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.
Risk Model Validation Services: Independent, unbiased validation services for proprietary and third-party risk models.
Credit Risk Advisory Services: Moody's Analytics credit risk advisory services enable faster, better informed credit decisions through a holistic and consistent assessment of risk.
Credit Risk Modeling: Moody’s Analytics delivers award-winning credit models and expert advisory services to provide you with best-in-class credit risk modeling solutions.
Economic Research: Moody's Analytics provides comprehensive economic analysis to help clients understand key economic drivers across all geographic levels.
Economic Scenarios: Moody's Analytics provides internally and globally consistent economic, regulatory, and custom scenarios.
Economic Forecasts: Moody's Analytics provides trusted macro and regional forecasts to help clients assess potential economic outcomes.
Stress Testing: Moody’s Analytics helps financial institutions develop collaborative, auditable, repeatable, and transparent stress testing programs to meet regulatory demands.
Portfolio Optimization: Quantify diversification benefits across portfolios and define risk types that inform risk management and active asset allocation decisions.
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.
This paper presents best practices for addressing PRA Consultation Paper CP29/16.
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.
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.
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.
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.