Collections Risk Management Lead

Flex is building the AI-native private bank for business owners.

We’re re-architecting the entire financial system for entrepreneurs—from the first dollar a business earns to how that value compounds, moves, and is ultimately spent in real life. Banking, credit, payments, personal finance, and financial operations—rebuilt from the ground up as a single, intelligent system. Flex is the full financial home for ambitious owners.

Since launching publicly in September 2023, Flex has scaled from zero to nine-figure annualized revenue, with a clear path to profitability by late 2026. We move fast, ship relentlessly, and operate with extreme ownership.

Our customers are affluent business owners ($3–$200M in revenue)—the backbone of the economy and one of the most underserved segments in finance. They’re stuck with outdated banks and fragmented tools. We’re replacing all of it. The opportunity is massive: a ~$1T+ revenue market hiding in plain sight. Our ambition is to build a product that is fundamentally better—not incrementally improved.

Flex Fuels Ambition.

The Collections Risk Management Lead is a key member of the Flex Risk Management Leadership Team (reports to the Chief Risk Officer) who will have the opportunity to take the Fraud Risk Management function at Flex to a level that rivals the best in class.

Core Responsibilities

• Own end-to-end collections risk management for Flex's credit card portfolio across consumer and small business segments — end-to-end meaning full lifecycle coverage from early delinquency through post charge-off recovery:
• • Early stage collections: monitor roll rates and delinquency migration across DPD buckets; design and refine treatment strategies by risk segment, balance tier, and obligor type; optimize contact timing, channel mix, and messaging to maximize cure rates before accounts deteriorate further
  • Late stage collections: manage pre-charge-off intervention strategies; own the analytical framework for determining when accounts warrant accelerated action versus continued treatment; maintain visibility into cure and re-default patterns by treatment cohort
  • Hardship & modification management: maintain analytical visibility into hardship program utilization, modification outcomes, and re-default rates; identify where hardship programs are being used appropriately versus as avoidance behavior
  • Settlement strategy: define settlement authorization frameworks by balance tier, DPD, and obligor type; evaluate the NPV trade-off between discounted resolution and continued collection effort; govern agency settlement authority to avoid both under-recovery and adverse selection among accounts that would have paid in full
  • Vendor & agency management: define the strategic boundary between in-house collections and third-party placement — knowing when to keep accounts internal and when placement generates better expected recovery net of cost; evaluate and manage agency relationships on the basis of liquidation rates, compliance posture, consumer treatment standards, and cost-to-collect; own the KPI framework for vendor performance and hold agencies accountable to it
  • Litigation: identify accounts where legal escalation is warranted based on balance size, recovery probability, and obligor profile; maintain an analytical framework for litigation referral thresholds and track outcomes by segment; understand the owner-as-guarantor dimension in SMB accounts and where personal liability creates additional recovery optionality
  • Charge-off & recovery: own charge-off timing policy and its interaction with loss reserve mechanics; build and maintain recovery rate forecasts by vintage, segment, and channel; track net loss emergence and recovery curves over time
  • SMB-specific collections dynamics: apply a distinct analytical lens to small business obligors — seasonal cash flow patterns, owner-business financial entanglement, and the limits of standard consumer treatment strategies in a business context

• Build and maintain collections performance frameworks that surface deterioration signals early and enable proactive treatment rather than reactive loss management
• Synthesize data across sources — payment history, bureau refreshes, transaction behavior, contact records, and macro indicators — to segment the delinquent population intelligently and match treatment intensity to recovery probability
• Lead periodic collections reviews: own the data, design the narrative, and present delinquency trends, recovery performance, and vendor outcomes to risk committees and senior leadership
• Partner cross-functionally with credit, legal & compliance, finance, and operations to ensure collections strategy is aligned with loss reserve inputs, regulatory obligations, and customer experience standards
• Contribute to stress testing and loss forecasting: model collections performance under adverse conditions and translate recovery assumptions into net loss projections
• Serve as the internal SME on collections analytics — establishing measurement standards, treatment logic, and vendor governance frameworks as the portfolio scales

Qualifications

This role sits in the foundational build path of core risk management disciplines, and we expect significant upward potential for the right candidate. The emphasis is on finding colleagues with a strong foundation more than a ‘minimum number of years’ constraint. We can work with people who have 7–15 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

Mindset

We believe in the culture of ownership at Flex. All employees are given Equity in the company in addition to the Base Compensation.

Flexbase Technologies Inc.