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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

Producing Objective Income & Balance Sheet Forecasts Presentation Slides

In this presentation, we demonstrate how forecasts based on industry data can be used to generate an objective benchmark of a bank's performance under baseline and stressed scenarios. We demonstrate results though case study of regional banks, peer groups, and larger CCAR-sized institutions.

November 2017 Pdf Brian Poi

Producing Objective Income & Balance Sheet Forecasts

In this webinar, we demonstrate how forecasts based on industry data can be used to generate an objective benchmark of a bank’s performance under baseline and stressed scenarios. We demonstrate results though case study of regional banks, peer groups, and larger CCAR-sized institutions.

November 2017 WebPage Brian Poi

Improved Deposit Modeling: Using Moody's Analytics Forecasts of Bank Financial

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

Forecasting Income Statements & Balance Sheets Using Industry Data

In this presentation, 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

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

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].

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.