As new regulations require increased visibility of risk management processes, financial institutions often struggle to find strategic value in new investments beyond regulatory compliance. There is a need for tools that not only optimize long-term business strategy but also answer last-minute questions about rapidly changing economic conditions. Linking strategic tools with forecasting models can also provide greater clarity on the purpose of stress testing initiatives and therefore enhance regulatory compliance.
Regulatory requirements have increased across financial institutions in the past decade, and they continue to demand more transparency across the organization. While chasing regulatory compliance, senior management often lacks the time and resources to leverage the output of regulatory exercises for strategic insights. Firms have invested an estimated $12 billion to $15 billion in risk technology and data infrastructure, according to a McKinsey survey.1 If they can appropriately leverage these investments, firms can expect benefits in the range of $19 billion to $24 billion. This paper focuses on how to unlock this value by using new tools to expand key performance metric forecasting under various economic conditions to guide and optimize business strategy.
There are a number of challenges and considerations that must be addressed to effectively forecast capital adequacy (e.g., Common Equity Tier 1). The scope of the calculation is the main issue, as the following must at a minimum be forecast consistently under each scenario:
- Allowances and resulting provisions
- Interest income and expenses, as well as other sources of income
- Risk-weighted assets
While all of these calculations are required for stress testing analysis, the key hurdle to leveraging stress testing infrastructure is the abundance of granular bottom-up models that are time-intensive and computationally demanding. However, understanding the portfolio and economic drivers in resulting forecasts remains critical and necessitates some drill-down abilities.
Currently, the processes in place for stress testing and other regulatory exercises focus on detailed granular analysis, but there is a market need for strategic tools to support a timely analysis for identifying which scenarios and strategies to drill into comprehensively. As shown in Figure 1, financial organizations have focused most of the investments on these goals:
- Data quality, aggregation, and availability
- Compliance and risk reporting
However, the $19 billion to $24 billion worth of benefits that McKinsey predicts are found in the top two layers:
- Strategic decision-making
When it comes to forecasting, capital planning groups are looking to understand the relative performance of scenarios, while regulators are continuing to ask how the organization ensures it adheres to its risk appetite. There is an increasing need for tools that optimize business strategy while simultaneously providing senior management rapid feedback on frequent “what if” scenarios.
A wide variety of “what if” market-moving events requires senior management to be adequately prepared by understanding the potential impact to their organizations. Events such as the UK’s vote to withdraw from the EU and a Chinese growth slowdown have highlighted the need to consider and implement appropriate strategies for these events. Market sentiment shifts rapidly and many events happen overnight, causing senior management to request timely answers on the possible impact to capital forecasts. There is a clear need for an abbreviated top-down analysis to provide rapid feedback and assess many strategies prior to running a more thorough analysis on the chosen scenarios.
Moreover, regulators are increasingly focused on how financial institutions adhere to risk appetite statements. Ensuring that claims made to the market trickle down into actionable measurement at the business-line level has been a challenge across institutions. Management must also show regulators that their internal processes support a portfolio that will withstand a wide variety of economic conditions, which may require running quantitative analyses for those scenarios and considering multiple growth strategies that would perform well within risk appetite bounds.
Business strategy optimization is desired and often elusive for many financial institutions. Following the financial crisis, common practice has moved toward managing capital almost entirely based on the expanded regulatory requirements and standards, but buffers are necessary to account for unforeseen market conditions. Most organizations do not have a way to quantify the “right size” capital buffer, as they do not have an efficient way to analyze additional scenarios and strategic actions. Furthermore, as acquisitions continue and further complicate the equation, data is often not available to run detailed bottom-up models to project the impact on capital ratios.
Capital strategy decisions are heavily scrutinized by the market. Tools that can aid in business optimization and risk quantification will help link operations and processes across diverse financial institutions. Focusing on the drivers of capital metrics such as provisions, interest income, and expenses allows a communicable strategic vision.
Provisions are modeled through a combination of credit loss and allowance models, and they have significant impact on forecast capital ratios by directly impacting net income. Credit losses are highly correlated with the economic cycle, and they are critical for strategic and “what if” analyses. Risk management and allowance requirements often use granular loss modeling, while forecasts for new volumes can be at a more aggregated level.
Interest income and expenses, in conjunction with capital strategy, drive forecasts of capital expectations over time based on a given scenario. Tools developed need to have flexibility in assumptions around items that contribute to net income.
Strategic tools should be tied directly to other models used by various business lines in financial institutions. One way to ensure consistency between strategic and regulatory initiatives is to directly anchor strategic results to forecasts generated by more granular models. The anchoring ensures strategic tools can produce directional indication for additional “what if” analyses and business strategies under consideration.
In conclusion, many financial institutions would benefit from using strategic decision-making tools that offer timely ways to consider strategies and manage risk appetite from the top down. In the past, capital planning, risk management, and portfolio management remained in silos within organizations, and in many cases, those functions were further distributed by region. Increasing scrutiny by the market and regulators has led to increasing demands on senior management to quantify and be able to justify strategic actions and decisions. This, in turn, has been driving the demand for tools that can be leveraged for strategic decision-making and optimization.
1 Harreis, Holger, Matthias Lange, Jorge Machado, Kayvaun Rowshankish, and David Schraa. "A marathon, not a sprint: Capturing value from BCBS 239 and beyond." Risk. McKinsey & Company. June 2015.
Juan M. Licari, PhD, is Chief International Economist with Moody's Analytics. As the Head of Economic and Credit Research in EMEA, APAC and Latin America, Juan and his team specialize in generating alternative macroeconomic forecasts and building econometric tools to model credit risk portfolios.
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