Juan M. Licari, PhD, is Chief International Economist with Moody's Analytics. As the Head of Economic and Credit Research in EMEA, APAC and Latin America, Juan and his team specialize in generating alternative macroeconomic forecasts and building econometric tools to model credit risk portfolios.

Juan and his team develop and implement solutions that explicitly connect credit performance data to the underlying economic cycle, allowing portfolio managers to plan for forward-looking macroeconomic conditions and stressed scenarios. An experienced modeler, Juan has designed and implemented several IFRS 9, A-IRB, ICAAP, and stress-testing platforms for major institutions. In addition Juan regularly publishes research and presents at Moody's Analytics and industry events. He holds a PhD and an MA in economics from the University of Pennsylvania and graduated summa cum laude from the National University of Cordoba in Argentina.

Published Work

Dynamic Model-Building: A Proposed Variable Selection Algorithm

In this article, we propose an innovative algorithm that is well suited to building dynamic models for credit and market risk metrics, consistent with regulatory requirements around stress testing, forecasting, and IFRS 9.

January 2018

U.K. Residential Mortgages Risk Weights: PRA Consultation Paper CP29/16

This paper presents best practices for addressing PRA Consultation Paper CP29/16.

October 2016

Probability-Weighted Outcomes Under IFRS 9: A Macroeconomic Approach

In this article, we discuss development of a framework that addresses the forward-looking and probability-weighted aspects of IFRS 9 impairment calculation using macroeconomic forecasts. In it, we address questions around the practical use of alternative scenarios and their probabilities.

June 2016

Complying with IFRS 9 Impairment Calculations for Retail Portfolios

This article discusses how to address the specific challenges that IFRS 9 poses for retail portfolios, including incorporating forward-looking information into impairment models, recognizing significant increases in credit risks, and determining the length of an instrument's lifetime.

June 2016

Advanced Estimation and Simulation Methods for Retail Credit Portfolios: Frequentist vs. Bayesian Techniques

In this article, we compare the results of estimating retail portfolio risk parameters (e.g., PDs, EADs, LGDs) and simulating portfolio default losses using traditional – frequentist – methods versus Bayesian techniques.

December 2015

Multi-Period Credit Risk Analysis: A Macro-Scenario Approach Presentation Slides

In this presentation, Dr. Juan Licari of Moody's Analytics will present an innovative framework for stochastic scenario generation that allows risk managers and economists to build multi-period environments, integrating conditional credit and market risk modeling to meet dynamic stress testing needs.

December 2015