Head of Risk

Head-Portfolio Risk Analytics

About the Role As GM/AVP with Airtel Money Limited, you will own the analytical engine that keeps our unsecured digital loan book performing at scale. This is a senior leadership role that sits at the intersection of risk strategy, advanced analytics, and business growth.

Location-Gurgaon Full-Time

8–12 Years Experience GM / AVP Level

1.Portfolio Risk Ownership

• End-to-end portfolio analytics: Own the full analytical lifecycle of the unsecured digital loan book from origination quality to vintage performance, delinquency roll rates, and loss forecasting.
• Risk KPI framework: Define, build, and continuously evolve KPIs and dashboards that give real-time visibility into portfolio health, concentration risk, and early warning signals.
• Vintage & cohort analysis: Lead deep cohort studies to understand how borrower behaviour evolves over time across product types, acquisition channels, and credit tiers.
• Stress testing & scenario modelling: Build forward-looking stress test frameworks to assess portfolio resilience under adverse macro and credit conditions.

2.Advanced Credit & Behavioural Analytics

• Predictive modelling: Design, develop, and deploy best-in-class models for default probability, delinquency forecasting, behavioural scoring, and ECL estimation.
• Scorecard development: Drive and monitor application, behaviour, and collection scorecards with rigorous validation, back-testing, and champion-challenger frameworks.
• Early warning systems: Develop and operationalise EWS triggers that enable proactive collection and risk mitigation before accounts deteriorate.

3.Data Infrastructure & Large-Scale Analytics

• Big data fluency: Work confidently with large-scale, high-velocity data environments, structured and unstructured, typical of a digital lending business processing millions of transactions.
• Data pipeline ownership: Build & maintain robust pipelines for risk metrics computation, model scoring, and MIS reporting at scale.
• Data quality governance: Establish and enforce data standards and governance practices to ensure analytical integrity across all risk functions.

4.Credit Policy & Risk Strategy

• Policy co-creation: Partner with the NBFC credit team to continuously refine and improve underwriting policies translating portfolio analytics into sharper approval criteria, pricing bands, and limit strategies.
• Approval rate optimisation: Identify systematic false-rejection patterns and work with credit teams to improve approval rates on genuinely creditworthy borrowers without expanding risk appetite.
• Product risk advisory: Provide pre-launch risk assessment and post-launch performance monitoring for all new digital lending products.
• Collections strategy support: Translate portfolio analytics into actionable collection segmentation strategies for early, mid, and late-stage delinquency.

5.Leadership & Cross-Functional Collaboration

• Team building: Lead and mentor a team of risk analysts and data scientists-setting analytical standards, managing delivery, and developing talent.
• Stakeholder management: Translate complex analytical outputs into clear business narratives for CXO, Board etc.
• Product & tech collaboration: Partner with product and technology teams to embed risk analytics into decisioning systems, APIs, and customer journeys.

6.Regulatory Compliance & Governance

• RBI compliance: Ensure all models, analytics, and reporting comply with RBI guidelines, NBFC prudential norms, and consumer lending regulations.
• Model governance: Maintain comprehensive model documentation, validation records, and audit trails for internal and regulatory review.
• Regulatory reporting: Own portfolio reports & risk disclosures for regulatory submissions & board-level governance.

Minimum Qualifications & Requirements 1.Education

• Bachelor's or Master's degree in Statistics, Mathematics, Economics, Engineering, or quantitative Finance.
• MBA from a premier institution with strong quantitative specialisation is highly preferred.

2.Experience

• 8–12 years of progressive experience in credit risk analytics, with a clear track record of owning portfolio risk in a bank, NBFC, or fintech.
• Mandatory domain: Prior hands-on experience in unsecured digital lending (PL, BNPL or digital credit lines)

3.Technical & Analytical Skills

• SQL (Advanced)/ Python, Statistical modelling: Logistic regression, Decision Trees, and ensemble methods.
• Data visualisation: Tableau, Power BI, or equivalent

4.Core Competencies

• Systems thinking: Ability to see the full credit lifecycle: origination to write-off and understand how decisions at each stage affect the next.
• Risk intuition: Strong instinct for identifying what a number means in context, not just what it says.
• Executive communication: Ability to distil complex analytical findings into sharp, actionable insights for senior leadership and boards.
• Speed and rigour: Operates with both analytical precision and the urgency required in a fast-scaling digital lending business.

5.Soft Skills

• Strong leadership presence with the ability to influence decisions across functions without direct authority.
• High ownership mindset- treats portfolio performance as a personal accountability not just a reporting function.
• Comfortable with ambiguity, able to structure problems independently and drive to conclusions.
• Collaborative and intellectually curious with a genuine interest in building something at scale.

Preferred Attributes

• Experience with automated underwriting or real-time decisioning systems integrated with risk models.
• Familiarity with advanced IRB approaches, IFRS 9 provisioning models, or ECL frameworks.
• Prior exposure to telecom data, alternate data, or bureau-thin file underwriting strategies.
• Experience with A/B testing, experimental design, and causal inference in a credit context.
• Knowledge of co-lending model frameworks and LSP-NBFC risk-sharing structures.
• Understanding of collection analytics, recovery modelling, and post-write-off strategies.

What We Are Looking For- In One Line A sharp, senior risk analytics leader who has owned an unsecured digital loan book end-to-end, is fluent in large-scale data environments & can convert portfolio intelligence into business decisions that drive profitable, sustainable growth.