Welcome to the My Home Page
This sight is dedicated to my research interests:
I am a quantitative practitioner and researcher in the field of risk modeling and management. I am
currently affiliated with PNC Financial Services, as an SVP - Lead Expert in Quantitative Modeling and
Analytics in the Analytics & portfolio Management - Model Development division. I am a subject matter
expert, advising bank stakeholders on risk modeling issues and prudential regulation. I also conduct
independent research in finance and participate in industry thought leadership initiatives as a
quantitative modeling expert. Currently I am involved in various research projects and thought
leadership in CECL, scenario generation, integrated stress testing, model risk, wholesale credit risk,
operational risk and asset price bubbles. Prior research spanned the economics of financial
distress, building loan level econometric models of Basel parameters (Loss Given Default, Exposure
and Probability of Default), studying returns on defaulted debt, calibrating capital models with
systematic recovery risk to historical default and loss data, a generalized pair copula framework for
risk aggregation, Bayesian modelling of credit risk and rating transitions, prediction of bankruptcy
resolution and analysis of the determinants of financial distress. I also study various topics in finance,
such as correlation forecasting and modelling of CDS spreads. I hold a doctorate in business from
the City University of New York in finance and I am a Chartered Financial Analyst.
Topics that I am interested in include:
Miscellaneous: Related Interests, Hobbies,etc.
On my spare time I enjoy studying the history of economic and finance thought, recreational
programming / development, an extensive music collection and running.
Current industry projects include wholesale credit model development (PD multi-calibration and
predictive credit risk models for financial institutions); model risk management and risk policy, leading
1st line model validation & quality control for model development; machine learning modeling for LGD
in partnership with Global Credit Data..
Current research includes analysis of modeling assumptions in the CECL accounting standard;
the impact of asset price bubbles on credit and liquidity risk quantification; scenario generation for
stress testing incorporating heavy tailed distributions through a regime switching methodology; a
framework for integrated stress testing that includes risk appetite and capital optimization.
Risk modelling methodologies and analytics
Jacobs Risk Advisory Services, Inc.: Risk Modeling, Methodologies and Analytics
Economic capital modeling and aggregation
Statistical/econometric techniques, including machine learning and AI
Credit derivatives and loan valuation
Credit risk, stress testing and CECL