Nittin Chavan

About Nittin Chavan

A conscientious and results-driven Analytics Consultant with 6.5+ years of proven experience in Credit Risk Modeling, Business Reporting, and Data Analytics across Retail and Wholesale Banking, Risk Management, and Financial Services.I specialize in transforming complex data into meaningful insights that support both regulatory compliance and strategic decision-making. My experience spans across the development, validation, and monitoring of PD (Probability of Default), LGD (Loss Given Default), and EAD (Exposure at Default) scorecard models, aligned with IFRS 9, IRB, and CCAR frameworks.I’ve worked on loss forecasting and Expected Credit Loss (ECL) computation for both retail and wholesale portfolios, applying forward-looking macroeconomic scenarios under IFRS 9 and supporting capital adequacy assessments through Expected and Unexpected Loss calculations under IRB. I’ve also supported CCAR stress testing, projecting losses under baseline and severely adverse economic conditions.My work includes model monitoring and enhancement overlays, ensuring model performance through regular scenario analysis, sensitivity testing, benchmarking, backtesting, and evaluating discrimination and stability metrics. I’ve built automated reporting solutions and dashboards that help leadership teams monitor delinquency trends, portfolio risk movements, and model performance.Known for strong business acumen and technical depth, I’ve authored regulatory-compliant model documentation, contributed to audit and regulatory interactions, and mentored junior analysts across projects.Proficient in SAS, SQL, Python, R, Tableau, Power BI, and Excel, I’m passionate about leveraging data to drive smarter risk decisions and ensure long-term financial resilience.

Experience

1. Manager

   JPMorganChase

   Dec 2021 — Present · Mumbai, IN

   Analyze structured and unstructured loss forecasting data to provide insight into activities for managing risk, improving business performance, or predicting future behaviour of customers to drive marketing campaigns Developed and validated statistical models, including Probability of Default (PD), Loss Given Default (LGD), and Exposure at Default (EAD), to assess credit risk and optimize lending decisions. Extensive knowledge and experience in IFRS9, IRB, and conducting stress testing and forecasting exercises within retail banking Skilled in managing the entire lifecycle of credit risk models, including design, development, deployment, monitoring, and performance tracking Conducted data analysis to evaluate credit risk trends and support strategic decision-making Engage stakeholders in defining self-service analytics, dashboards, and actionable enterprise business intelligence reports Perform data analysis to deliver a platform for decision making pertaining to a variety of business issues Ensured compliance with regulatory capital requirements by conducting thorough data analytics and validation processes, leading to accurate capitaladequacy reporting and risk assessment Analyzed portfolio trends and recommended changes in credit policies, leading to a 20% reduction in high-risk exposures and minimizing potentiallosses. Designed and implemented enhanced risk models and robust monitoring frameworks, resulting in a 15% reduction in default rates by proactivelyidentifying high-risk accounts and deploying targeted interventions Designed tailored repayment plans for delinquent customers, improving retention rates by 25% and recovering $1.5M in outstanding debt. Implemented dynamic monitoring systems for early detection of delinquency trends, enabling faster corrective actions that decreased delinquency rates by 10% in six months

Education

• Lokmanya Tilak College of Engineering

  Bachelor of Engineering - BE, Electrical

  2014 — 2018