Kissht - Collection Analytics & Modeling Role
2 weeks ago
Description:Job Overview:- The role involves developing and optimizing scorecards, early warning models, and segmentation frameworks to improve recovery rates and reduce delinquencies.- You will collaborate with risk, operations, and product teams to design data-backed strategies, run A/B tests, and track key collection KPIs.- Strong skills in SQL, Python, and BI tools are essential, along with a solid understanding of collection workflows and analytics-driven decision-making.Key Responsibilities:- Develop, monitor, and enhance collection scorecards and early warning models to predict delinquency and optimize recovery efforts.- Perform vintage and roll-rate analyses, flow rate tracking, and lag-based recovery modelling.- Design segmentation strategies for bucket-wise, geography-wise, and product-wise collections.- Partner with operations to run championchallenger strategies and A/B tests to optimize field and digital collections.- Build dashboards to track collection KPIs, including DPD movement, cure rates, and agency performance.- Work closely with credit policy and risk to ensure collection strategies align with risk appetite and loss forecasts.- Collaborate with data engineering and product teams to enable real-time portfolio insights and collector performance analytics.Required Skills:- Strong proficiency in SQL, Python, and Excel for data analysis and automation.- Experience with statistical modelling, logistic regression, and machine learning techniques for risk prediction.- Hands-on with BI tools (Power BI / Tableau / Looker) for visual analytics.- Understanding of collection operations workflows, dialler strategies, and agency management KPIs.- Ability to translate insights into actionable business recommendations.Preferred Qualifications:- 4-10 years of experience in collections or risk analytics within consumer lending.- Exposure to digital collection platforms, tele-calling optimization, or field force productivity models.- Educational background in Statistics, Mathematics, Economics, Engineering, or related field. (ref:iimjobs.com)
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