Head of Collections Analytics and Strategy

View full description

Requirements:

• 5+ years of experience in collections analytics, credit risk, or a similar data-driven strategy role, with a strong track record of performance optimization in unsecured lending.
• At least 2 years in a leadership or team management role, with experience in leading and developing cross-functional teams.
• Experience with managing large-scale, multi-faceted collections strategies, including call centers, customer engagement, and ECL modeling.
• Proficiency in SQL, Python, or similar data extraction and manipulation tools for handling large datasets.
• Strong experience with statistical modeling and analytics tools to develop and improve ECL models and optimize recovery strategies.
• Expertise in cohort analysis, book analysis, and segmentation strategies, understanding the nuances between these approaches and their impact on recovery performance.
• Ability to apply predictive analytics and build actionable strategies to improve key KPIs, including recovery rates, aging of debt, and delinquency rates.
• A deep understanding of the relationship between underwriting decisions and collections performance, and how those impact the recovery process.
• Ability to isolate and quantify the effects of underwriting vs. collections strategies on performance, using data to drive improvements in both areas.
• Experience optimizing recovery strategies across different segments of a consumer loan portfolio.
• Ability to think strategically about collections while being hands-on in analyzing the data and understanding the granular details (SQL queries, statistical models).

Responsibilities:

• Lead the analytics and strategy for optimizing collections processes across the unsecured lending portfolio.
• Develop, maintain, and refine ECL models (Expected Credit Loss) to predict and optimize recovery rates.
• Use cohort analysis and book analysis to assess performance, measure recovery effectiveness, and adjust strategy based on trends.
• Drive A/B testing, test-learn-iterate approaches to improve collections strategies, optimizing both short-term recovery and long-term customer relationships.
• Understand how different data dimensions affect each other and synthesize findings to create actionable insights.
• Perform data extraction and analysis (SQL, Python, or other analytics tools) to monitor collections performance, ensuring accuracy and completeness in reporting.
• Build sophisticated models to isolate recovery rates impacted by underwriting decisions vs. collections efforts.
• Conduct in-depth analyses to understand portfolio behavior and segment customers based on recovery likelihood and repayment capacity.
• Evaluate the relationship between credit underwriting decisions and recovery performance, identifying areas for improvement in both functions.
• Manage a cross-functional team of analysts and collections specialists, ensuring they have the tools, training, and support to optimize performance.
• Continuously refine and enhance the recovery rates across different segments, ensuring alignment between underwriting, collections, and customer service.
• Work closely with the call center teams, providing guidance on the tonality of calls, communication approaches, and overall strategy for handling collections.
• Develop and track key performance metrics for the team, providing regular feedback and leading initiatives to improve operational efficiency.
• Ensure the collection strategy aligns with broader business goals, focusing on profitability, risk management, and customer experience.
• Manage and optimize the entire collections lifecycle, from initial outreach through final resolution, while balancing risk and customer satisfaction.
• Implement innovative strategies to improve recovery rates, considering customer segmentation, call center strategies, and collection tools.
• Collaborate closely with key internal stakeholders, such as the underwriting team, data science teams, marketing, and senior leadership, to refine the collections strategy and align on business objectives.
• Effectively communicate insights and recommendations to senior leadership, including reports on performance, improvements, and optimizations.
• Advocate for a test-learn-iterate mindset across departments to drive data-informed decisions that continuously improve collections outcomes.