Finalyse Flood Risk Prototype was created in response to the supervisory expectations set by the European Central Bank (ECB) regarding effective management of climate and environmental risks. The ECB published these expectations in November 2020, followed by the release of the thematic review results and a compendium of good practices in November 2022. The article highlights the practical implementation of the Finalyse Flood Risk Prototype specifically for the exposure class of commercial and residential real estate mortgage loans (CRRE). The objective of the exercise is to evaluate the impact of fluvial flood risk on capital requirements for financial institutions, specifically by considering the impact on their Risk-Weighted Assets (RWA). Overall, the development and implementation of the Finalyse Flood Risk Prototype address the ECB’s supervisory expectations and provide banks with a practical tool to assess and manage physical risks associated with flooding, with potential for expansion into other areas of risk assessment.

This article discusses the risks associated with the use of vendor models for IFRS9 compliance by financial institutions, which have increasingly turned to external agencies for model development. While these models are complex and require rigorous evaluation, evaluating vendor models can be particularly challenging due to the proprietary components that vendors may choose not to disclose. The article highlights four types of risks related to vendor models: vendor-specific, institution-specific, implementation-related, and business continuity-related, and outlines different industry-standard approaches to mitigate these risks. The considerations specific to IFRS9 usage of vendor models will help users align their model risk management policies and practices with regulatory guidance. The article emphasizes the need for caution when incorporating vendor models into IFRS9 compliance strategy and recommends Finalyse Risk Advisory team as a trusted partner to guide financial institutions through the complex process of vendor model usage.

In this article we explore the impact of increasing interest rates on Asset and Liability Management (ALM) and offer best practices for effective ALM, using the recent case of Silicon Valley Bank (SVB) as an example. In today’s unpredictable world, marked by events such as the 2008 financial crisis, the ongoing global health crisis, and geopolitical changes, financial institutions as well as their management and decision boards have a crucial responsibility to deploy best practices to protect the interests of their shareholders and customers. Managing the mismatches between assets and liabilities, both in terms of interest rate and liquidity risks is essential to maintain a healthy balance sheet.

The accurate estimation of the credit risk parameters is crucial for provisioning under IFRS9 and capital requirements (when using an IRB approach) as well as for setting up strategies for pricing, risk appetite setting, etc. Due to their unique characteristics, Low Default Portfolios (LDPs) pose distinct challenges that require modellers to explore different modelling and calibration approaches. The application of any alternative modelling technique for LDPs must be independently evaluated for each case based on various factors such as portfolio characteristics, segment, data availability, rating homogeneity, etc. This blog post elaborates on the relevant regulatory landscape, challenges and potential solutions for dealing with the LDPs.

In November 2022, the ECB published the “Walking the talk: Banks gearing up to manage risks from climate change and environmental degradation” report, which concludes that implemented practices do not always reach the desired level of soundness, comprehensiveness, or effectiveness. This article focuses on climate risk management. We argue that, whilst sophisticated practices are necessary, banks could optimise their approaches based on the structure of their portfolios without compromising their existing Net-Zero commitments. We discuss how to meet the regulator’s required level of maturity for materiality and credit risk assessments, whilst considering business logic and strategy in selecting the appropriate solutions to implement.