Six risk management considerations amid the current market volatility

Effective risk management is vital for banks, particularly amid market fluctuations and growing regulatory demands. Banks lacking strong data, model, and reporting processes may be ill-equipped to handle tail risks of the kind that have recently toppled notable institutions on both sides of the Atlantic.

A robust risk management program relies on high-quality data that is well-structured and accessible. Good data processes are essential for developing risk models and

supporting stress tests that can gauge banks’ resilience against financial shocks.

Furthermore, enterprise-level data management is crucial for regulatory compliance. Authorities are expected to intensify scrutiny of banks and heighten expectations for data and model control given the recent upheavals.

Here are six key considerations they should weigh when reviewing their risk management processes and infrastructure:

Embed structure and controls

Amid heightened regulatory scrutiny and changing economic conditions, banks must adopt software solutions that embed structure and controls in their data management processes. This is essential to mitigate human error and prevent the dissemination of duplicative or inaccurate data.  

Additionally, solutions prioritizing data control can bolster model risk management, ensuring that banks have the necessary insights and tools at hand to understand their risks and make informed decisions.

Stringent governance procedures for data and spreadsheets are also crucial to meeting stress testing and resolution planning demands. The growing credit risk concerns and the need for adequate credit loss reserves also underline the importance of proper tools.

In the US, the CECL accounting methodology requires firms to use forward-looking estimates for future loan impairments. Advanced data management solutions may assist banks with CECL, asset-liability, and liquidity risk management, providing access to accurate data and models. These software solutions also support model risk management, enabling informed decisions and regulatory compliance.

Ensure independent testing and validation of software

In an environment where inaccurate data or modeling can have severe consequences, it is essential to employ tools that offer independent testing and validation of the outputs generated by new or existing software packages. Specifically, tools that can streamline data connectivity processes and ensure data auditability are highly valuable in the current market landscape.

Acquire stop-gap solutions

At some institutions, a wholesale overhaul of existing systems and workflows may be necessary to accord with tighter regulations and to meet internal risk management priorities. Reforms of this kind may lead to a cleanout of existing spreadsheets and statistical packages. In these cases, software that can serve as an interim stop-gap solution to complement implementation and onboarding of other solutions may be necessary to ensure continuity of operations and provide additional support during times of change.

Have a business continuity program

Institutions have to invest in robust failover solutions in the event of primary system fails. The importance of these solutions was brought into sharp relief by the recent cyber attack on ION Markets, which caused trade feeds to go missing from exchanges and forced brokers to rely on manual processes, which are highly inefficient and prone to error.

Failover solutions are also essential to minimizing service interruptions and preventing data loss. However, in many cases the go-to failover solution are spreadsheets, which lack the necessary securities and controls to handle sensitive data and protocols.

Ensure ALM and ALCO oversight

Effective software is also essential for navigating the market risks that have grabbed headlines in recent weeks. Banks have to manage their balance sheets effectively, particularly in light of changing interest rates and other market stressors. This means being able to furnish their asset-liability oversight functions with up-to-the-minute information, so that any potential risky mismatches are caught quickly and actioned on.

Enhance liquidity and cash management modeling and testing

The current environment has also underlined the fact that liquidity is not the same as cash, and that depositor behavior can bring about catastrophic risks. Banks need sophisticated tools to track their liability outflows on the one hand and high-quality liquid assets on the other. They also need to assess the robustness of their asset monetization capabilities through regular stress tests and by investing in cutting-edge liquidity risk models.

When it comes to risk management, financial institutions of all sizes face a similar challenge: data is dispersed across the enterprise, making it difficult to get to grips with their credit, liquidity, and asset-liability mismatch risks or meet regulatory requirements. What they need are solutions that help consolidate their data into a more unified view, allowing them to better assess risk and make more informed decisions.

How Coherent Spark can assist

Coherent Spark is a solution that converts spreadsheets into enterprise-grade code, allowing for greater data control, auditability, and security. Spark can supplement financial institutions’ existing software, bridge gaps where end-user computing applications are deployed, or serve as a temporary solution while banks transition to entirely new software packages. Coherent Spark’s primary mission is to assist financial institutions in taking control of their data and enterprise spreadsheets in a cost-effective manner. Spark’s features can help banks avoid the pitfalls of ineffective risk management, human error, and patchy version control.