Manager - ECL

ECL – Expected Credit Loss Bangalore/Mumbai, India

2 – 8 Years

Risk & Analytics

Full-Time

ABOUT PAYU FINANCE

PayU Finance is a leading fintech lending company, part of the global PayU Group, committed to democratising financial services across emerging markets. We leverage cutting-edge technology and data-driven insights to provide innovative credit products to individuals and businesses. Our Risk & Analytics team sits at the heart of our lending business, ensuring responsible growth through rigorous credit risk frameworks, regulatory compliance, and advanced quantitative modelling.

ROLE OVERVIEW

We are looking for a highly motivated and analytically rigorous Senior / Lead Risk Analyst to own the end-to-end Expected Credit Loss ( ECL ) process under Ind AS 109 / IFRS 9. You will lead monthly ECL calculations, build and validate quantitative credit models (PD, LGD, EAD), drive regulatory and audit readiness, and champion automation initiatives to modernise our credit risk reporting stack. This is a high-visibility role with direct interaction with Finance, Risk Management, Regulators, and senior leadership.

KEY RESPONSIBILITIES

Monthly ECL Calculation & Data Validation

Accurately compute monthly Expected Credit Loss ( ECL ) per Ind AS 109 / IFRS 9 or relevant regulatory standards.

Collect, clean, and validate data inputs to ensure accuracy, completeness, and consistency across systems.

Analyse data quality, proactively identify anomalies or gaps, and implement corrective actions.

Perform reconciliations, sensitivity analyses and back testing to validate ECL results.

Deliver monthly ECL outputs within defined deadlines to support financial reporting and management decisions.

02 ECL Model Development & Validation

Design and develop quantitative ECL models incorporating PD (Probability of Default), LGD (Loss Given Default), and EAD (Exposure at Default) parameters.

Conduct rigorous model validation to assess performance, stability, and regulatory compliance.

Update and recalibrate models in response to new data, market changes, or evolving regulations; maintain version control.

Conduct scenario and sensitivity analyses for macroeconomic impact assessment on credit provisions.

Document methodologies, model assumptions, and validation results to ensure transparency and audit readiness.

Collaborate with data scientists, risk analysts, and IT teams for model enhancement and system integration.

03 Cross-Functional Collaboration

Liaise with the Risk Management team to align ECL models with the company's risk appetite and credit risk frameworks.

Partner with Finance to ensure ECL estimates are consistent with financial reporting requirements and compliance obligations.

Respond to data and reporting requests from rating agencies, banking partners, and key stakeholders.

Facilitate knowledge-sharing workshops to improve ECL calculation accuracy and awareness across teams.

Serve as the subject matter expert and primary point of contact for queries on ECL methodologies, assumptions, and data interpretation.

04 Regulatory & Audit Coordination

Act as the primary liaison during internal and external audits, supplying documentation and clarifications related to ECL models, NPA classification, and asset quality.

Prepare timely and accurate responses to regulatory enquiries; submit credit risk and provisioning data per prescribed timelines.

Implement remedial actions arising from audit findings and regulatory directives to strengthen compliance posture.

Stay current on regulatory developments (RBI guidelines, Ind AS updates, IFRS 9 amendments) affecting ECL reporting and asset classification.

Support regulator reviews by ensuring data transparency, methodological consistency, and comprehensive audit trails.

05 Reporting & Process Automation

Prepare detailed ECL reports for management, auditors, and regulators, highlighting key insights, trends, and risk indicators.

Maintain comprehensive documentation of processes, calculations, and underlying assumptions for sustained audit readiness.

Lead automation initiatives for ECL calculations and management reporting using SQL, Python, and BI tools.

Continuously evaluate existing processes and identify opportunities to improve accuracy, speed, and operational reliability.

Monitor and report on automation benefits including time savings, error reduction, and enhanced compliance outcomes.

QUALIFICATIONS & EXPERIENCE

Education: Bachelor's or Master's degree in Finance, Statistics, Mathematics, Economics, Engineering, or a related quantitative discipline. CA / FRM / CFA qualification is a strong advantage.

Experience: 4 – 7 years of hands-on experience in credit risk modelling, ECL /IFRS 9 implementation, or provisioning within a bank, NBFC, or fintech lending institution.

Technical Skills: Proficiency in SQL and Python (or R) for data analysis and model development. Familiarity with BI tools (Power BI / Tableau) and Excel-based financial modelling.

Domain Knowledge: Deep understanding of Ind AS 109 / IFRS 9 ECL framework, PD-LGD-EAD modelling, NPA classification norms, and RBI regulatory requirements for provisioning.

Soft Skills: Strong analytical thinking, attention to detail, excellent written and verbal communication, and ability to present complex quantitative concepts to non-technical stakeholders.

Preferred: Prior experience in fintech or digital lending; exposure to credit bureau data, collections risk, or early warning systems is a plus.

WHY JOIN PAYU FINANCE?

High-impact role with direct visibility to senior leadership and regulators.

Opportunity to shape and modernise the ECL framework in a fast-growing fintech.

Be part of a global fintech group operating across 50+ markets.

Culture of innovation, data-driven decision-making, and continuous learning.

Competitive compensation, performance bonuses, and comprehensive benefits.

Collaborative, inclusive, and intellectually stimulating work environment.