A Proactive, Integrated Approach to Capital Planning
Our software is a breakthrough in financial modelling, applying advanced algorithms, machine learning and data mining to measure our clients’ key performance indicators under any future scenario. It enables a new range of financial analyses that were previously impossible.
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A Proactive, Integrated Approach to Capital Planning

A Proactive, Integrated Approach to Capital Planning

Read our CEO Alla Gil’s take on how to reduce costs and increase efficiency: practical steps for navigating market uncertainty in GARP magazine.

More than a decade after the financial crisis, senior managers of financial institutions face two challenging tasks. They must deal with evolving regulations and new accounting standards, while simultaneously ensuring that they continue to deliver results in an increasingly volatile market environment.

Alla Gil
Alla Gil

While some experts have called for harmonization of stress tests, coordination among so many supervisory agencies is no easy task. Indeed, today, many different jurisdictions and regulatory bodies have their own unique requirements for stress tests, and these regulatory demands impose high costs on banks.

Fragmentation within a bank is another reason for the excessive cost of stress testing. It is not uncommon for one person, for example, to develop probabilities of default (PDs) for capital stress testing while another develops PD models for expected credit loss for the same loans. These people may work in different departments and produce inconsistent results, even for the same obligor.

To reduce the cost drastically, increase efficiency and expand from stress testing to planning, banks need a coordinated approach for all capital and liquidity requirements, supported by seamless coordination of business objectives, robust models and an integrated data infrastructure.

Practical Principles

This type of approach is driven by a few key principles: (1) generation of multiple scenarios (ideally in the hundreds or thousands); (2) assessment of capital plans and liquidity needs on all scenarios; and (3) selection of the most impactful scenarios for more detailed analysis.

Common practice is to build a few scenarios with a high level of granularity, but human ability to envision future events is limited. Analysts usually rely on experience or imagine major disasters as they construct such limited number of scenarios, while ignoring all the other possibilities. (Indeed, the human mind is incapable of looking through all the possible combinations.)

The problem with this limited‐scenario approach is that the most impactful scenarios could contain a combination of factors – each of which is perhaps innocuous on its own, but, when combined, can lead to a very adverse outcome.

To be prepared for any plausible scenario and avoid surprises (like those experienced by many during the last financial crisis), one must generate multiple scenarios that incorporate institution‐specific macroeconomic and market variables, realistic extreme risks and snowball effects. Such scenarios will implicitly generate dynamic correlations, creating potentially unprecedented outcomes with realistic probabilities.

These forward‐looking scenarios can be used both for risk management and strategic planning. Scenarios in the middle of the distribution can be used for business‐as‐usual (BAU) capital planning and current expected credit loss (CECL) calculations, while those in the tail can be used for BAU risk management, stress testing, recovery and resolution.

While switching from a few to multiple scenarios, the granularity with which a bank’s key performance indicators (KPIs) are calculated must be revisited. The detailed bottom‐up approach required by formal stress testing makes it difficult to deal with even a few mandatory scenarios.

In contrast, with multiple scenarios, an initial top‐down approach is more practical. It allows for estimating KPIs, as well as capital and liquidity indicators, on each scenario at each future point in time. It can be performed on aggregated data using uniform (from a risk perspective) segments of loans, deposits, fees and other balance sheet and income statement items.

Moreover, this preliminary step creates a complete distribution and shows risk managers the scenarios on which risk committees should focus for detailed analysis and fine‐tuning. It is not meant to replace current practices, but rather to enhance and focus them for better governance, consistency and coordination.

Leave No Stone Unturned

It is critical to generate scenarios in an intuitive and transparent manner while incorporating realistic changes in variable interdependencies that occur when trends break. Only then can risk managers be assured that they left no stone unturned, discovered potential hidden risk concentrations and identified all potential combinations of market moves that could lead to adverse performance.

Using publicly disclosed data on business segments and pools of loans (instead of individual loans and deposits), a bank’s own idiosyncratic scenarios can be discovered and implemented at a fairly high level. Senior management can formulate and review its strategic growth plans, while simultaneously identifying early warning signals and creating contingency plans. All planned and contingent management actions can be overlaid on multiple scenarios, with their consequences analyzed and actions agreed to in advance.

Multiple scenarios also help to verify that the proposed solution to mitigate an adverse scenario will not inadvertently generate a new risk. If banks are prepared for any scenario, they can accommodate multiple stress tests for capital and liquidity, market and credit risks, as well as cyber, operational and business risks. What’s more, better scenario insights lead to more accurate – and not necessarily higher – capital requirements.

A bank that harmonizes its capital and liquidity stress tests can also positively change its accounting practices and strategic planning, yielding better results with lower cost and less impact on internal resources.

Alla Gil is the co‐founder and CEO of Straterix, which provides unique scenario tools for strategic planning and risk management. Prior to forming Straterix, she was the global head of Strategic Advisory at Goldman Sachs, Citigroup and Nomura, where she advised financial institutions and corporations on stress testing, ALM, long‐term risk projections and optimal capital allocation.