Credit Risk Strategy

2 weeks ago

Bengaluru Gurugram, India Kriyah Consulting Full time ₹ 8,00,000 - ₹ 24,00,000 per year

Job Summary:

We are looking for an Analytics Professional (48 years) with strong expertise in Credit Risk Strategy and Banking Analytics. The role combines credit risk policy analytics, portfolio strategy, and advanced data analytics to drive smarter decision-making in unsecured lending portfolios (Credit Cards, BNPL, POS Lending).

The ideal candidate is hands-on with SQL and Python and has experience in credit risk analytics, policy development, portfolio tracking, and advanced data insights. This role requires working with senior stakeholders to influence risk strategy, optimize acquisition & collections policies, and deliver actionable insights through data.

Key Responsibilities:

  • Develop and enhance credit risk strategies for products such as Credit Cards, BNPL, and POS Lending.
  • Conduct portfolio analytics, policy reviews, and performance tracking across acquisition, line management, collections, and fraud risk.
  • Provide data-driven recommendations to optimize risk policies, funnel performance, and post-issuance loan behavior.
  • Analyze large, complex datasets using SQL and Python to identify trends, patterns, and risk drivers.
  • Build and automate dashboards & reports (Power BI / Tableau) to provide actionable insights to risk teams and senior leadership.
  • Support strategic and tactical initiatives for US-based banks' Risk Teams.
  • Translate analytical findings into business-friendly presentations and risk strategies for technical and non-technical stakeholders.
  • Partner with cross-functional teams in risk management, operations, and policy analytics to deliver impact.
  • Mentor and guide junior analysts, supporting skill development in credit risk and analytics.

Required Skills & Qualifications:

  • Experience: 4–8 years in Analytics / Decision Science, preferably in BFSI (Banking & Financial Services).
  • Technical Skills: Strong SQL & Python (mandatory); exposure to SAS, PySpark, ML techniques is a plus.
  • Domain Expertise: Credit Risk Strategy, Portfolio Analytics, Policy Development, Risk Concepts (delinquencies, pre-payments, loss curves, collections, acquisition scorecards).
  • Tools: Tableau/Power BI for dashboarding and reporting automation.
  • Business Acumen: Strong understanding of Retail Banking / Lending / Risk Management.

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