Crunch Time in the Banking Sector: Why Stress Testing Means Bringing Risk and Finance Together

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With the European Banking Association (EBA) stress test and the Targeted Review of Internal Models (TRIM) initiative in 2018, there are more reasons than ever for banks to be consistently data-oriented and analytical. All banks know that. The bad news is that very few institutions are fully convinced of the merits of this course, or ready to move across to this approach. The good news, though, is that there are workable solutions.

From current to future thinking

Troy Haines, a leading thinker on risk and management at SAS (and formerly from JPMorgan Chase), summarizes it this way: A chief risk officer (CRO) needs to change his mindset from “What is” to “What if.” The challenge is to create a data infrastructure in risk and finance that allows simulations and scenario analyses across the entire company and all disciplines. Most banks are still a long way from achieving that. They continue to struggle to collect data for stress testing and particularly to deliver it on time. On top of that, the European Central Bank has added another risk issue to the agenda, with model risk management and the TRIM initiative.

Hidden Insigths: Crunch Time in the Banking Sector: Why Stress Testing Means Bringing Risk and Finance Together

Consolidation of risk and finance is essential

It is clear that the obvious deficits in many banks will not be eliminated with specific changes to the existing data strategy. It is also clear that the disruptive changes in the market mean that it is no longer enough just to comply with regulatory requirements. A uniform data platform is crucial to allow modern services to be offered to modern banking customers. If considerable investments in risk reporting systems are required, then they should also provide a payoff in the form of value creation for the business.

The logical way to do this is to consolidate risk and finance at the data level. This is undoubtedly a huge step for most financial services providers, and requires considerable resources and investment. But it is also essential if CROs are genuinely to reach a point of being able to consider “what if.” It is also possible, because the first reports are now emerging from banks that have taken the lead in this area, and whose expectations have been confirmed. These include ABN AMRO, which has combined finance and reporting with the help of Wolters Kluver and SAS Risk.

Best practices like these prove that the hurdles are not technical. In other words, there are no technical reasons why banks should not manage stress testing and also be able to provide managers with a consistent analytical foundation. SAS® Infrastructure for Risk Management is a technical platform that provides a consolidated and holistic view of the data, enables maximum automation and ensures full transparency. It is flexible so that banks can use models created in different programming languages.

Read more about SAS' methodologies and best practices to help you establish a risk-aware culture, optimize capital and liquidity, and meet regulatory demands on our Risk Management solutions pages.

This post was first published in German on our blog Mehr Wissen.
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About Author

Matthias Piston

Risk Management Expert

In my role as Risk Management Expert I advise banks to design architectures and processes to fulfill legal requiremenets and drive business value from it. My particular focus is helping people involved in the compliance process to automate data preparation tasks so that their time and energy can prioritize more impactful analysis. | In meiner Position bei SAS als Risk-Management-Experte berate ich Banken bei der Entwicklung von IT-Architekturen und Prozessen, damit sie den rechtlichen Anforderungen entsprechen können und schaffe damit Mehrwert für diese Kunden. Mein Beratungsfokus liegt dabei auf der Unterstützung der Fachbereiche. Hier müssen Prozesse automatisiert und standardisiert werden (bspw. bei der Datenaufbereitung). Das ermöglicht es den Kunden, mehr Zeit auf die fachliche Bewertung zu legen und sich weniger um die Daten kümmern zu müssen. Denn Ursachenforschung ist für unsere Kunden wichtiger als Datenbeschaffung und Datenbereinigung.

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