R&D Tax Credits for Fintech Companies

R&D Tax Credits for Fintech Innovation

Payment processing innovation, fraud detection algorithms, regulatory compliance technology, and security features qualify for substantial R&D tax credits. Average fintech savings: $200K-$600K annually.

$200K-$600K
Average Annual Credits
70-85%
Dev Time Qualifying
35%
Combined Fed + State Rate
98%
Fintech Companies Qualify

Why Fintech Companies Are Ideal for R&D Tax Credits

Fintech is one of the most R&D-intensive industries. Between payment processing innovation, fraud detection algorithms, regulatory compliance requirements, and security challenges, fintech companies face constant technical uncertainty.

Every aspect of fintech development involves solving novel problems: How do we process payments in under 100ms? How do we detect sophisticated fraud patterns? How do we comply with evolving regulations across 50 states? These are textbook examples of qualifying R&D.

Unlike other industries where R&D might be 20-30% of development work, fintech companies often see 70-85% of engineering time qualifying because nearly everything involves technical innovation and compliance challenges.

Fintech-Specific R&D Opportunities

Payment Processing Innovation

ACH, card networks, instant payments, crypto integration

Fraud Detection & Prevention

Machine learning models, pattern recognition, risk scoring

Regulatory Compliance Technology

KYC/AML, money transmission licenses, BSA reporting

Security & Encryption

PCI DSS compliance, tokenization, end-to-end encryption

What Fintech Development Activities Qualify?

Fintech development almost always involves technical uncertainty due to security requirements, regulatory complexity, and performance demands. Here's what typically qualifies:

Payment Processing & Infrastructure

Qualifying Activities:

  • Building payment processing engines with sub-100ms latency
  • ACH file generation and processing automation
  • Card network integration (Visa, Mastercard APIs)
  • Real-time payment reconciliation systems
  • Instant payment/settlement infrastructure (RTP, FedNow)
  • Cryptocurrency payment gateway integration
  • Multi-currency conversion and forex optimization
  • Payment retry logic and failure handling

Why This Qualifies:

Payment processing involves significant technical uncertainty around performance, reliability, and integration complexity. Solutions aren't available off-the-shelf.

Typical Credit Value:

2-3 engineers working on payment infrastructure for a year = $80K-$120K in credits

Fraud Detection & Risk Management

Qualifying Activities:

  • Machine learning fraud detection models
  • Real-time transaction risk scoring algorithms
  • Behavioral analytics and anomaly detection
  • Device fingerprinting and bot detection
  • Network analysis for identifying fraud rings
  • Adaptive rules engines that learn from patterns
  • 3D Secure integration and authentication flows
  • Chargeback prediction and prevention systems

Why This Qualifies:

Fraud detection is inherently experimental - you're constantly testing new algorithms, features, and models to stay ahead of evolving fraud tactics. High technical uncertainty.

Typical Credit Value:

1-2 data scientists + 2-3 engineers = $100K-$180K in credits

Regulatory Compliance Technology

Qualifying Activities:

  • KYC (Know Your Customer) automation and verification
  • AML (Anti-Money Laundering) monitoring systems
  • Suspicious Activity Report (SAR) generation
  • OFAC sanctions screening and watchlist monitoring
  • Multi-state money transmission license compliance
  • Open banking API compliance (PSD2, etc.)
  • Dodd-Frank, CFPB compliance automation
  • Audit trail and reporting infrastructure

Why This Qualifies:

Building technology to automate complex, evolving regulatory requirements involves significant R&D. You're solving problems that don't have clear technical solutions.

Typical Credit Value:

2-4 engineers on compliance tech = $70K-$140K in credits

Security, Encryption & Data Protection

Qualifying Activities:

  • PCI DSS Level 1 compliance implementation
  • End-to-end encryption for sensitive financial data
  • Tokenization of payment card data
  • Hardware Security Module (HSM) integration
  • Multi-factor authentication systems
  • Secure key management and rotation
  • Zero-knowledge proof implementations
  • Penetration testing remediation and hardening

Why This Qualifies:

Financial data security requirements are among the most stringent. Implementing cryptographic systems and security controls at scale involves significant R&D.

Typical Credit Value:

1-2 security engineers full-time = $50K-$100K in credits

What Doesn't Qualify for Fintech Companies

Non-Technical Activities:

  • • Financial product design and market research
  • • Licensing applications and regulatory filings
  • • Partnership negotiations with banks
  • • Marketing website and content development
  • • Customer support and onboarding
  • • Financial modeling and underwriting criteria

Routine Technical Work:

  • • Using Stripe/Plaid APIs without customization
  • • Standard web app development (dashboard, forms)
  • • Basic database CRUD operations
  • • System administration and DevOps
  • • Bug fixes without technical challenges
  • • Documentation and training materials

Real Fintech R&D Credit Calculation

Series B Digital Banking Platform Example

Company Profile

Business:Digital banking platform
Funding Stage:Series B ($45M raised)
Engineering Team:18 full-time engineers
Average Salary:$155K + benefits ($185K total)
Contractors/Consultants:$350K annually
Infrastructure & Tools:$180K annually

Engineering Team Allocation

Payment infrastructure team:5 engineers (90% R&D)
Fraud/risk team:3 engineers (95% R&D)
Compliance tech team:4 engineers (85% R&D)
Security/encryption team:2 engineers (80% R&D)
Product/frontend team:4 engineers (40% R&D)
Weighted Average R&D:~75%

Qualified Research Expenses (QREs)

Engineering salaries (18 × $185K)$3,330,000
× 75% time on qualifying R&D$2,497,500
Contract developers & consultants$350,000
× 65% qualifying rate (IRS rule)$227,500
Cloud infrastructure & dev tools$180,000
× 50% used for R&D activities$90,000
Total QRE$2,815,000

Federal Credits:

Total QRE$2,815,000
× Federal rate (20%)$563,000

State Credits (NY example):

Total QRE$2,815,000
× NY rate (9%, refundable)$253,350

Total Annual R&D Tax Benefit:

Federal + State credits combined

$816,350

Enough to hire 4+ engineers

Common R&D Credit Mistakes for Fintech Companies

Fintech companies often leave money on the table due to these common mistakes:

Mistake #1: Thinking "We're Just Using APIs"

Many fintech companies use Stripe, Plaid, or other APIs and think they don't qualify. But if you're building custom logic on top (fraud detection, custom flows, optimization), that qualifies.

Reality Check:

The API is just infrastructure. Your custom payment logic, reconciliation, error handling, and optimization work on top of those APIs is qualifying R&D.

Mistake #2: Not Capturing Compliance Tech Work

Building technology to automate KYC, AML, and other compliance requirements is highly qualifying R&D work, but many companies don't track it separately from "operations."

Solution:

Tag compliance technology projects separately in your system. Automation of regulatory requirements almost always qualifies due to technical complexity.

Mistake #3: Missing Fraud Detection R&D

Fraud detection and risk modeling is pure R&D - constant experimentation with algorithms, features, and models. Yet many companies don't allocate enough credit to this work.

Solution:

Document model iterations, features tested, and performance improvements. All data science work on fraud/risk qualifies at close to 100% of time.

Mistake #4: Ignoring Security Engineering

PCI DSS compliance, encryption implementation, and security hardening involve significant R&D but are often categorized as "compliance" or "infrastructure" and missed.

Solution:

Security engineering work implementing encryption, tokenization, and PCI controls qualifies. Document the technical challenges and experimentation involved.

FINTECH CASE STUDY

How We Helped a Payment Processor Claim $487K in R&D Credits

$487K
Total first-year credits
83%
Engineering time qualifying
$0
Upfront cost (contingency)

The Company:

A Series A payment processing platform for marketplaces and platforms. $8M ARR, 15 engineers, processing $500M+ in annual payment volume. Core product: white-label payment infrastructure with embedded banking features.

The Situation:

Company had never claimed R&D credits. Their previous accountant said they were "just integrating existing payment APIs" and didn't qualify. They were burning $180K/month and needed to extend runway before Series B.

What We Found:

  • • Custom payment routing logic to optimize approval rates and costs
  • • Real-time fraud detection ML models trained on transaction patterns
  • • Multi-state money transmission compliance automation
  • • KYC/AML workflow engine with custom risk scoring
  • • PCI Level 1 certification with custom tokenization
  • • ACH processing with same-day settlement optimization

Result: 83% of engineering time qualified for R&D credits - far higher than the company expected.

Credits Claimed:

Federal Credit:

$372,000

California State:

$115,000

Elected payroll tax credit for immediate cash benefit. Set up quarterly tracking system for ongoing annual claims.

"We assumed our work didn't count because we use Stripe and Plaid APIs. SpryTax showed us that all the custom logic we built on top - fraud detection, routing optimization, compliance automation - is exactly what R&D credits are designed for. The $487K in credits gave us an extra 3 months of runway that was critical for hitting our Series B milestones."

— CEO & Founder

Ready to Claim Your Fintech R&D Tax Credits?

Get a free assessment to see how much your fintech development qualifies for. Most companies claim $200K-$600K annually.

Contingency pricing • No upfront cost • 98% of fintech companies qualify