Credit risk - Scorecard Specialist

Reporting to: Head ERM

Role Purpose:

The Scorecard Specialist will design, govern, and optimize credit risk scorecards for a diverse portfolio covering Conventional, Islamic, Digital, and Nano-lending segments. The role is critical in transitioning the bank’s risk architecture into a high-velocity, data-driven engine that ensures Regulatory compliance and risk-adjusted returns in the MSME, Micro, and Nano lending.

Key Responsibilities

1. Scorecard Development

• Design and maintain application, behavioral, and collection scorecards for microfinance products.
• Develop specialized models for Nano-lending, focusing on high-frequency, low-ticket transactions and short-term delinquency cycles.
• Lead the migration from manual/rule-based underwriting to automated, data-led credit decisioning.

2. Digital & Nano-Lending Enablement

• Incorporate Alternative Data (telco/utility data, device metadata, transactional footprints) to drive Instant Credit.
• Embed scorecards into digital journeys (Mobile Apps, APIs) to facilitate Straight-Through Processing (STP).
• Optimize decision engines to handle the scale and velocity required for nano-credit products.

3. Governance & Regulatory Compliance

• Ensure all models comply with SBP Prudential Regulation standards for risk-sharing products.
• Establish a Model Risk Management (MRM) framework, including back-testing, stress testing, and periodic recalibration.
• Prepare technical documentation for SBP inspections and external audits.

Key Skills & Competencies

• Proficiency in handling high-volume data.
• Ability to balance the conservative nature of traditional banking with the rapid experimentation of a Fintech environment.

Education & Experience

• Bachelor’s or Master’s degree in Statistics, Data Science, Finance, or a related quantitative field.
• 5-7+ years in Credit Risk Modeling/Analytics.
• Proven track record in developing and managing scorecards.
• Experience in a bank-to-digital transformation or a Neo-bank startup environment.

Tools & Technical Exposure

• Expert level in Python, R, or SQL.
• Hands-on experience with Decision Engines and Loan Origination Systems (LOS).
• Experience with Big Data environments and real-time data processing for nano-decisions.

Success Metrics

• Maintaining NPL ratios within appetite for both high-risk Nano and traditional portfolios.
• Significant reduction in Turnaround Time (TAT) via automated digital scoring.
• 100% adherence to SBP mandates with zero major audit findings.