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For Accurate Capital Forecasts, Granularity Is Key

Copyright 2015 by the Risk Management Association (www.rmahq.org). All rights reserved. Used by permission.

About the Author: David Andrukonis has validated forecasting, valuation, and credit risk models for bank clients; developed risk-ranking methodology for client loan portfolios; and performed ABS valuations at RiskSpan. David is the author also of Pitfalls in Conventional Earnings-Based DSCR Measures (The RMA Journal).


To satisfy DFAST requirements and optimize shareholder value, banks need to make valid forecasts of their capital position under the DFAST-designated macroeconomic scenarios.

A capital forecast is an output of many inputs - inputs that vary in volatility and in the attention they receive from regulators. This article - based on work by my team at RiskSpan - will suggest that, among the components of a capital forecast, the provision for loan losses merits special attention. It will outline a framework for modeling loan losses accurately during all phases of the business cycle and demonstrate the beneficial impact of this approach on our ultimate capital forecast.

Figure 1 lays out the process by which a bank’s financial line items drive capital. Forecasting capital requires understanding and forecasting these components. The loss provision figure stands out as one of the most volatile drivers of capital and one of the most scrutinized after credit models failed to predict losses adequately during the financial crisis.

We base our assessment of the relative sensitivities of the different drivers of capital to macroeconomic stress on the DFAST 2015 aggregate results. We compared line item projections under the adverse scenario to those from the severely adverse scenario. As does the Fed’s DFAST report, we focus ...

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