The Critical Role of Scenario Analysis in Modern ALM Practices

Reflecting back on 2023, the banking sector witnessed unprecedented challenges and significant shifts. The year was a defining moment, characterized by global economic volatility and specific incidents that tested the resilience of financial institutions. These developments have firmly established Asset Liability Management (ALM) as a crucial element in the strategic toolkit of banks. In 2024, we are now acutely aware that ALM goes far beyond regulatory compliance, embodying a vital component in ensuring the stability and strategic foresight of banks.


The Shift to Scenario-Based Analysis

Regulators are increasingly favouring narrative led scenario-based analysis in ALM. This shift marks a significant move away from relying solely on historical data. Historical data, while valuable, may not always provide accurate predictions in today’s rapidly changing market conditions.

In the context of complex scenario analysis, traditional tools like Excel are proving inadequate. The complexity and intricacy of modern financial scenarios require more dynamic, and flexible tools. Excel’s limitations in handling large, complex, interconnected datasets and in providing real-time analysis make it insufficient for current ALM needs.

Scenario Analysis in Banking: An Overview

Scenario analysis in banking is a critical tool for assessing the impact of various hypothetical economic and financial situations on a bank’s operations. It involves creating different ‘what-if’ scenarios – such as fluctuations in interest rates or market changes – and evaluating their potential effects on the bank’s financial stability. This approach enables banks to identify risks and prepare for diverse future conditions, going beyond traditional forecasting that relies heavily on past data. It’s essential for effective risk management and strategic decision-making, helping banks navigate uncertainties in the fast-evolving financial landscape.


The Power of MORS’s Scenario Engine

At MORS, we champion the use of “what if” scenario analysis in ALM. Our solution is designed with a powerful scenario engine at its core, enabling banks to quickly configure and calculate diverse scenarios. This capability is crucial for generating relevant, timely, and actionable insights.

In an environment where market conditions can change rapidly, the ability to quickly set up and run new scenarios is invaluable. It is also imperative to have a robust, ongoing process for scenarios governance and back testing. MORS scenario engine allows for agility, ensuring that banks can respond to market shifts with informed decisions. Whether it’s forecasting Liquidity ratios, such Liquidity Coverage Ratios (LCR), or projecting Interest Rate Risk in the Banking Book (IRRBB) type of metrics, i.e Net Interest Income (NII), Earnings at Risk (EaR) or Economic Value of Equity (EVE) our system provides the flexibility and speed required for effective analysis. MORS Scenario Engine also provides the bank with a robust and transparent framework for managing its library of scenarios.

The strength of our scenario analysis lies in its ability to provide actionable insights. Banks can no longer afford delays due to for example excessive data management or reconciliation. MORS equips ALM practitioners with tools to focus on information analysis and the ability on act on the insights.


Conclusion

The evolving role of ALM in banks today necessitates a shift to more advanced, scenario-based analysis tools. MORS Software is at the forefront of this transformation, offering solutions that empower banks to stay ahead in a turbulent world and volatile market. With our scenario engine, banks can move beyond the limitations of traditional tools and embrace the future of ALM with confidence.

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