Assistant Vice President - Collection

The candidate will have responsibilities across the following functions:

End-to-End Collection Strategy Design:

• Develop and optimise data-driven collection strategies across: Pre-due stage, Early bucket collections, Late bucket collections, recovery, and write-off management
• Design stage-wise treatment strategies to maximise resolution rates and minimise roll-forward.

Risk and Portfolio Analytics:

• Conduct in-depth portfolio analysis to identify risk trends, delinquency drivers, and behavioural patterns.
• Develop and monitor portfolio scorecards.
• Perform risk segmentation to enable differentiated strategy deployment.
• Analyse large historical datasets to extract actionable insights and improve collection efficiency.

Advanced Data and AI/ML Implementation:

• Develop and deploy AI/ML models for: Delinquency prediction, Roll rate forecasting, Recovery propensity, Contactability optimization
• Partner with data engineering teams for seamless data integration and model deployment.
• Evaluate model performance, stability, and recalibration needs.

Strategy Performance Monitoring:

• Design performance dashboards and KPIs for collection effectiveness.
• Monitor employee scorecards aligned with productivity, efficiency, and compliance.
• Conduct champion-challenger testing to continuously optimise strategies.

Big Data and Data Interpretation:

• Work with large, complex structured and unstructured datasets.
• Perform cohort analysis, roll-rate analysis, vintage analysis, and behavioural segmentation.
• Interpret historical performance data to refine future strategy design.

Stakeholder Collaboration:

• Collaborate with Risk, Operations, Product, Technology, and Senior Leadership teams.
• Present analytical findings and strategic recommendations to leadership.

Requirements:

• Master's or Bachelor's degree in Engineering, Computer Science, IT, Data Science, Statistics, Mathematics, Economics, or related quantitative discipline.
• 4-8+ years of relevant experience in collections analytics, credit risk, or financial services.

Technical Skills:

• Strong proficiency in: SQL, Python / R, Advanced Excel, Data visualisation tools (Power BI / Tableau).
• Deep understanding of: Portfolio scorecards, Risk segmentation methodologies, Employee performance scorecards, Roll rate and vintage analysis, AI/ML model development and validation, Big data ecosystems and data integration frameworks.

Core Competencies:

• Strong analytical and problem-solving skills.
• Strategic thinking with business acumen.
• Deep understanding of credit risk and collections lifecycle.
• Ability to interpret complex datasets and convert insights into executable strategies.
• Excellent communication and stakeholder management skills.

Preferred Attributes:

• Experience in NBFC/Banking/FinTech collections environment.
• Exposure to regulatory compliance in collections.
• Hands-on experience with large-scale portfolio management.
• Proven track record of driving measurable improvement in collection efficiency and recovery rates.