Lending and credit risk
Decisions about who you lend to, at what price, and what happens after the loan is booked.
Credit policy design and evaluation
Design a credit box, or test an existing one: who you approve, at what limit, with what verification, and how the application funnel and offers shape who applies. We measure which rules actually rank-order risk and what each change would do to approvals, losses and return.
Questions we help answer
- Is our credit box leaving profitable volume on the table, or approving loans we shouldn't?
- Which policy rules still earn their place, and which only add friction to the funnel?
- How does our policy compare with peers and with what our funding partners expect?
What you get
- Policy diagnostic with swap-set and segment-level return analysis
- Redesigned policy, counteroffer and verification strategy with projected approval, loss and yield impact
- Policy documentation that holds up to partner, auditor and regulator review
Pricing and unit economics
Set prices from loss-adjusted returns, not a competitor's rate card. Risk-based pricing, price response and adverse selection, channel and acquisition cost, and return by segment.
Questions we help answer
- Are we pricing for risk, or giving away margin to our best customers?
- What does a rate change do to take-up, mix and losses?
- Which acquisition channels actually pay back after credit losses?
What you get
- Segment-level unit economics and return model
- Risk-based pricing grid with test design for rollout
- Channel and lead-pricing framework tied to expected value
Credit model strategy
Decide whether to build, buy or replace a credit model, and make sure it changes decisions. Custom versus bureau and vendor scores, model development oversight, deployment into policy, and performance monitoring.
Questions we help answer
- Would a custom model beat the bureau score enough to justify it?
- Is our model degrading, and would we know if it were?
- How do we turn better model rank-ordering into better approvals and pricing?
What you get
- Build-versus-buy assessment with expected lift
- Model development roadmap and oversight of build
- Monitoring framework with drift triggers and decision impact
Fraud strategy
Stop application and first-party fraud without blocking good customers. Real-time decision gates, verification design, and the right balance of automation and manual review.
Questions we help answer
- How much of what we call credit loss is really fraud?
- Where can we automate review without letting fraud through?
- What is each verification step costing us in conversion?
What you get
- Fraud loss decomposition by type and channel
- Real-time fraud gate design and rules strategy
- Operating model for review queues and escalation
Collections and recovery strategy
Reduce losses after the loan is booked. Roll-rate segmentation, treatment and channel strategy, and champion/challenger testing.
Questions we help answer
- Which accounts will self-cure, and which need early contact?
- Is our collections effort matched to where it changes outcomes?
- Which treatments actually reduce charge-offs?
What you get
- Segmented treatment strategy with champion/challenger tests
- Collections performance diagnostic
- Loss impact tracking against plan
Loss forecasting and stress testing
Forecast losses that management, auditors and examiners will accept. Vintage and roll-rate forecasting, CECL reserve review, macro scenarios and stress testing.
Questions we help answer
- Is our reserve consistent with how our portfolio actually performs?
- How would our book perform in a recession scenario?
- Can we explain forecast-to-actual variance every quarter?
What you get
- Loss forecasting methodology review or build
- Scenario and stress results with documented assumptions
- Quarterly variance reporting for management and the board
New product launch
Launch a credit product without its own performance history. Proxy data, launch credit box and limits, test-and-learn design, early-warning triggers and launch economics.
Questions we help answer
- What credit policy can we defend when we have no history?
- How do we learn fast without taking a large loss on the first vintages?
- What will regulators and partners want to see before launch?
What you get
- Launch credit framework and product economics
- Test-and-learn design with scale-up gates
- Early-warning dashboard and triggers
Competitive and market analysis
Know what competitors are doing from what they have to disclose. Public filings, ABS trust performance, call reports, BDC marks and changes in lenders' published credit criteria.
Questions we help answer
- How is our portfolio performing relative to comparable lenders and trusts?
- Are competitors tightening or loosening their credit box?
- What does a competitor's deal or reserve tell us about its risk?
What you get
- Peer benchmarking from public and ABS data
- Credit-box direction tracking across competitors
- Deal and disclosure analysis for specific transactions
Capital markets and partnerships
Deals that move loans, funding and risk between originators, banks and investors.
Bank–fintech partnerships
Design or evaluate a partnership between a bank or credit union and a fintech originator. Our founder has been on both sides: buying fintech loans at a bank, and restructuring bank partnerships as the fintech.
Questions we help answer
- Is this partner's underwriting, fraud control and servicing good enough to put on our balance sheet?
- Are the economics and capital terms of our partnership fair, and can they be restructured?
- What should we monitor once the program is live?
What you get
- Partner due diligence and program evaluation
- Partnership economics and term-structure analysis
- Ongoing program performance monitoring
Forward-flow deal design and evaluation
Structure or evaluate an agreement to sell or buy loans on an ongoing basis. Eligibility criteria, pricing mechanics, concentration limits, performance triggers, servicing terms and reporting.
Questions we help answer
- Is this price fair for the credit we're actually going to deliver or receive?
- Which triggers and eligibility terms will bind first under stress?
- What reporting will the buyer need, and can we produce it?
What you get
- Deal term review or design
- Pricing and return analysis under base and stress cases
- Ongoing performance reporting and covenant monitoring
Funding readiness: warehouse and ABS
Get a lender ready for warehouse lenders and securitization investors, or help an investor read a lender's data. Vintage and static-pool analysis, trigger headroom, data tapes and investor reporting.
Questions we help answer
- Do our advance rates and triggers fit our actual performance, and how much headroom do we have?
- Is our performance data ready for warehouse lenders and ABS investors?
- How is a deal or trust performing against its original expectations?
What you get
- Vintage, static-pool and trigger-headroom analysis
- Lender- and investor-ready data package and reporting
- Trust and facility surveillance against peers
Portfolio valuation and sales
Price a whole-loan portfolio to buy, sell or mark. Loss, prepayment and cash-flow assumptions from tape-level data, diligence on the originator and its servicing, and a clear read on what a price implies.
Questions we help answer
- What is this portfolio worth, and what is the price implying?
- What did the originator's policies and servicing put into this pool?
- Is our fair value mark consistent with the market?
What you get
- Loan-level valuation with assumption sensitivities
- Originator, pool and servicing due diligence
- Price-implied loss, life and return analysis