Douglas heads the Moody’s Analytics Single Obligor Research Group. This group produces credit risk metrics of small businesses, medium-sized enterprises, large corporations, financial institutions, and sovereigns worldwide. The group’s models are used by banks, asset managers, insurance companies, accounting firms, and corporations to measure name-specific credit risk for a wide variety of purposes. We measure credit risk using information drawn from financial statements, regulatory filings, security prices, derivative contracts, and behavioral and payment information. Previously, Doug was a principal at William M. Mercer, Inc. He has a PhD from Columbia University and a BA from Oberlin College, both in economics.

Validating and Understanding a Highly Nonlinear Machine Learning Model

Presentation from Moody’s Analytics Summit 2018

November 2018

This presentation provides an overview of the components, aspects, and validation of a highly nonlinear machine learning model.

Published Work
Whitepaper

Sovereign & Size-Adjusted EDF-Implied Rating Template (for Private Firms)

RiskCalc™ EDF™ (Expected Default Frequency) values and agency ratings are widely used credit risk measures. RiskCalc EDF values typically measure default risk for private companies, while agency ratings are only available for rated companies. A RiskCalc EDF value measures a company's standalone credit risk based on financial statement information, while an agency rating considers qualitative factors such as Business Profile, Financial Policy, external support, and country-related risks. Moody's Analytics new Sovereign & Size-Adjusted EDF-Implied Rating Template combines RiskCalc EDF values with additional factors to provide a rating comparable to agency ratings for private companies. The new template applies to RiskCalc EDF values across numerous geographies and regulatory environments. With the new template, users can generate a rating more comparable to an agency rating than RiskCalc EDF values or EDF-implied ratings. Analyzing data from 3,900+ companies in 60+ countries, we find that sovereign rating and total asset size, in addition to EDF value, have a statistically significant impact on an agency rating — our quantitative template incorporating these three variables reliably estimates agency ratings in a robust fashion.

December 2018
Webinar-on-Demand

Identifying At-Risk Firms in Your Private Firm Portfolio

Identifying At-Risk Firms in Your Private Firm Portfolio

October 2018
Whitepaper

Features of a Lifetime PD Model: Evidence from Public, Private, and Rated Firms

With the new CECL and IFRS 9 requirements, we see an increased need for lifetime probability of default models. In this document, we formally investigate and summarize the term structure properties consistently seen across public, private, and rated firms. We observe that the default rate for “good” firms tends to increase over time, while the default rate for “bad” firms decreases over time, an indication of the mean-reversion effect seen with firms' default risk.

May 2018
Whitepaper

Features of a Lifetime PD Model: Evidence from Public, Private, and Rated Firms

With the new CECL and IFRS 9 requirements, this document formally investigates and summarizes the term structure properties consistently seen across public, private, and rated firms.

May 2018
Whitepaper

Combining Financial and Behavioral Information to Predict Defaults for Small and Medium-Sized Enterprises: A Dynamic Weighting Approach

This note presents the first tool that assesses borrowers' credit risk using a scientific method that leverages both financial and behavioral information.

September 2017
Whitepaper

Combining Financial and Behavioral Information to Predict Defaults for Small and Medium-Sized Enterprises – A Dynamic Weighting Approach

One large challenge lenders currently face is how to combine different types of information into metrics that can support good business decisions. Currently, the banking industry uses two primary types of information — financial information and behavioral information — independently, to assess risk. Financial information includes Income Statement, Balance Sheet, Cash Flow, and Financial Ratios. Behavioral information includes spending and payment patterns, among others. Both types of information provide unique insights, but, to date, they have not been combined to generate one comprehensive risk metric for commercial use.

September 2017