Intern, Internal Ratings Management, Global Risk Management
Toronto, Ontario, Canada
● Responsible for migration of analytical capability from SAS to Python by developing models (Back testing of (PD) per portfolio, Risk-weighted assets, etc.) in Python that includes the entire life cycle of projects – data extraction from RDBMS, data cleaning, exploratory data analysis, transitioning from framework of BASEL III, and modelling. Delivered recommendations/alternatives to address problems faced by SAS● Developed Internal Ratings (IG) model for Transportation Infrastructure borrowers. Introduced qualitative factor to address external factors. Automated the validation process using Python which reduced the manual effort of comparing various files● Validated various bank models such as PD (Probability of Default), LGD (Loss Given Default), EAD (Exposure After Default) for retail/wholesale/transportation models. Validations include testing in areas of data, BASEL III framework, outcome analysis, process accuracy, and governance ● Liaison with External consortiums such as GCD (Global Credit Data) to gather historical defaults data and work closely across multi-departments to capture additional credit data collection for stress testing, back testing models, Benchmarking of current predicted PD, EAD and LGD for named counterparties and specific banking book clusters. It helped in fostering impressive time and relationship management skills ● Created GUI automation tool in Python to compare tables from RDBMS and extract/display the rows where data has changes. This tool is widely used to check the integrity of data being used and has reduced the time lag of validation process● Showed excellent communication and quick learning skill by leading multiple presentations to teams of managers from different departments. Showcased great team player characteristics as group work required coordination with team members and helped in brining different ideas to the table and stepped up where the team was lagging behind