FSA Proposed Changes to Reverse Stress Testing

Stress and scenario testing should be an integral part of the tools used by the firm’s

senior management in making integrated business strategy, risk management and capital planning decisions. Recent market events have shown the importance of strong governance in firms. Senior management at less affected firms had more successfully established comprehensive firm-wide risk assessment processes in which thoughtful stress and scenario testing played a material part, allowing better-informed and more timely decision-making. However, reviews of firms’ Pillar 2 individual capital assessments, and broader work on stress and scenario testing arrangements, have indicated that for many firms stress and scenario testing is not as robust, nor as embedded in senior management decision-making, as we would like.

In its consultation paper, Stress and scenario testing, Financial Services Authority (FSA) proposes changes to rules and guidance on stress and scenario testing.

In this article, we summarize one of the proposed changes, namely, the reverse-stress test requirement.

Under this new requirement, a firm is required to explicitly identify and assess the scenarios most likely to cause its current business plan to become unviable. In this context, a firm’s business plan should be assumed unviable at the point that crystallising risks cause the market to lose confidence in it, with the consequence that counterparties and other stakeholders are unwilling to transact with it or provide capital to the firm and, where relevant, that existing counterparties may seek to terminate their contracts. Recent experience suggests that such a point may be reached well before a firm’s regulatory capital is exhausted.

The intention behind the introduction of this new requirement is to encourage firms: first, to explore more fully the vulnerabilities of their current business plan (including ‘tail risks’ as well as milder adverse scenarios); second, to make decisions that better integrate business and capital planning; and third, to improve their contingency planning. In the case of “common platform firms’’ the reverse-stress test requirement elaborates the MiFID-derived requirements on risk control.

The proposed requirement is intended to be holistic, so firms should consider liquidity risks as well as risks to their capital positions.

An underlying objective would be to improve consumer protection and market confidence by ensuring that a firm can survive long enough after risks have crystallised for one of the following to occur:

  • the market decides that its lack of confidence is unfounded and re-commences transacting with the firm;
  • the firm down-sizes and re-structures its business;
  • the firm is taken over, or its business is transferred in an orderly manner; or
  • public authorities take over the firm, or wind down its business in an orderly manner.

As a result, it is our view that adequate stress and scenario testing arrangements at a firm should help both to reduce the probability of its financial failure of a firm and the consequent wider impact and costs of any financial failure by making any wind down or re-structuring orderly.

The process of identifying and analysing adverse scenarios that, if they were to occur, would cause a firm’s business model vulnerabilities to crystallise should include a consideration of the likelihood or remoteness of such risks arising in practice.

The introduction of a reverse-stress test requirement should not be interpreted as indicating that we are now pursuing a ‘zero-failure’ policy.

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Data Science in Finance: 9-Book Bundle

Data Science in Finance Book Bundle

Master R and Python for financial data science with our comprehensive bundle of 9 ebooks.

What's Included:

  • Getting Started with R
  • R Programming for Data Science
  • Data Visualization with R
  • Financial Time Series Analysis with R
  • Quantitative Trading Strategies with R
  • Derivatives with R
  • Credit Risk Modelling With R
  • Python for Data Science
  • Machine Learning in Finance using Python

Each book comes with PDFs, detailed explanations, step-by-step instructions, data files, and complete downloadable R code for all examples.