Collections Risk Management Lead
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Job Description
Analytics professional with credit analytics expertise supporting risk management and portfolio management. Analyzing data for informed credit decisions and risk assessments in a remote role.
Responsibilities:
- Analyze new applicant data to support automated and manual credit decisioning.
- Work with data extracted from business financial statements, tax documents, and banking integrations (e.g., Quickbooks, Netsuite, Plaid, etc).
- Leverage insights from adjacent product usage (e.g., business banking, payments platforms) to evaluate risk profiles.
- Build dashboards or tools to surface real-time indicators for underwriting and fraud detection.
- Monitor account-level behavior post-origination, including spend and payment patterns, credit utilization, and engagement.
- Identify signs of weakening creditworthiness using internal data and third-party credit reports (e.g., Experian, D&B).
- Track and analyze delinquency trends and payment consistency to refine risk models and collections strategies.
- Develop behavioral segments and performance cohorts for proactive account management.
- Support P&L analysis of the unsecured credit card product, including interchange income, interest revenue, rewards cost, and charge-off rates.
- Build models to evaluate customer lifetime value, profitability segmentation, and risk-adjusted returns.
- Assist in identifying drivers of loss and opportunities for margin improvement.
Requirements:
- 5–15 years of hands-on Collections risk management experience; direct exposure to both a bank or regulated card program and a fintech strongly preferred
- Hands-on familiarity with the full delinquency lifecycle: DPD bucket management, treatment strategy design, charge-off policy, recovery curve modeling, and net loss attribution
- Practical experience managing or working alongside third-party collections agencies — understands liquidation economics, placement timing trade-offs, cost-to-collect dynamics, and how to build a KPI framework that holds vendors accountable without creating perverse incentives
- Analytically self-sufficient: proficient in SQL and Python or R; capable of building roll rate matrices, cure rate cohorts, and recovery forecasts from raw data rather than consuming pre-built reports
- Familiar with the regulatory overlay on collections: FDCPA obligations, Reg F communication rules, UDAAP considerations in treatment strategy design, and state-level restrictions that affect contact and remediation practices
- Understands the distinct dynamics of SMB collections — cash flow seasonality, the owner as guarantor, and where standard consumer treatment logic breaks down
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