Risk engines, fraud models & payment rails
Estimate your credit →Building risk models, fraud systems, payment infrastructure, and compliant core platforms requires experimentation to meet accuracy, latency, integrity, and security requirements.
The credit is calculated on qualified research expenses (QREs) — primarily wages for engineers and technical staff who spend time on qualifying activities, plus supplies, cloud/compute, and 65% of qualified contract research.
The table below lists the business components that most often qualify, a common example, and the technical uncertainty that makes each one defensible.
| Business component | Example | Technical uncertainty |
|---|---|---|
| Risk & underwriting engines | Credit or insurance risk model | Which model predicts risk accurately and fairly? |
| Fraud detection | Real-time fraud-scoring model | How to catch fraud while minimizing false positives? |
| Payment rails & infrastructure | Payment processing, ledger system | How to process reliably at scale and low latency? |
| Trading & pricing systems | Pricing engine or execution algorithm | Which approach prices and executes correctly? |
| Compliance & RegTech automation | KYC/AML automation | How to automate compliance accurately? |
| Core platform & ledger | Double-entry ledger, reconciliation engine | How to ensure consistency and integrity at scale? |
| Identity & data security | Identity verification, encryption | Which architecture is both secure and performant? |
| Embedded finance & APIs | Banking-as-a-service APIs | How to integrate reliably across partners? |
Wages for time spent on qualified research may count toward your credit. Percentages depend on facts and must be documented.
Illustrative example using sample figures. Your actual credit depends on your facts; see Form 6765 and consult a tax professional.
The IRS requires qualifying research to satisfy four tests. Here's how they typically map for this industry:
The activity aims at improving a product, process, software, or technique used in the business — not just a business outcome.
The work relies on principles of engineering, computer science, biology, chemistry, or another hard science to resolve uncertainty.
There was genuine uncertainty at the outset about whether — or how — the component could be built or improved.
The team evaluated alternatives: A/B tests, prototypes, benchmarks, simulations, or iterative design-build-test cycles.
Most companies underestimate what they can claim. Our study covers every qualifying role, every component, and every year still open for amendment.
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