Airtel - Head - Portfolio Risk Analytics (8-12 yrs)

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

Employment Type: Full-Time

Experience: 8- 12 Years Experience

Level: 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:

- 812 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:

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.