Overall:

The main responsibility is to provide data analytics, data visualization to improve portfolio performance and collection strategy. Play a vital role in enhancing our end-to-end collection lifecycle through data-driven insights, AI solutions, and strategic initiatives.

Roles and Responsibilities:

Data Analytics & Risk Insights

• Analyze customer behavior, delinquency patterns, and portfolio performance to support risk and collection strategy design.

• Provide segmentation, predictive analytics, and performance reporting to optimize collection performance and operational efficiency.

• Develop dashboards, scorecards, and data visualizations for management and operational teams.

Collection Strategy Optimization

• Design and recommend collection strategies across different delinquency buckets (early, mid, and late stage).

• Collaborate with the collection team to implement call prioritization models, treatment strategies, and agent allocation.

• Monitor roll rates, cure rates, and NPL trends to assess the effectiveness of current strategies and propose enhancements.

Innovation & AI in Collection

• Support the development and implementation of AI tools and automation (e.g., AI Collection Bot, SMS automation, predictive dialers).

• Analyze the impact of AI vs. human agent collection performance using data-driven metrics such as contact rate, promise-to-pay rate, and recovery rate.

Cross-Functional Collaboration

• Work closely with IT, Collection, and external vendors to support data integration, project execution, and strategic alignment.

Qualification :

• Bachelor’s or Master’s degree in Statistics, Data Science, Engineering, Finance, or related fields.

• 2–5 years of experience in credit risk analytics, collection strategy, or related roles in consumer finance, digital lending, or retail banking.

• Strong analytical mindset with experience in SQL, Python, R, or similar data tools.

• Familiarity with collection systems, scorecards, or AI tools for delinquency management is a plus.

• Strong communication skills and ability to turn complex data into actionable insights.

• Experience working in fast-paced, agile, or digital environments is an advantage.

• Good command of English (spoken and written).