Collections Risk Analyst

Job Description

About Digni Fi: Digni Fi is a mission-driven company whose Point-of-Sale financing solution helps 2,000+ partners increase revenue, drive accessory orders, and decrease deferred repairs. By partnering with dealerships and service centers, Digni Fi offers financing products at the point of sale for consumers to finance auto repairs, service, parts, accessories, maintenance packages and more. Our mission is to help auto dealers and service centers grow by offering their customers innovative, inclusive financing.

Our vision is to make financing for the needs of daily life accessible and inclusive. Come join us on this exciting ride!

About the Role: Ready to turn collections data into insights that help our team succeed?

As a Digni Fi Collections Risk Analyst, you’ll support collections performance and strategy through portfolio analytics and performance reporting. You’ll analyze delinquency trends across stages and vintages, evaluate multi-channel contact strategies (including AI voice agents), and provide data-driven insights that help optimize recovery outcomes while maintaining our commitment to customer respect. Working with SQL and Python daily, you’ll design performance analyses, support A/B testing of new technologies and approaches, and collaborate with Collections leadership, Credit Risk, and Compliance to identify what’s working and where strategies can improve.

This role offers significant exposure to AI-enabled collections technology while building deep expertise in consumer lending risk management as we help customers navigate unexpected vehicle repair costs.

What You Will Do:

• Produce recurring collections performance reporting (delinquency migration, roll rates, cure rates, recovery rates, net credit loss) across stages and vintages.
• Analyze cohort and vintage performance to identify emerging risks, behavior shifts, and early warning indicators.
• Support creation of executive-level summaries for collections leadership.
• Maintain, validate, and enhance reporting accuracy and data controls.

• Analyze performance of AI voice agents using metrics such as RPC, completion rates, escalation rates, sentiment scoring, intent recognition, and FCR.
• Support A/B testing of contact strategies, voice agent configurations, channel sequencing, timing, and messaging frameworks.
• Evaluate multi-channel collections performance (voice, SMS, digital self-service) to support contact strategy optimization.
• Provide analytical support for cost-benefit analysis, ROI, and performance trends for AI-enabled collections tools.
• Identify potential compliance concerns by reviewing call/interaction performance trends and escalating when appropriate.

• Segment delinquent accounts using payment behavior, prior outcomes, risk indicators, and exposure/Value-at-Risk.
• Analyze propensity-to-pay patterns to distinguish self-cure accounts from high-risk segments.
• Support strategy recommendations for treatment paths, contact intensity, channel selection, hardship eligibility, and escalations.

• Contribute to analysis of delinquency trends, roll rates, and recovery curves for loss forecasting and CECL-related inputs.
• Support forecasting variance analysis and capacity planning discussions.
• Provide data and insights that connect collections performance to broader credit and financial metrics.

• Analyze operational performance (RPC rates, contact rates, promise-to-pay kept rates, agent/AI productivity, campaign outcomes).
• Identify bottlenecks or opportunities for process and strategy optimization.
• Support ad-hoc analytics for policy changes, new treatments, and technology initiatives.

• Collaborate with credit risk, data/BI, and servicing teams to ensure aligned metric definitions and shared understanding of portfolio health.
• Partner with compliance and legal on analytics related to regulatory controls and contact strategy governance.
• Engage with technology and vendor teams as needed to access data, support performance…