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Regulators are placing increased emphasis on the rigor by which banks model their income and balance sheet projections.

In this webinar, Dr. Brian Poi, Director, Economic Research, demonstrates how forecasts based on industry data can be used to generate an objective benchmark for internally generated forecasts.

Related Insights

Improved Deposit Modeling: Using Moody's Analytics Forecasts of Bank Financial Statements to Augment Internal Data

In this article, we demonstrate how to combine our forecasts of bank financial statements with internal data to produce forecasts that better reflect the macroeconomic environment posited under the various Comprehensive Capital Analysis and Review scenarios.

August 2016 Pdf Dr. Tony HughesBrian Poi

Improved Deposit Modeling: Using Moody's Analytics Forecasts of Bank Financial Statements to Augment Internal Data

We demonstrate how our service can be used to produce more realistic forecasts of income and balance sheet statements.

July 2016 Pdf Dr. Tony HughesBrian Poi

Forecasting Income Statements & Balance Sheets Using Industry Data

In this webinar, Dr. Brian Poi, Director, Economic Research, demonstrates how forecasts based on industry data can be used to generate an objective benchmark for internally generated forecasts.

October 2015 Pdf Brian Poi

Improved Deposit Modeling Using Moody's Analytics Pre-Provision Net Revenue Factors Library to Augment Internal Data

In this article we demonstrate how to combine the PPNR Factors Library with internal data to produce forecasts that better reflect the macroeconomic environment posited under the various U.S. CCAR scenarios.

July 2015 Pdf Brian Poi

Multicollinearity and Stress Testing

Multicollinearity, the phenomenon in which the regressors of a model are correlated with each other, apparently causes a lot of confusion among practitioners and users of stress testing models. This article seeks to dispel this confusion.

May 2015 WebPage Dr. Tony HughesBrian Poi

Stress Testing and Strategic Planning Using Peer Analysis

Banks face the difficult task of building hundreds of forecasting models that disentangle macroeconomic effects from bank-specific decisions. We propose an approach based on consistently reported industry data that simplifies the modeler’s task and at the same time increases forecast accuracy.

Previewing This Year's Stress Tests Using the Bank Call Report Forecasts

Risk modelers at banks often feel pressure to produce conservative, as opposed to strictly accurate, forecasts of a bank’s resilience in times of stress. Regulators typically frown on capital plans that have even the barest whiff of optimism[1].