold necessary to correctly identify recovered dossiers is determined following different criteria. In order to evaluate the approach analyzed, the results form the Random Forest framework are compared to those of more classical Logit methods proving to be as reliable and slightly more performing even with a limited set of information. The RF approach used to forecast the overall recovery at aggregate levels is then extended to analyze the recovery dynamic on the basis of provided payment flows, obtaining good results again at aggregate level. Like for the overall recovery rate model, the dynamic is also studied at aggregate level on the basis of a simple functional form for which parameters’ fitting is much less calculation intensive, obtaining a good fit to the real recovery profile.
Risk Sharing Insurance Schemes for Invoice Discounting Platforms
Executive Summary
This paper analyses how a peer-to-peer (P2P) insurance scheme can be set up to cover credit losses originated by unpaid invoices traded on invoice discounting marketplace platforms. We propose i) how companies selling their receivables on the marketplace platforms can pool resources to guarantee the coverage of the credit losses suffered by the buyers of the invoices, ii) how to allocate the share of losses on each participant to the pool, and finally iii) how to redistribute amongst participants the remaining share of the pool after the losses are covered. We start by studying the trivial case of the loss suffered by the buyer on a single invoice, then we show how a form of loss coverage can be obtained by each seller and finally we analyse the full risk sharing by all sellers, and the insurance mechanism that can be set up that is fair to each participant.
Climate Change Risk: Guidelines for Financial Institutions and Stress-Test Frameworks
Executive Summary
During the last few years climate-related risks and their impacts on financial institutions have increasingly become one of the main topics of discussion in the financial environment. This paper aims, first of all, to provide the definitions of ESG factors and risks, together with an overview of the supervisory expectations about their inclusion into financial institutions’ business strategy, internal governance and risk management framework. Secondly, it describes the status quo of the stress test framework, focusing on the main challenges to be faced by financial institutions when adapting their existing engines to the peculiarities of ESG risks, with a deep-dive on the climate change specific stress-test which will be conducted by ECB in 2022.
Impact of Covid-19 Announcements on Financial Markets
Executive Summary
The purpose of this content is to provide a detailed analysis of the financial markets trend after the outbreak of the novel Coronavirus, trying to explain how the covid-related announcements have affected the markets. In particular, the paper focuses on highlighting the differences between the first and second wave of Covid-19. After a brief illustration of the pandemic effect on financial markets during 2020, two main categories have been identified among the announcements that most influenced the markets: medical bulletins, which report the daily number of confirmed cases and deaths, and government actions to counter the health and economic impact of the pandemic, including closure policies and social distancing, prevention campaigns and the use of medical devices and economic aids. These measures, together with the redundancy of news talking about the severity of the pandemic, also affected investors sentiment, which in turn weighed on equity market returns. Through a pooled OLS regression analysis with panel data, we find that during the first wave the stock market reacts negatively to the rise in confirmed cases, to lockdown and social distancing policies. Throughout the second wave, the markets are generally independent of medical bulletins and reacts negatively to the increase in government healthcare actions. The introduction of vaccine may have played a crucial role in these months, bringing new hopes and changing the markets trend. For this reason, future studies may focus on the relation between vaccines administrations and stock markets.
A Quantization Overview to Credit Counterparty Risk
Executive Summary
The counterparty risk topic has become predominant over the past few years according to the worldwide financial crisis happened in 2007-2008 and the following European sovereign debt crisis. It began to receive a growing attention from regulators, which required financial institutions to comply with more punctual conditions concerning counterparty credit exposures arising from derivatives, securities financing transactions, default and downgrade risks characterizing the Over The Counter derivatives market. Consequently, banks started to develop a series of effective and more accurate measures of risk, aimed at estimating the future MTM (or MTFs) value of a derivative at a potential default date, which is typically highly uncertain (as seen from today), over prescribed time horizon and fixed grid of time buckets. The most common approach to quantify the future MTM value is Monte Carlo simulation, which exhibits remarkable difficulties in terms of high computational cost, particularly when the problem dimension increase. Indeed, it’s particularly dependent on the number of considered assets. This is why many financial players moved to more effective and time saving technologies, e.g., based on grid computing and Graphics Processing Units (GPU) capabilities. Within this paper we would like to approach an alternative method based on different algorithmic strategies, quantization. The present paper gives an initial overview of both Monte Carlo Method and quantization approach with a subsequent comparison of the numerical application results among different practical cases. The goal is to show how the quantization approach outperforms Monte Carlo, both in terms of accuracy and computational efforts.
New Standard Conventions for Cash Product and Impacts on Banking Processes and Procedures
Executive Summary
IBOR reform may risk to create divergences in the cash products market as there are not standards defined at internation level. The market participants are facing a transformation which will bare the results only in the next years. Also, the deadline of the LIBOR dismission, changes depending on the currency area and this does not help to reach standards and to provide a clean and stable picture of the markets to participants. The sterling working group, the ARCC and the Euro working group are working to define same conventions to mitigate the unpredictable changes of the transition and this articles aims to clear the different choices and the actions made so far.
Fallback Rate: Cash and Derivatives Products
Executive Summary
Fallback clause is one of the most important pieces to complete the LIBOR reform. It allows legacy contracts to have legal continuity and avoid litigation among contractual parties. The main organizations for Cash products and derivatives propose different approaches about the application of the clause in the legacy contracts. ISDA, for derivatives contracts, launched in October 2020 a protocol to amend contracts by using the fallback clause previously defined in the various working groups. The supplement will amend ISDA’s standard definitions to incorporate robust fallbacks for legacy derivatives linked to IBORs from January 25th, 2021. For cash products, FCA and LMA, with the support of the main regulators, have been working together with the market participants in order to define common rules and waterfall choices to amend the contracts. The following papers tries to illustrate (i) the different approaches in the two areas, (ii) the trigger events for the fallback clause and (iii) how the migration could happen once the LIBORs will be dismissed.
Introduction on Money Laundering and Financial Terrorism Risks
Executive Summary
The author would provide an overview of Anti-Money Laundering and Combating Financing of Terrorism (AML/CFT) policies and procedures in place. In the first section, the author presents a general overview of International Standards with a focus on interpretative notes on the risk-based approach and FIU. To follow, the author gives a summary of the European legislation and the last contributions of i Basel Committee and European Banking Authority.
Vulnerability Analysis on Italian Banks during the Covid-19 Pandemic
Executive Summary
The results of this vulnerability assessment show that the Italian banking sector is fairly positioned to take on the pandemic-induced stress impact, but capital depletion in this scenario could be material especially for Retail Lenders and Small Domestic banks that have the greatest CET1 impact and need a capital increase between 2021 and 2022 to comply with the prudential capital ratios set by the Supervisor. The most significant effects on banks’ capital requirements are given by the credit component, since the effect of the credit support measures (moratoria and loan guarantees) reveal partially the real risk of credit exposures thus increasing the risk of “cliff effect”.
2019 FRTB Review - Main Interventions (Rev.)
Executive Summary
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This paper provides a summary on the main innovations about the Fundamental Review of the Trading Book, the new regulatory capital requirements for Market Risk. In particular, the author focuses on the modifications of the standards introduced by the Basel Committee on Banking Supervision in January 2019, highlighting the amendments with respect to the 2016 version and providing a qualitative assessment on each kind of intervention.
Synergies and Challenges in the Implementation of Basel IV Regulations Process (Rev.)
Executive Summary
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Due to the need for all European banks to comply with the upcoming regulatory frameworks issued by BCBS and ISDA authorities, the authors decided to analyze three of the most impacting regulations for the bank Risk IT function. The recent regulatory need to have a more risk-sensitive framework translated into the design of quite refined methodologies also for standardized approaches: considering the sensitivity-based common approach, the authors chose to focus on the FRTB-SBM, SIMM and SA-CVA regulations and to give a representation of the workflow needed for the metric calculation. The article has the intention to find all relevant similarities and synergies, both on a methodological and technical point of view, that can be exploited by banks, as well as to warn against some challenges that can arise from their implementation.
The Effects of FRTB in the CVA Risk Framework (Rev.2)
Executive Summary
In the light of the recent publication of the finalised Basel 3 review by the Basel Committee on Banking Supervision (BCBS), the authors analyse the effects of the incoming FRTB regulation on the CVA risk framework. As explained in the article, the Basel Committee in 2015 started an important review of the CVA risk framework which has been finalized in December 2017 with the publication of the new Basel 3 standards. In July 2020, BCBS published the revised version of CVA risk framework after November 2019 consultation. The regulator is proposing a new sensitivity-based CVA risk charge with the intention of being much more consistent with the FRTB standardised approach. The paper is also a chance for the authors to explore the shortcomings and the challenges implied in the newly proposed CVA regulation, especially with respect to the concurrent financial risk frameworks.
The LIBOR Reform and the Revolution of the New Benchmark Rates: Overnight Rates and New Conventions on Contracts and Instruments
Executive Summary
The advent of the new reference rates, strongly desired following the credibility crisis of LIBORs, has led for almost all currencies, to the definition of specific Overnight rates as new reference (risk-free) rates. This determines a strong innovation in all banking and financial products indexed at these rates. In the article technical aspects and open problems.
The Propagation of Liquidity Shocks in the Interbank Market:an Analysis on Systemic Risk
Executive Summary
The main concern of this work is on the understanding of the drivers of financial contagion within the banking sector. The interbank market represents the major channel through which liquidity shocks propagate within the financial system. The analysis provides a description of the repo market's dynamics, that represents the main source of short term funding for financial intermediaries. The evolution of the structure of this market is characterized by a sharp increase in complexity and concentration. This tendency has increased the exposure of the financial system to systemic outbreaks. Moreover, we consider a theoretical framework based on graph theory, that is able to reproduce a financial network and its dynamics in response to a set of liquidity shocks. The work takes into consideration two distinct graph models, Erdös and Rényi model and the Scale Free model. The former is characterized by a binomial degree distribution while the latter produces network structures characterized by power law degree distributions, that are suitable to reproduce the high levels of concentration that are actually observed in real financial configurations. The resilience of the banking sector is then evaluated through the use of an enhancement of the model for the dynamics of financial contagion, developed by Gai, Haldane and Kapadia [15] that is applied to the two network structures previously introduced. The analysis also stresses the importance of both micro and macro-prudential regulation in order to prevent systemic outbreaks. From a macro perspective, the introduction of a periodical stress testing framework for liquidity risk would increase the central supervision over the risk of observing crunches in the interbank market that might impair several interlinked financial markets and ultimately the real economy.
Climate Change Risk: Overview of the Current Landscape and Next Steps for Financial Institutions
Executive Summary
Despite the overshadowing effect of the Covid-19 pandemic during the second quarter of the year, discussions centered on the impacts and opportunities arising from the inclusion of climate change risk into financial institutions' governance, strategy, risk management and disclosure frameworks are constantly getting more intense: this paper aims to provide help to banks (and risk managers, in particular) in comprehending the nature and implications of such new types of risk and to comply with future directives. The paper will provide an overview of the most recent developments in Regulatory and Supervisory expectations for the European area, as well as suggestions related to risk metrics computation's methodologies and a simple practical example of scenario analysis performed with the use of Iason's G-RiskPar tool.
Remote Working:Advices to Reduce Risks and Boost Productivity
Executive Summary
This article has the main purpose to put forward some ideas to embrace a new way of working, that implies a change of mentality but can also be very effective at the productive level; we provide some practical advices on how to manage potential operative risks and maximize benefits working from home. In the last part, we shows how technology can play a pivotal role in supporting and maximizing performances of remote working.
The LIBOR Reform and the New Reference Rates Revolution: Origin and Guidelines
Executive Summary
Starting from the well-known problem of LIBOR rates manipulation, on the thrust of the Financial Stability Board, an extensive reform, for the development of new benchmark rates (RFRs), was conducted at the international level. In this work, the first of a series, after a brief introduction, we try to focus the attention on the operational changes expected within the interest rate market, in light of the indications provided by the Regulators.
New Challenge on SA-CCR: an Overview on Implementation Process
Executive Summary
All European banks need to comply with the improvements in the calculation of capital requirements introduced with Basel III. In 2014, the Basel Committee introduced a Standard Approach for Counterparty Credit Risk (SA-CCR) that is the object of some review by the European Banking Authority and Financial Industry in the last years. The authors have been focused on the last changes of the SA-CCR framework, highlighting the amendments introduced and the industry response to the proposed framework. Furthermore, the authors provide an overview of SA-CCR implementation in a European Bank, highlighting possible critical points in the implementation phase.
2020 EU-wide EBA Stress Test:A Methodological Analysis on the Credit Risk Perspective
Executive Summary
This paper addresses the main novelties brought by the 2020 EU-wide stress test methodological note. These variations are mainly a consequence of results of the last stress test exercise as well as the regulatory changes (new DoD, new securitization framework and CRR II as well as the prudential back-stop rule), which have already or will come into effect during the timespan of the exercise. In comparison to the previous methodology (i.e. 2018 EU-wide stress test methodological note), the paper analyses the main topics on which clear differences emerge: scenario reversion, macro-economic projections, provision calculation for NPEs, securitisation exposures, PIT parameters, provision for sovereigns, LTV and impact on REA and IRB regulatory EL. In addition to that, the paper provides a constructive overview of the critical points for the future consideration of the stress test methodology
NPL Classification A Random Forest Approach (Rev.)
Executive Summary
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Artificial Intelligence has quickly entered in the financial services industry, covering a wide range of applications. This work proposes a structured statistical approach to classify NPL assets according to their potential recovery level, within an unsecured commercial portfolio. Asset classification is based on the information provided with the NPL portfolios and, possibly, some information gathered during the recovery process. The framework adopted is based on two different components: one targeting the cases that will be recovered and one estimating their recovery level, in particular the work compares a Machine Learning technique known as Random Forest to a better-known Logit approach. The first is introduced with a review of the underlining Decision Tree theory, including its performance metrics, to which an extended Confusion table is added to facilitate the comparison of the event recovery forecasts provided by the different models. The comparison shows that the Random Forest approach is as reliable and performing as the more known Logistic approach, providing a solid overall performance even with a limited set of information. It also successfully tests the ability to compare a portfolio under management to a new one of the same type.
FinTechs and Challenger Banks: Old Business, Brand New Approach
Executive Summary
FinTechs are increasingly challenging the status quo of the financial system, either providing brand new services or revisiting the actual players' offerings. The rise of these companies is fueled by big financing from PE, VC and crowdfunding, and by an extremely favourable ground from both a regulatory and a clientele point of view. Given this general scenario, the paper focuses on the major new fintech players in the European banking landscape, analysing their business model and the possible implications for the traditional commercial banks.
Security Market: an Overview of Repo and Security Lending Transactions
Executive Summary
With this work, we would like to provide an overview of the Repurchase Agreement (Repo) and the Security Lending markets. Often, it could be difficult to distinguish Repo and Security Lending: analyzing both typologies of instruments we first look for any differences for what concerns their technical structures, economic profile, participants, legal arrangements. Second, we analyze how these kind of instruments behaved and which vulnerabilities appeared during the last financial and banking crisis. We end the article focusing on structured typologies of Repo, tri-party trade and the total return swap highlighting characteristics in common with classic Repo.
NPL Classification A Random Forest Approach
Executive Summary
Artificial Intelligence has quickly entered in the financial services industry, covering a wide range of applications. This work proposes a structured statistical approach to classify NPL assets according to their potential recovery level, within an unsecured commercial portfolio. Asset classification is based on the information provided with the NPL portfolios and, possibly, some information gathered during the recovery process. The framework adopted is based on two different components: one targeting the cases that will be recovered and one estimating their recovery level, in particular the work compares a Machine Learning technique known as Random Forest to a better-known Logit approach. The first is introduced with a review of the underlining Decision Tree theory, including its performance metrics, to which an extended Confusion table is added to facilitate the comparison of the event recovery forecasts provided by the different models. The comparison shows that the Random Forest approach is as reliable and performing as the more known Logistic approach, providing a solid overall performance even with a limited set of information. It also successfully tests the ability to compare a portfolio under management to a new one of the same type.
BigTech and New Banking Landscape - Evolution, Benefits, Risks and Oversights
Executive Summary
Nowadays advance in technology, coupled with huge amount of heterogeneous data being available, is boosting developments in fields as marketing, robotics, automotive, etc. In this sense, the financial sector is not any different, having already experimented substantial changes from, just to name a few, trading activities to credit lending's. Entrance of new players, from small FinTech companies to BigTech firms, has the potential of either enhance or disrupt the status quo of the financial ecosystem. Examples are already tangible in countries like China, were Alipay, Tencent and Ant Financial are having a sensible impact on payments and credit provisioning activities. Since even more firms are attracted by the potential revenue streams coming from opportunities within the financial sector, regulators has started posing questions about how non-financial institutions should be regulated. This paper aims at providing an overview of the current FinTech and BigTech landscape, with emphasis on the main services provided, coupled with a summary of the assessments already performed by surveillance authorities (mainly BIS) on risks and opportunities the financial sector is facing.
Risk and Profitability of Sight Deposits in the Italian Banking Industry (Rev)
Executive Summary
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This article presents a stochastic risk factor approach to gauge the expected profitability and the liquidity and duration risks of sight deposits of the Italian banking industry, using public data available from Banca d'Italia, spanning over a long period of time that includes the Euro Crisis. The approach is applied to both retail and corporate customers, and it considers their different behaviour based on the size of their deposit.
Modeling of Libor-Ois Basis (Rev)
Executive Summary
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The authors introduce a set of models that explain the market phenomenology of Libor forward fixings implied in swap prices. The models are all based on the idea that the Libor fixings refer to a panel of primary banks whose composition may change over time. This effect is crucial to obtain the observed humped forward fixing curves, that could not be otherwise retrieved by a simple credit default model or by a forward interest rate analogy. The models differ only in the assumptions on how the panel composition will change in the future.
Market Instruments for Collateral Management (Rev)
Executive Summary
We analyse the most common market instruments to manage and optimise collateral allocation: the repo, the sell/buy back and security lending.
Collateral Management: Processes, Tools and Metrics (Rev)
Executive Summary
Collateral management is a crucial activity in the financial industry. The author introduces a framework to analyse the supply and the demand of collateral internally originated by the banking activity, the tools to manage both and the targets that should be aimed at.
Towards a Theory of Internal Valuation and Transfer Pricing of Products in a Bank: Funding, Credit Risk and Economic Capital (Rev)
Executive Summary
In this article the author outlines a framework to theoretically identify the components of the value that a bank should attach to a deal. Moreover the framework suggests how to charge these components to the relevant departments and/or to the final counterparty (client) by an internal transfer pricing system.
Maximizing Cumulative Prospect Utility for Target Annuity Investment Strategies
Executive Summary
The aim of this paper is to show how to use the cumulative prospect theory, created by Kahneman and Tversky, that takes into account the customer's parameters of risk-aversion and reaction to extreme events, loss and gains, in order to plan an investment strategy (mainly based on portfolio insurance techniques) to receive a target annuity after a previously established period of time.
Are EBA Stress-Test Exercises Driving Banks into Different Business Models?
Executive Summary
The paper provides a general analysis of banking business models identification and evolution, and the relationship between the historical behaviour of business models and EBA stress-test projections, with particular attention to Italian banks. The authors propose a new approach to identify business models and then investigate if EU wide stress-test exercises reflect or contrast the past. In addition, they suggest that several banks involved in the stress-test exercises changed business model in order to respond to the continuously increasing regulatory framework even at the expense of economic performances. Finally, the focus on Italian banks, highlights the role of national characteristics that should be considered when analyzing and comparing banks.
A Benchmark Framework for IFRS9 Multiyear-PD Curves Estimation and Stress Testing Exercise - an Application
Executive Summary
This paper presents an econometric and statistic methodologies to manage the enhancement of credit risk modelling introduced with the IFRS9 regulation and it sketches a framework to asses the new IFRS9 measures on a credit portfolio considering different macro-economic scenarios. More specifically, we calibrate the models with the purpose of creation of the multi-year IFRS9 PD curves that can be used to evaluate the Expected Credit Loss 1y and Lifetime for Italian credit portfolios. The framework developed take advantage of the well known theory behind the satellite models to define the sensitivity of credit risk to the macroeconomic environment where the creditors operate. The data, that are a benchmark of Italian system, are retrieved from the public database of "Banca d'Italia" where they are collected according to geographical area and economic activities. To model the macroeconomic environment we calibrate a structural vector autoregression model, in order to describe the behavior of the most relevant economic indicators. The statistical technique examined to estimate the satellite models and VAR parameters is the Bayesian Averaging of Classical Estimation which is widely used also by the ECB in building benchmark models. This framework allows for i) evaluating different macro-economic scenarios; ii) identifying an Italian benchmark of credit risk measure under the new IFRS9 approach; iii) defining a solid framework in order to calculate the Expected Credit Loss for accounting purposes, which can be used on any Italian credit portfolios; iv) estimating the credit risk portfolio sensitivity to the macro-economic shocks, according to its composition in term of economic activities and geographic area of the creditors that belonging to it.
2019 FRTB Review - Main Interventions
Executive Summary
This paper provides a summary on the main innovations about the Fundamental Review of the Trading Book, the new regulatory capital requirements for Market Risk. In particular, the author focuses on the modifications of the standards introduced by the Basel Committee on Banking Supervision in January 2019, highlighting the amendments with respect to the 2016 version and providing a qualitative assessment on each kind of intervention.
Advances in Incremental Valuation of Financial Contracts and Definition of the Economic Meaning of the Capital Value Adjustment (KVA)
Executive Summary
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We extend the analysis we sketched in Castagna and we provide an application of the framework we introduced to incrementally evaluate financial contracts within a financial institution's balance sheet
An overview of BREXIT effects on the Banking System
Executive Summary
The decision by Great Britain to leave Europe is certainly an extraordinary event. Following what has been proposed by some Regulatory Opinions and some already developed works, this article presents a brief overview of the systemic effects for the Banks active in the Community market and in the UK. The effects of the so-called BREXIT can be observed in all the operating levels of the Banks and will determine the need, by the Institutes, to develop a series of procedures to mitigate the risks inherent in this event.
Interest Rate Benchmarks Reform - Time to Transition is Now
Executive Summary
The paper provides a general overview on the ongoing process of reforming Interest Rate Benchmarks, with particular attention to the Euro Area. The authors highlight the potential implications that this reform would have on both business and technical aspects of banks' processes, with focus on the Risk Management fields. Due to the magnitudo of the change and the challenges posed by its implications, the authors believe banks should start transition processes now in order to minimize disruption when current IR benchmarks will cease to be contributed (for some of them as early as 2020). In addition, they suggest banks could take this transition also as a chance to optimize current processes within their risk frameworks in order to reduce complexity and increase efficiency.
SA-CCR Implications and Challenges of the New Regulation
Executive Summary
In light of the revised regulatory frameworks for market and counterparty risks, the author gives an overview on the Standardised Approach for Counterparty Credit Risk (SA-CCR) and its implementation issues in a bank Risk framework. The approach presented by the Basel Committee on Banking Supervision on March 2014 required a study performed by the European Banking Authority concerning the mapping of derivative transactions to risk categories and the correction of regulatory formulas in the current context of negative interest rates. Although the new regulation solves some shortcomings of the current standard approach to CCR, e.g. partially recognizing netting benefits coming from margining and hedging, a few features still need particular attention in order to properly measure the risks associated to the instruments in scope of the regulation. In particular, as also pointed out by EBA, a significant impact on the final capital requirement (the EAD) can derive from the methodology employed to identifiy the primary risk driver of each transaction. After revising the methodologies proposed by EBA, a case study is presented, based on a portfolio including cross currency swaps, and an alternative methodology, aimed at assessing the materiality of each risk driver of the transaction, is proposed. The details on the latter are left to a future publication.
Synergies and challenges in the implementation of Basel IV regulations
Executive Summary
Due to the need for all European banks to comply with the upcoming regulatory frameworks issued by BCBS and ISDA authorities, the authors decided to analyze three of the most impacting regulations for the bank Risk IT function. The recent regulatory need to have a more risk-sensitive framework translated into the design of quite refined methodologies also for standardized approaches: considering the sensitivity-based common approach, the authors chose to focus on the FRTB-SBM, SIMM and SA-CVA regulations and to give a representation of the workflow needed for the metric calculation. The article has the intention to find all relevant similarities and synergies, both on a methodological and technical point of view, that can be exploited by banks, as well as to warn against some challenges that can arise from their implementation.
Modelling Banking Commissions
Executive Summary
This paper presents a procedure for the modelling of net bank commissions (Non Interest Rate Income) as a function of macroeconomic variables. The methodology used to estimate the models is based on a Bayesian approach (BACE) method which provides the degree of relevance for each macroeconomic variable, determining its impact in explaining the evolution of the commissions. Uses of the procedure described above range from internal management purposes to regulatory and supervisory stress testing. A quantitative analysis of the commissions is presented for the Italian banking system, at an aggregate level, and for a sample of Italian banks, at single entity level.
Analysis of the New Standards to Measure and Manage the Risk of the Banking Book Issued by BIS Committee
Executive Summary
This paper presents an analysis of the new standards issued in April 2016 by the Basel Committee, on the measurement and the management of the IRRBB. We will investigate how the new rules will affect the processes currently run by banks and if they are consistent with sound financial principles.
The Effect of the FRTB in the CVA Risk Framework (Rev)
Executive Summary
In the light of the recent publication of the finalised Basel 3 review by the Basel Committee on Banking Supervision (BCBS), the authors analyse the effects of the incoming FRTB regulation on the CVA risk framework. As explained in the article, the revision of regulatory CVA standards, started in 2015 with consultative papers, has been finalised in December 2017 by the Basel Committee with the publication of the new Basel 3 framework. The regulator is proposing a new sensitivity-based CVA risk charge with the intention of being much more consistent with the FRTB standardised approach. The paper is also a chance for the authors to explore the shortcomings and the challenges implied in the newly proposed CVA regulation, especially with respect to the concurrent financial risk frameworks.
Benchmark Framework for NMDM
Executive Summary
This paper presents an application of stochastic risk factor approach to model the non-maturing deposits and it sketches a benchmark framework to assess the related expected profitability and the liquidity and duration risks of a bank compared with the rest of the economic system it works within. More specifically, we calibrate the model to system data for sight deposits of the Italian banking industry, available from the public statistical data base of Banca d'Italia, spanning over a long period of time that includes the Euro Crisis. The approach is applied to both retail and corporate customers, and it considers their different behaviour based on the size of their deposit. It allows for i) an integrated modelling of the market interest rates, creditworthiness of the bank and evolution of the deposits' volume; ii) stochastic risk factors driving deposits' rates and volume; iii) unified and consistent measurement of the interest rate risk and the liquidity; iv) negative interest rates, both at inception and in the future; v) the evaluation of optionalities such as the zero floor on the deposits rates; vi) stress testing for ALM purposes.
The Effect of the FRTB in the CVA Risk Framework
Executive Summary
In the light of the recent reviews performed by the BCBS, the authors analyse the effects of the incoming FRTB regulation on the CVA risk framework. As explained in the article, the consultative papers published by the Basel Committee between July 2015 and March 2016 are proposing a new sensitivity-based CVA risk charge that would be much more consistent with the FRTB standardised approach than the current Basel 3 framework. The article is also a chance for the authors to explore the shortcomings and the challenges implied in the newly proposed CVA regulation, especially with respect to the concurrent financial risk frameworks.
Funding Valuation Adjustment (FVA) and Theory of the Firm: A Theoretical Justification of the Inclusion of Funding Costs in the Evaluation of Financial Contracts
Executive Summary
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We propose a justification of the current practice to charge funding costs in the price of the investments of a bank (and more generally of a firm) within the classical theory of the firm originated from the works by Modigliani and Miller and Merton. This is a first attempt to generalize these works leading to interesting, but not completely sound, results.
Pricing of derivatives contracts under collateral agreements: liquidity and funding value adjustments
Executive Summary
* A Brief Digression on Price and Value * Pricing in a Simple Discrete Setting * Replicating Portfolio in Continuous Time * Pricing with Funding Rate Different from Investment Rate * Funding Rate Different from Investment Rate and Repo Rate * Interest Rate Derivatives * Organization of the Dealing Room
Smile-consistent CMS adjustment in closed form: introducing the Vanna-Volga approach
Executive Summary
In this article, we introduce the Vanna-Volga approach for an alternative valuation of CMS convexity adjustments. Our pricing procedure leads to closed-form formulas that are extremely simple to implement and that retrieve, within bid-ask spreads, market data of CMS swap spreads.
Consistent pricing of FX options
Executive Summary
In the current markets, options with different strikes or maturities are usually priced with different implied volatilities. This stylized fact, which is commonly referred to as smile effect, can be accommodated by resorting to specific models, either for pricing exotic derivatives or for inferring implied volatilities for non quoted strikes or maturities. The former task is typically achieved by introducing alternative dynamics for the underlying asset price, whereas the latter is often tackled by means of statical adjustments or interpolations. In this article, we deal with this latter issue and analyze a possible solution in a foreign exchange (FX) option market. In such a market, in fact, there are only three active quotes for each market maturity, thus presenting us with the problem of a consistent determination of the other implied volatilities. FX brokers and market makers typically address this issue by using an empirical procedure, also named Vanna-Volga (VV), to construct the whole smile for a given maturity. Volatility quotes are then provided in terms of the option’s ∆, for ranges from the 5∆ put to the 5∆ call.In the following, we will review this market procedure for a given currency. In particular, we will derive closed-form formulas so as to render its construction more explicit. We will then test the robustness (in a static sense) of the resulting smile, in that changing consistently the three initial pairs of strike and volatility produces eventually the same implied volatility curve. We will also show that the same procedure applied to European style claims is consistent with static-replication results and consider, as an example, the practical case of a quanto European option. We will finally prove that the market procedure can also be justified in dynamical terms, by defining a hedging strategy that is locally replicating and self-financing.
Sight deposit and non-maturing liability modelling
Executive Summary
In this article we present a review of the most significant approaches provided by the literature and the market practice for the modeling of non-maturing deposits accounts. We describe the bond portfolio replication approach and then move to the class of stochastic factor models, showing how the latter are capable of provide more effective tools for the interest rate and liquidity risk management of these balance-sheet items.
On the dynamic replication of the DVA: do banks hedge their debit value adjustment or their destroying value adjustment?
Executive Summary
We investigate if it is feasible to dynamically replicate the DVA. If the answer is positive, the DVA is a quantity that can be fairly deducted from the liabilities of a financial institution. In this case, the argument in Burgard and Kjaer, where a dynamic replication strategy is derived in details, will be accepted. If on the contrary the answer is negative, then the DVA should be considered as a cost and as such it should be deducted from the equity of the financial institution. In this second case we confirm the results in Castagna. We will analyse the problem under a very wide perspective. We will show that dynamically replicating the DVA hides very subtle assumptions about the composition of the balance sheet of the financial institution. We will also point out which are the (negative) consequences for the business if the financial institution will organize the derivatives business so as to hedge and replicate also the DVA and we will demonstrate how the bank’s franchise will be gradually eroded.
Pricing of collateralized derivatives contracts when more than one currency are involved: liquidity and funding value adjustments
Executive Summary
In this paper we try and complete the analysis conducted in Castagna "Pricing of derivatives contracts under collateral agreements: Liquidity and funding value adjustments" by investigating the valuation of collateralized derivative contracts when more than one currency are involved. This can happen for three reasons: 1. The contract’s pay-off is denominated in some currency YYY but collateral is posted in another currency XXX; 2. The contract is written on an FX rate; 3. The contract’s pay-off depends on assets or market variables denominated in different currencies (e.g.: a cross currency interest rate swap). In theory we could have many currencies involved, but in what follows we restrict our analysis to the case when only two currencies have to be considered. We will analyse all the cases enumerated above and we will define the liquidity value adjustments and funding value adjustments for collateralized contracts.
Analytical pricing of CDOs in a multi-factor setting by a moment-matching approach
Executive Summary
The financial crisis started in the 2007 highlights the need for a more robust approach to accurately pricing and measuring the risk of investment positions held by financial institutions in credit derivatives such as collateralized debt obligations (CDOs). Pricing of CDOs is typically performed by modelling the correlation between debtors. The approaches followed are of two types: a reduced form approach, relying on the specification of the default as a rare event (basically it is the first jump of a Poisson process), so that default correlation can be attained via some form of dependency of the debtors’ default intensities; and a structural approach, based on the Merton’s model, assuming a dependency of the debtors’ asset dynamics on one ore more common factors, thus obtaining a default correlation that can be seen as the result of a copula function.
Funding, liquidity, credit and counterparty links and implications
Executive Summary
The problem of how to include correctly liquidity costs into the pricing of financial contracts has recently risen. The connections between the funding costs and the adjustments due to the compensation that a party has to pay to the counterparty for the losses on a contract caused by its default (the so called debit value adjustment, hereon DVA) have been inquired in some work. The related issue on how to properly compute and consider the DVA has been investigated by other authors. In this work we try and clarify what is the essence of the DVA: we believe we offer a robust conceptual framework to consistently include the DVA in the balance sheet of a financial institution. Under this perspective, to our knowledge never proposed before, the DVA does not manifest any counterintuitive effects, such as a reduction of the current value of the liabilities of a counterparty when its creditworthiness worsens. On the other hand, the link between funding costs and DVA will be easily identified and considered, and in this way we can also establish in a thorough fashion how to discount positive and negative future cash-flows.
Pricing swaps including funding costs
Executive Summary
In Castagna "Funding, liquidity, credit and counterparty risk: Links and implications." we have tried to correctly define the Debit Value Adjustment (DVA) of a derivative contract, coming up with a definition that declares the DVA the worsening of contract conditions for a counterparty because it has to compensate the other party for the possibility of its own default. The DVA is very strictly linked to funding costs (FC) when the contract is a loan, a bond or more generally some kind of borrowing. The link is much less tight, and in fact it could even be non existent, for some derivatives contracts such as swaps. The funding costs for a derivative contract is actually the DVA (plus liquidity premium and intermediation cost, if priced in market quotes) that a counterparty has to pay on the loan contracts it has to close to fund, if needed, negative cumulated cash-flows until maturity. In this paper we study how to include funding costs into the pricing of interest rate swaps and we show how they affect the value of the swap via a Funding Value Adjustment (FVA), in analogy with the Credit Value Adjustment (CVA) and the DVA. In what follows we consider the pricing of swap contracts with no collateral agreement or any other form of credit risk mitigations.
Analytical credit VaR with stochastic probabilities of defaults and recoveries
Executive Summary
We extend the model presented in Bonollo et al. "II second pillar: An analytical VaR with contagion and sectorial risks" by introducing a multiscenario framework that allows for a richer and more realistic specification, including non-static (stochastic) probabilities of default and losses given default. Though more complex from a computational point of view, the model with scenarios is still tractable analytically, yielding results in closed form expressions. The approximated value at risk has been calculated by generalizing the procedure exposed in "II second pillar: An analytical VaR with contagion and sectorial risks" for the single scenario case, in the presence of granularity in the exposures, sector concentration and contagion. The outcome is not simply a weighted sum of the VaRs in the individual scenarios, but results in a more involved function of the single scenarios’ parameters. The theoretical model description is complemented with an in-depth numerical analysis.
Just in Time
ECB - Aggregated Results of SREP 2022
Executive Summary
The ECB published the results of its Supervisory Review and Evaluation Process (SREP) for 2022. This process provides an overall assessment of the challenges facing significant institutions, together with the corresponding capital requirements and other supervisory measures that banks are expected to comply with for the year ahead, in order to better face these challenges. The SREP was conducted amid deteriorating economic conditions and financial market dynamics following Russia’s invasion of Ukraine.
ECB Staff Opinion on the First Set of European Sustainability Reporting Standards
Executive Summary
As part of the European Union activities for the development and approval of the Corporate Sustainability Reporting Directive (CSRD), which introduces disclosure requirements on sustainability topics for firms in the EU, on 22 November 2022 the European Financial Reporting Advisory Group (EFRAG) submitted a first set of European Sustainability Reporting Standards (ESRS) to the European Commission. Consequently, on 25 November 2022 the European Central Bank (ECB) was consulted by the European Commission to provide technical advice on the proposed set of standards. Accordingly, the ECB Staff prepared an opinion, published in January 2023, to provide the Commission with a feedback and to suggest possible adjustments and improvements on elements of relevance to the ECB’s tasks and to better align the standards to the prudential framework. The ECB Staff opinion focuses predominantly on the standards that were considered most relevant to the ECB’s tasks, namely: ESRS 1 (General Requirements), ESRS 2 (General Disclosures), ESRS E1 (Climate change), Other environmental standards. The present document provides an overview of the main points highlighted by the ECB Staff and summarizes the main feedbacks provided on each of the aforementioned standards.
Stress Test EBA 2023
Executive Summary
EBA ha lanciato lo Stress Test 2023 a fine gennaio a livello di UE su un campione di 70 banche. In particolare, nell’ultimo trimestre del 2022 si è assistito ad un aumento persistente dell’inflazione, un inasprimento delle condizioni finanziarie e a un deterioramento delle prospettive economiche a cui lo scenario avverso di stress test ha dovuto fare seguito. Alla luce delle tensioni economiche attuali e degli shock applicati dall’ultimo Stress Test, rimangono alcune perplessità di fondo sulle ampiezze degli scenari, sulla coerenza tra i paesi di aree geografiche contigue e sulla reale utilità degli stress test.
2023 EBA Consultation Paper on the Amending ITS on Supervisory Reporting to Introduce New IRRBB Reporting
Executive Summary
This consultation paper proposes amendments to the ITS on supervisory reporting with regard to Interest Rate Risk in the Banking Book (IRRBB) reporting requirements. This harmonised reporting aims to bring the data quality required for assessing IRRBB risks on an appropriate scale of institutions, including large institutions, institutions other than large institutions and Small and Non-Complex Institutions (SNCI). The first reference date for the application of these technical standards is foreseen to be June 2024. The expected implementation period for the proposed changes is approximately 1 year.
ECB – Towards Climate-related Statistical Indicators
Executive Summary
Coherently with its climate action plan, in January 2023 the European Central Bank (ECB) published a first set of climate-related statistical indicators to better assess the impact of climate-related risks on the financial sector and to monitor the development of sustainable and green finance The indicators cover three areas: Experimental indicators on sustainable finance, Analytical indicators on carbon emissions financed by financial institutions, Analytical indicators on climate-related physical risks. Such indicators leverage on existing data from the European System of Central Banks (ESCB) or other, publicly available, data whenever possible. The statistics are still a work in progress and are intended to facilitate the possibility to better capture data related to climate-related risks and to the green transition. The ECB, together with the national central banks, will continue its activity to improve the methodology and the data used, especially as new data sources will become available in line with EU initiatives on climate-related disclosures and reporting.
AI Risk Management Framework
Executive Summary
AI systems and the contexts in which they are deployed are frequently complex, making it difficult to detect and respond to failures when they occur. These risks make AI a uniquely challenging technology to deploy and utilize. Without proper controls, AI systems can amplify, perpetuate, or exacerbate inequitable or undesirable outcomes for individuals and communities. Responsible AI practices can help align the decisions about AI system design, development, and uses with intended aim and values. On 26 January 2023, National Institute of Standards and Technology (NIST) released its Artificial Intelligence Risk Management Framework (AI RFM), a guidance document for voluntary use by organizations designing, developing, deploying or using AI systems to help manage the risks of AI technologies. The AI RMF follows a direction from U.S. Congress for NIST to develop the framework and was produced in close collaboration with the private and public sectors over the past 18 months.
The EBA Roadmap on Sustainable Finance
Executive Summary
The European Banking Authority (EBA) recognizes the threat to financial and economic stability of risks embedded in ESG factors, such as climate change and social and human right issues. It is in the context of a continuous effort to mitigate these risks and strengthen the financial sector that, in December 2019. the EBA first published its action plan on sustainable finance in which it analyzed market practices related to ESG aspects and provided an initial guidance on specific aspects. Following increased awareness and in parallel with international policy developments the EBA has been requested to broaden its scope and take concrete actions in a wider set of policy areas in a now more mature framework for sustainable finance. This roadmap outlines the EBA’s workplan on sustainable finance and Environment, Social and Governance (ESG) risks replacing the EBA’s first action plan on sustainable finance.
Digital Operational Resilience Act - DORA
Executive Summary
The European Central Bank recognized that cyber risk tripled between 2013 and 2020, with the financial sector being one of the most exposed. In this context, the regulatory requirements applying to the banking sector have been steadily increasing to make sure that IT and cybersecurity risk management keep up with innovation, and with criminal activity. The digitization cannot be related only to the ICT and Cyber domains but, on the contrary, pertains to the entire corporate business. In accordance with this perspective, the direction towards which the new Regulation points, published in the EU’s Official Journal on 27 December 2022, is to develop an intelligence strategy, including the following domains in the analysis of threats and risk: geopolitical, economic and regulatory. Digital Operational Resilience Act (DORA) Regulation entered into force 20 days after the EU publication and shall apply from 17 January 2025.
BCBS – Frequently Asked Questions on Climate-Related Financial Risks Focus on Credit Risk
Executive Summary
The Basel Committee on Banking Supervision (BCBS) is taking a holistic approach to addressing climate-related financial risks to the global banking system in support of its mandate to strengthen the regulation, supervision and practices of banks with the purpose of enhancing financial stability. To this aim and as part of this approach, the Basel Committee has developed responses to a set of FAQs to clarify how climate-related financial risks may be captured in existing Pillar 1 standards. The FAQs and related responses provided by the Committee refer to Credit, Operational, Market and Liquidity Risk. Nevertheless, the focus of the present document is on FAQs related only to Credit Risk, which constitute by far the most consistent part of the BCBS publication.
ECB: Thematic Review on Climate and Environmental Risks
Executive Summary
ECB has concluded its thematic review on climate-related and environmental risks, which is aimed at fostering the alignment of the banking sector with its supervisory expectations (Expectations 1-10), set out in its Guide on climate-related and environmental risks published in November 2020 to ensure that the banking sector effectively and comprehensively addresses climate-related and environmental risks. The ECB also observed good practices being deployed in relation to broader environmental risks, with institutions leveraging existing climate-related risk approaches.
Virtual Asset: Aggiornamenti sulle Operazioni Sospette
Executive Summary
Nel dicembre 2022, la financial unit italiana (UIF) ha pubblicato una newsletter dedicata alle operazioni sospette in materia di Virtual Asset. In particolare si è assistito a un notevole incremento delle SOS negli ultimi 3 anni, in parte legato alla difficoltà di ricostruire i corrispettivi flussi. Come suggerito dagli Standard di GAFI-FATF, sono in corso di definizione una serie di normative ad hoc all’interno del c.d. AML Package.
ECB Climate Stress Test – Overview on Best Practices
Executive Summary
The main contribution of this report is to provide banks with examples and suggestions on how to improve their climate stress testing capabilities based on identified good practices stemming from the 2022 ECB Climate Stress Test (CST) and to support banks in their transitional journey. In particular, the necessity to adequately incorporate climate and environmental risks in banks’ stress testing frameworks and the importance of climate-related data collection are the key elements discussed in the report in order to align banks with industry best practices and meet ECB expectations.
ECB - SSM Supervisory Priorities 2023-2025
Executive Summary
ECB Banking Supervision, in close collaboration with national competent authorities, has reviewed its strategic priorities for the next three years. The review builds on a thorough assessment of the main risks and vulnerabilities for supervised banks, considers the progress made on the priorities endorsed last year and draws on the outcome of the 2022 Supervisory Review and Evaluation Process (SREP). The SSM supervisory priorities for 2023-2025 aim to strengthen supervisory efforts in delivering the medium-term strategic objectives while adjusting the focus to shifting challenges. Supervised institutions will be requested to strengthen their resilience to immediate macro-financial and geopolitical shocks (Priority 1), address digitalisation challenges and strengthen management bodies’ steering capabilities (Priority 2) and step up their efforts in addressing climate change (Priority 3).
2022 EBA Guidelines on IRRBB and CSRBB
Executive Summary
The 2022 EBA Guidelines on IRRBB & CSRBB (EBA/GL/2022/14) will replace, starting from 30 June 2023 for IRRBB side and 30 December 2023 for CSRBB side, the 2018 EBA GLs on IRRBB (EBA/GL/2018/02) that have been in place from June 2019. These GLs specify the criteria for the identification, management and mitigation by institutions of IRRBB either if they implement internal systems or use the standardized methodology or the simplified standardized methodology for the evaluation of IRRBB. Furthermore, they include criteria for determining whether the institutions’ internal systems for evaluating IRRBB are non-satisfactory. In addition, the GLs specify additional criteria for the assessment and monitoring by institutions of their credit spread risk arising from their non-trading book activities (CSRBB).
2022 EBA Final Draft on RTS on Standardized Approach and Simplified Standardized Approach for IRRBB
Executive Summary
For a better evaluation of the risks resulting from potential changes in interest rates that affect both the economic value of equity (EVE) and the net interest income (NII) of an institution's non-trading book activities, EBA has created a Standardized (SA) and a Simplified Standardized Approach (S-SA). The objective is to define a set of rules for cash flow slotting and management of behavioral cash flows using standardized constraints (e.g., Basel caps on NMDS core components or predefined scalars for measuring interest rate sensitivity) as well as to specify the calculation process for EVE and NII risk measures The simplified approach reflects the generally less advanced capabilities of the small and non-complex institutions, satisfying the need of a methodology that is at least as conservative. The RTS drafts will be submitted to the Commission for approval before being reviewed by the European Parliament and Council and published in the Official Journal of the European Union. Meanwhile, the EBA will continue to hold regular stakeholder consultations in order to closely monitor the IRRBB components.
2022 EBA Final Draft on RTS for Supervisory Outliers Tests (SOTs) for IRRBB
Executive Summary
EBA, in compliance with Art. 98 of the Directive 2013/36/EU, is in charge of specifying the supervisory shock scenarios as well as the modelling and parametric assumptions for the exercise of the supervisory outlier tests (SOTs) on the economic value of equity (EVE) and net interest income (NII) related to the interest rate risk arising from institutions’ banking book activities (IRRBB). For the first time, the 2022 final draft RTS specifies the interest rate shock scenarios as well as the modelling and parametric requirements relating to the SOT on NII, providing a metric for quantifying a “large decline” in NII as set out in Article 98(a) of the Directive 2013/36/EU. For both the SOT on EVE and on NII, the 2022 final draft RTS outlines a re-calibration of the post-shock interest rate floor to be applied under each scenario. The new lower bound with gradual and moderate increases finds its rationale in the inconsistency with respect to 2020 observed interest rates.
EBA 2023 EU-wide Stress Test Market Risk
Executive Summary
This document presents the main differences in terms of Market Risk between the EBA 2021 Stress Test methodology and that recently published for the year envisaged in 2023. The differences that emerge are broken down on the basis of the different impact stemming from these changes. In particular, two cases are identified: Relevant changes, where further hitch of an implementation nature or considerable impacts at the output level are expected Slight changes, where no significant changes are expected either of a methodological nature or in terms of results.
Machine Learning Framework
Executive Summary
Artificial intelligence (AI) is a rapidly evolving family of technologies. In particular, the use of AI can foster positive social and environmental outcomes and provide key competitive advantages to businesses and the economy and can entail new risks or negative consequences for individuals or for society (e.g. safety and protection, fundamental rights, difficulty in verifying compliance with current regulations, legal uncertainty for businesses, lack of trust between businesses and citizens, regulatory responses that fragment the EU market). This JIT shows that ML techniques have already permeated the financial sector to a considerable extent and highlights the main aspects for establishing an effective development and validation framework.
Challenger Models: Methodological Approach and Use
Executive Summary
Banks have internal validation processes that include proven procedures to ensure, among other things: safeguarding the accuracy, robustness and stability of the estimate of all relevant risk parameters; and safeguarding the correct / appropriate use of internal models by preventing potential inaccuracies that would lead to incorrect results for the intended use. In the light of above, this JIT provides the methodological approach and use of challenger model, that allows to compare the results of a model with the results of an alternative model starting from the same information used in the development phase.
AML/CFT Colleges in European Union: Evidences from EBA
Executive Summary
On September 1st 2022, the European Banking Authority provided an update on the functioning in the previous year of AML/CFT supervisory colleges. This second report summarizes the findings made by EBA staff during their participation in AML/CFT college meetings and highlights a series of good practises spotted in them. EBA believes that a broad implementation of these procedures could foster ongoing collaboration and proactive information within colleges, which is crucial to identify emerging risks at an early stage. Finally, we could find six EBA actions that lead supervisors should consider implementing in future AML/CFT colleges to further enhance their effectiveness.
Regolamento (UE) 1273/2022 - Nuovi Obblighi di Comunicazione
Executive Summary
Con la delibera dell’ 11 agosto 2022, il Comitato di Sicurezza Finanziaria ha conferito l’incarico alla UIF la ricezione e raccolta delle informazioni previste dagli Articoli 8 e 9 del Regolamento Europeo n. 269/2014 a seguito delle modifiche previste dal Regolamento Europeo n. 1273/2022. Nel primo capitolo sono presentate le due regolamentazioni europee, di seguito vengono presentate le relative modalità di adempimento. Tali dati sono trasmessi dalla UIF alla Commissione Europea, previa informativa al Comitato di Sicurezza Finanziaria.
Climate Risk Stress Test 2022
Executive Summary
The 2022 climate stress-test (CST) could be seen as a joint exercise of 104 banks in regard to the ECB's Climate and Environment Guidance. Goals: - Improving the capabilities of banks and supervisors to assess climate risk; - Provide guidance to banks for future activities; - Developing climate risk awareness and making easier shrinking vulnerability to its possible materialization; -Raise awareness of climate risk and facilitate the reduction of vulnerability to its possible materialization. Due to its nature, the 2022 CST will not have a direct quantitative impact on banks’ regulatory capital.
Bank of England – PRA: Model Risk Management Principles for Banks
Executive Summary
The increasing use of models to inform key business decisions and the increasing complexity of models invariably increases firms' potential exposure to model risk. The PRA-BoE proposes to adopt five principles which it considers key in establishing an effective model risk management (MRM) framework. The principles are intended to complement existing requirements and supervisory expectations in force on MRM and include proposals for: a) a proportionate implementation within firms; b) the identification and allocation of responsibility for the overall MRM framework; c) reporting on the effectiveness of MRM; d) identifying and managing the risks associated with the use of Artificial Intelligence (AI) technology in modelling techniques such as Machine Learning (ML).
Capturing Risk Differentials from Climate-related Risks
Executive Summary
The aim of climate-related risk differential analyses is determining whether there is a consistent link between the greenness of financial institutions assets and their credit profile, thus providing evidence for the introduction of adjustment factors in Pillar 1 framework accordingly. With the 2020 Status Report, the Central Banks and Supervisors’ Network for Greening the Financial System (NGFS) tried to assess climate-related risk differentials on the basis of information provided by a sample of financial institutions. The results did not, however, allow to conclude on risk differentials between green and non-green assets. In 2021, the NGFS published a new report aiming to highlight whether the trends reported in classifications and risk differentials had significantly evolved since the Status Report publication. This document presents the state of the art of the most advanced practices implemented by financial institutions and credit rating agencies to monitor climate-related risks, and the related challenges they are facing in risk differential assessments, as they emerged from the 2021 NGFS report.
Climate Risk Measurement of Asset Eligible as Collateral for Refinancing Operations – Focus on Asset Backed Securities (ABS)
Executive Summary
This paper explains the steps taken to develop a measure of the environmental impact of ABS, an asset class of securities used as collateral in the framework of the ECB refinancing operations. The authors focus on ABS backed by auto loans or loans granted to Small and Medium Enterprises (SMEs) and explores ways to measure their climate risk. The ultimate goal was to define an alignment metric, i.e. to judge whether ABS related emissions would meet the Paris Agreements objectives. This paper aims to: Estimate the feasibility of different climate risk measurement approaches; Develop a theoretical framework to create indicators for any type of ABS; Assess the quality of data available and improvements needed; Explore ways to develop indicators to assess ABS, or propose regulatory amendments to enable such indicators computation. This paper uses data recovered from the European Data Warehouse (EDM) on a sample exclusively composed of homogeneous ABS and operates in three steps: 1.- Find external relevant data and link it to loan-by-loan available data; 2.- Identify relevant metrics derived from the datasets; 3.- Extend the measures to all outstanding ABS and assess their characteristics to establish a ranking.
Nuove Normative Fiscali alla Luce della Riforma Benchmark
Executive Summary
La riforma dei tassi di riferimento in area Euro, Dollaro, GBP, GPY prevede la dismissione dei tassi LIBOR e l’introduzione del tasso overnight €ster per l’area Euro, comportando una concezione nuova nell’utilizzo delle indicizzazioni su strumenti lineari sull’osservazione dei fixing e il calcolo del tasso cedolare. Le nuove metodologie di calcolo, combinate con le nuove regole di osservazione del fixing, implicano la gestione di una cedola di un titolo in due fasi distinte: una fase in cui il tasso è cosiddetto provvisorio in quanto la variazione del tasso è giornaliera fino alla scadenza del periodo di osservazione del fixing; una seconda fase in cui il tasso è certo poiché la base dei fixing è consolidata per il processo finale. Le due fasi hanno condotto a delle riflessioni da parte degli organi competenti sulla gestione della fiscalità per le cedole dei titoli in compravendita per conto terzi o in proprio dai diversi istituti finanziari.
EBA - Discussion Paper “The Role of Environmental Risks in the Prudential Framework”
Executive Summary
Risks stemming from climate change and broader environmental issues are changing the risk picture for the financial sector and will become even more prominent going forward. This raises the question as to whether the prudential framework can sufficiently account for these new risk drivers. In the paper, the EBA initiates the discussion on the adequacy of the current prudential framework with regards to environmental risk factors and evaluates pros and cons of different possible adjustments of the framework in order to fully capture the impacts of ESG factors ensuring, at the same time, a sound risk-based approach for the computation of capital requirements. The EBA encourages further developments in the use of mechanisms under the first pillar to adequately capture environmental risks and stresses the importance of collecting relevant and reliable information on environmental risks and their impact on the financial losses of entities
ECB Levereged Transactions – Supervisory Expectations Regarding the Design and Functioning of RAF and High Levels of Risk Taking
Executive Summary
Recently, the ECB sent a letter to SIs regarding the leveraged transactions (LTs): excessive risk taking is of particular concern to the ECB when it is coupled with inadequate risk management. ECB requires increased scrutiny and remedial actions going forward: these include an LT RAF that identifies, quantifies and limits risks in an appropriate manner, a reduction in risk taking and robust stress testing for the LT portfolio. The ECB intends to actively follow up on all aspects of this letter using a wide range of supervisory tools: failure to remedy these deficiencies will be addressed using all available supervisory tools - including, where relevant, increases in Pillar 2 requirements in the context of the annual SREP process.
Banca d'Italia - Aspettative di Vigilanza sui Rischi Climatici e Ambientali
Executive Summary
La Banca d’Italia, in linea con analoghe iniziative della BCE e di altre autorità di vigilanza nazionali, ha elaborato un primo insieme di aspettative di vigilanza sull’integrazione dei rischi climatici e ambientali nelle strategie aziendali, nei sistemi di governo, controllo e gestione dei rischi e nella informativa al mercato degli intermediari vigilati. Le aspettative forniscono indicazioni di carattere generale non vincolanti. La loro declinazione a livello operativo è rimessa al singolo intermediario. Il documento è rivolto ai soggetti vigilati e autorizzati dalla Banca d’Italia ai sensi del Testo Unico Bancario e del Testo Unico della Finanza: banche, SIM, SGR, SICAV/SICAF autogestite, intermediari finanziari ex Articolo 106 TUB e relative società capogruppo, istituti di pagamento, IMEL. La Banca d’Italia avvierà nel corso del 2022 un primo confronto con gli intermediari sul grado di rispondenza alle aspettative e sui piani di adeguamento. Tale valutazione sarà inclusa nei percorsi di analisi di vigilanza, con l’obiettivo di assicurare il progressivo allineamento delle prassi aziendali alle aspettative.
Corporate Default Forecasting with Machine Learning
Executive Summary
As part of the series “Temi di Discussione”, Banca d'Italia has published the paper "Corporate default forecasting with machine learning". The paper analyzes the performance of some machine learning models in estimating the probability of default, comparing the results with those obtained through traditional models, such as logistic regression. The results show that Machine Learning models provide a significant increase in discriminating power over traditional models when a limited set of information (balance sheet indicators) is available. This advantage decreases when credit behavioral indicators are also considered and becomes negligible in the case of small datasets. Lastly, the use of machine learning models allows a limited number of loans to be made to larger customers compared to traditional models, resulting in lower losses for the bank, but with a higher concentration risk.
Explainable Artificial Intelligence: Interpreting Default Forecasting Models Based on Machine Learning
Executive Summary
Within the series “Questioni di Economia e Finanza” Banca d'Italia published in March 2022 the paper "Explainable Artificial Intelligence: interpreting default forecasting models based on Machine Learning". The paper applies some of the most widely recognized methods in the eXplainable Artificial Intelligence (XAI) literature to measure the importance of individual indicators in estimating the probability of default, comparing the results obtained on a logistic model and on a random forest model. The results obtained show that the accuracy of traditional models depends mainly on credit behavioral indicators, while Machine Learning models give a relevant weight also to financial indicators: the use of Machine Learning techniques could therefore allow a higher accuracy in the evaluation of counterparties for which no credit behavioral information is available. Finally, the paper analyses the evolution of the importance of the variables for estimating the probability of default over the period 2009-2019. The results obtained show that, in periods of economic stress, variables characterized by a non-linear relationship with the dependent variable assume a greater importance in predicting default.
ESMA GL on Liquidity Stress Testing in UCITS and AIFs: Supervisory Expectations and Possible Challenges
Executive Summary
In September 2019 ESMA issued the Guidelines (GL) on liquidity stress testing (LTS) in UCITS and AIFs, whose main purpose is to ensure these Funds are sufficiently liquid to cope under severe liquidity risk scenarios. To this aim, the GL, which are applicable from 30 September 2020, establish periodic LST based on multiple severe but plausible scenarios, based also on the assumption of high-volume withdrawals requests from investors. The article “Liquidity Stress Test e Asset Management”, published on FinRiskAlert by Michele Bonollo, summarizes the elements of a fund liquidity stress test framework and highlights possible challenges related to the implementation of stress test frameworks compliant with ESMA GL.
Banca d’Italia Indagine sulla Gestione delle Inadempienze Probabili
Executive Summary
Il 25 marzo 2022 Banca d’Italia ha pubblicato, nell’ambito della Note di stabilità finanziaria e vigilanza, l’"Indagine sulla gestione delle Inadempienze Probabili". La gestione delle inadempienze probabili (IP), apre nuove sfide per le banche: i debitori classificati come IP versano in situazioni di difficoltà economica e finanziaria giudicate reversibili. Al fine di valutare il livello preparazione delle banche nella gestione attuale e prospettica delle IP, nel 2020 è stata condotta una rilevazione di carattere qualitativo presso le principali banche italiane. La rilevazione ha permesso di raccogliere informazioni sui presidi organizzativi e sui processi interni relativi alla gestione di questa tipologia di crediti deteriorati, consentendo di individuare delle best practice. Nel complesso, dall'indagine emerge che il quadro delle procedure in uso presso le banche per la gestione ed il monitoraggio delle IP è in progressivo miglioramento.
EBA Report on the 2021 Market Risk Benchmarking Exercise
Executive Summary
- The report present the results of the 2021 supervisory benchmarking exercise according to the article 78 of the Capital Requirement Directive (CRD) and the related regulatory and implementing technical standards (RTS) and (ITS) that define the scope, procedures and portfolios for benchmarking internal models for market risk (MR) - The report summarizes the conclusions drawn from a hypothetical portfolio exercise (HPE) conducted by the EBA during the 2020/2021 - The primary objective is to assess the level of variability observed in risk-weighted assets (RWA) for market risk produced by banks’ internal models - The results show a reduction in the dispersion of the IMV (Initial Market Valuation). In general, variability is substantially higher than in the previous exercise. - This is likely to be due to a substantial increase in market volatility, which impacted the level of the risk measures, increasing the dispersion. Overall, the variability for VaR is lower than the variability for sVaR and IRC while ES shows a dispersion similar to that found for VaR A comparison of the ratio between sVaR and VaR shows a decrease due to the substantial increase in VaR figures
EBA Report on the 2021 Credit Risk Benchmarking Exercise
Executive Summary
EBA published its Reports on the annual credit risk benchmarking exercises. These exercises aim at monitoring the consistency of RWAs across all EU institutions authorised to use internal approaches for the calculation of capital requirements. The variability of Credit Risk RWA remained rather stable, despite the pandemic and banks’ efforts to re-develop or re-calibrate their models to comply with the policies set out in the EBA internal rating-based roadmap. A particular focus has been put on analysing the impact of the pandemic and the compensating public measures on the IRB models
The Pricing of Green Bonds: External Reviews and the Shades of Green
Executive Summary
The paper presented in this Just in Time issue investigates the pricing implications of the greenness of bonds. The green-pricing effect is estimated through the "green bond premium", defined as the difference between the yields of matched conventional and green-labeled bonds. The green bonds show a statistically significant premium, which increases with external greenness evaluation and is higher for bonds with darker shades of green.
ECB: Aggregated Results of SREP 2021
Executive Summary
ECB has published the results of its Supervisory Review and Evaluation Process (SREP) for 2021. The 2021 supervisory cycle signaled a return to normality, following the pragmatic approach adopted in 2020, when capital requirements were kept stable on account of the pandemic and supervisory concerns were addressed mainly by means of recommendations, rather than requirements. The findings of that annual assessment indicate that significant institutions have maintained solid capital and liquidity positions. However, banks’ scores remain broadly stable overall. In the 2021 cycle, credit risk and internal governance were the two main areas in terms of remedial measures requested of banks.
The Low-carbon Transition, Climate Commitments and Firm Credit Risk
Executive Summary
This Just in Time issue is based on the ECB's Working Paper "The low-carbon transition, climate commitments and firm credit risk" (No 2631, December 2021). It explores how the need to transition to a low-carbon economy impacts on firm credit risk. It assesses how firm climate-related transition risk exposure, future commitments to reduce emissions, and environmental information disclosure influence two key measures of firms' credit risk: credit ratings and market-implied distance to default. Higher transition risk exposure is associated with higher credit risk. Nonetheless, the disclosure of emissions and the setting of forward-looking targets to curb them both result in lower credit risk. These results have relevant policy implications in terms of corporate disclosures and strategies relating to climate change, as well as for the treatment of climate-related transition risk in the financial sector.
Machine Learning for IRB Models EBA/DP/2021/04
Executive Summary
The aim of the EBA discussion paper "Machine Learning for IRB models" is to understand the challenges and opportunities coming from the world of machine learning (ML) should they be applied in the context of internal ratings-based (IRB) models to calculate regulatory capital for credit risk. The main pivotal challenge comes from their complexity which leads, at least for the more complex ML models, to challenges: i) in interpreting their results, ii) ensuring their adequate understanding by the management functions and bodies iii) justifying their results to supervisors. Acknowledging that ML might play an important part, the EBA is considering to provide a set of principle-based recommendations which should ensure an appropriate use of such techniques by institutions in the context of IRB models. This should ultimately ensure: i) a consistent and clear understanding of the prudential provisions, ii) how new sophisticated ML models can coexist and adhere with these requirements, iii) that the outcome – in terms of setting capital requirements in a prudent manner – continues to be harmonized across Europe.
AML/CFT: The Risk‐Based Supervision Guidelines of European Banking Authority
Executive Summary
The Fourth Directive (EU) 2015/849 recognizes that the ML/FT risk can change, and it sets the risk-based approach at the center of AML/CTF framework. This means that the stakeholders (i.e., Member States, competent authorities and obliged entities) should put in place dedicated processes in order to recognize, evaluate, supervise, handle and mitigate the money laundering and terrorist financing risks. In this work, the author reports the amendments proposed by EBA in the Final Report.
IOSCO - Environmental, Social and Governance (ESG) Ratings and Data Products Providers
Executive Summary
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The development of ESG rating and data products highlighted the lack of a regulation of the market. A fact-finding exercise conducted by IOSCO (International Organization Of Securities Commissions) with providers, users and companies which are the subject of these ESG ratings and data product, revealed the presence of several gaps, explained in detail in the report.
AI Fairness: Addressing Ethical and Reliability Concerns in AI Adoption
Executive Summary
Recent advancements in AI have led to striking performances, making algorithms ubiquitous in industries and ordinary life. However, AI functioning does not resemble human logic and is hard to interpret even for experts; moreover, small changes in input data may bring about a catastrophic drop in AI performance. Therefore, increasing concerns have risen on AI reliability, resiliency to environmental changes along with several ethical threads which arise from wide-scale AI adoption. This JIT touches upon AI-related risks and their technical origins. Furthermore, the key points of the recent EU regulatory framework for AI are listed. Finally, alternative AI approaches, with respect to the common data-driven Machine Learning algorithms, are introduced and discussed as a potential solution to many mentioned issues.