This role is for one of the Weekday's clients

Salary range: Rs 1500000 - Rs 2000000 (ie INR 15 - 20 LPA)

Min Experience: 4+ years

Location: Bengaluru
JobType: full-time

We are looking for a Head of Risk to build an underwriting engine that safely approves Gen Z customers often declined by traditional lenders, operating at the speed of a consumer app. You will be instrumental in replacing current decision-making processes with a robust, owned, and explainable scorecard, leveraging alternative data and on-platform behavioural signals to maximise approval rates within acceptable NPA bands. This role is critical for the company's growth, focusing on innovative risk assessment and management for a new generation of consumers.

Requirements

🎯 Key Responsibilities

• Build a clean, owned, and explainable application scorecard to replace current credit decisioning processes, independent of partner NBFC overlays.
• Ingest alternative data via the Account Aggregator framework, including parsing bank statements, analysing UPI transaction patterns, merchant categories, average balance velocity, and salary credit regularity.
• Utilise device quality, PIN code vintage, and telecom data as proxies for income and stability.
• Incorporate on-platform behavioural signals such as browsing depth, Wishlist-to-purchase conversion, and time-on-app before application.
• Implement risk-tiered approvals, aiming to maximise approval rates within an acceptable NPA band.
• Build the infrastructure to capture, store, and model repayment behaviour data for the proprietary Behavioural Credit Bureau.
• Develop a feature store to make behavioural signals available to the scoring engine in real time.
• Own the model monitoring stack, including drift detection, cohort performance tracking, and vintage analysis.
• Develop the Limit Graduation Engine logic for progressive credit journeys, managing limits from small to large tickets automatically and at scale.
• Incorporate repayment timeliness scoring, purchase frequency, category migration signals, and external signals via AA refresh into the limit graduation logic.
• Implement automated limit upgrade triggers balanced against NPA guardrails.
• Develop a predictive pre-delinquency model to flag accounts likely to miss payments based on behavioural changes.
• Design and implement empathetic, digital-first early outreach strategies for pre-delinquency intervention.
• Define escalation logic that preserves brand relationships during stress events.
• Establish closed-loop feedback mechanisms to analyse intervention effectiveness across customer segments and delinquency stages.

🛠️ Required Skills

Credit Risk, Underwriting, Data Analysis, Machine Learning, Python, SQL, Account Aggregator Framework, RBI Digital Lending Guidelines, Explainable AI, Model Monitoring, Feature Engineering

✨ Good to Have

NBFC OperationsCollections StrategyBehavioural EconomicsStatistical ModellingAWS/GCP/Azure

🤝 Soft Skills

• Problem Solving
• Analytical Thinking
• Strategic Planning
• Communication
• Leadership
• Adaptability

Critical Skills

Credit Risk

Underwriting

Machine Learning

Account Aggregator Framework

🏢 About the Company

• Focus on building explainable and auditable credit models.
• Emphasis on data-driven decision making and innovation in risk assessment.
• Commitment to regulatory compliance and ethical lending practices.
• Culture of ownership and accountability in risk management.
• Iterative approach to model development and performance monitoring.

Must-have skills

Credit Risk, Underwriting, Data Analysis

Good-to-have skills

Problem Solving Analytical Thinking Strategic Planning Communication Leadership Adaptability