FinTech

Ship compliant financial products in weeks, not quarters.

We build payment platforms, fraud detection, KYC automation, and credit scoring engines in 12 weeks. Compliance gets built into the architecture - not patched in the week before launch.

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12+

Fintech products

68%

Fewer false positives

85%

Faster KYC

Overview

Compliance shouldn't slow your launch

Fintech software development at RaftLabs is regulation-aware from sprint one. We bring patterns from 100+ products across adjacent industries to build fraud detection engines, KYC/AML automation, credit scoring models, and financial document processing - each engineered to meet PCI DSS, SOC 2, and jurisdiction-specific regulatory requirements without slowing your release cadence.

Fintech moves fast, but compliance doesn't forgive mistakes. Most teams either ship quick and scramble on audits, or spend months on compliance and miss their market window. Neither works.

Our payment platforms process $200M+ annually. Fraud detection systems cut false positives by 68%. KYC workflows bring onboarding from 3 days to 11 minutes. Every product launches compliant from day one.

We treat compliance as an architecture decision, not a checklist. PCI DSS, SOC 2, KYC/AML, state lending regulations - we've built for all of them. When auditors arrive, the documentation already exists.

Experience Signal

12+ fintech products shipped with audit-ready documentation. Payment platforms processing $200M+ annually, fraud detection cutting false positives 68%, and KYC workflows dropping onboarding from 3 days to 11 minutes. 12 weeks is our default, not our stretch goal.

12+

Fintech products

68%

Fewer false positives

Industry Pain Points

What's broken in fintech

01

KYC onboarding takes 2-5 days because identity verification, document review, and risk screening run as manual processes

02

Fraud detection systems flag 30-50% false positives, creating customer friction and expensive manual review queues

03

Regulatory changes require months of engineering work because compliance logic is hardcoded, not configurable

04

Credit decisioning relies on traditional bureau scores that exclude 45M thin-file Americans from financial products

05

Financial document processing - bank statements, tax returns, pay stubs - still runs on manual data entry and verification

06

Transaction monitoring generates thousands of alerts daily with no prioritization, burying real risks in noise

Solutions

Problems we solve in fintech

Each solution is built from patterns we've validated across 100+ products. No experiments on your budget.

01

Real-time fraud detection

Transaction scoring using behavioral patterns, device signals, and network analysis. Adapts to new fraud patterns without manual rule updates. Cuts false positives while catching more actual fraud.

02

Automated KYC and AML compliance

End-to-end identity verification - document authentication, facial matching, sanctions screening, and adverse media checks. Onboarding drops from days to minutes with full audit trails.

03

Alternative credit scoring

AI models that score creditworthiness using bank transaction data, payment history, employment stability, and behavioral signals - expanding approval rates for thin-file applicants without raising default risk.

04

Intelligent document processing

Extracts, validates, and structures data from bank statements, tax returns, pay stubs, and financial filings. Replaces manual data entry with 98%+ accuracy extraction and automated cross-referencing.

05

Regulatory change management

Monitors regulatory updates across federal and state jurisdictions. Maps changes to affected product logic and generates implementation specs for engineering teams. Keeps compliance current without reactive scrambles.

06

Transaction monitoring and SAR filing

Prioritizes suspicious activity alerts by risk score, cuts noise by 70-80%, and auto-drafts SAR narratives with supporting evidence. Compliance analysts focus on high-risk cases instead of clearing false alarms.

Use Cases

Real-world use cases

Fraud detection for a payment processor

Problem

A payment platform processing $180M annually had a 42% false positive rate on fraud alerts. Manual review cost $640K a year and legitimate customers were blocked an average of 3.2 times per year.

What we built

We built a multi-signal fraud scoring system using transaction velocity, device fingerprinting, behavioral patterns, and merchant risk profiles - with real-time decisioning and configurable risk thresholds.

Result

False positives dropped to 13%. Fraud losses decreased 38%. Customer complaints about blocked transactions fell 71%. Manual review costs dropped to $210K a year.

KYC automation for a neobank

Problem

A digital bank took 3.2 days on average for customer onboarding. 28% of applicants abandoned during the KYC process. Compliance staff spent 6 hours daily on manual document review.

What we built

We automated the full KYC pipeline - ID document authentication, facial liveness detection, sanctions and PEP screening, and risk scoring - with configurable rules for different account tiers and jurisdictions.

Result

Onboarding time dropped to 11 minutes. Abandonment rate fell to 9%. Compliance team reallocated 80% of manual review time to complex cases and audits.

Credit decisioning for a small-business lender

Problem

A small business lender approved only 18% of applications using traditional bureau scores. They rejected $42M in potentially good loans annually from thin-file applicants.

What we built

We built an alternative scoring model using bank transaction analysis, cash flow patterns, industry benchmarks, and payment behavior - with explainable scoring for compliance and fair lending requirements.

Result

Approval rate climbed to 31% without raising default rates. Annual loan volume grew $28M. The model passed fair lending review with full explainability documentation.

Proof

How we've solved fintech problems

FinTech

Mobile POS app for digital payments in remote areas

5K+ downloads in 3 months, 4.8-star rating, 10K+ transactions processed.

5K+

App downloads

4.8 stars

Google Play rating

Read case study

Our Approach

How we approach fintech projects

1
Phase 1· Week 1-2

Regulatory mapping and risk assessment

We map every applicable regulation - PCI DSS, SOC 2, KYC/AML, state-specific rules - and define compliance requirements before architecture. Risk assessment covers data handling, third-party dependencies, and audit needs.

Deliverables

  • Regulatory requirements matrix with control mappings
  • Risk assessment covering data, third-party, and operational risks
  • Compliance architecture requirements for engineering
2
Phase 2· Week 2-4

Secure architecture and model design

We design the system with compliance built into the data layer, API boundaries, and access controls. AI models are designed with explainability and bias testing from the start.

Deliverables

  • Secure architecture with compliance controls documented
  • AI model design with explainability and fairness framework
  • Integration plan for banking, payment, and data providers
3
Phase 3· Week 4-10

Build, test, and compliance validation

We build in sprints with continuous compliance testing. Penetration testing, model validation, and regulatory review happen during development, not after.

Deliverables

  • Production-ready product with compliance controls active
  • Penetration test results and remediation documentation
  • Model validation report with bias and performance metrics
4
Phase 4· Week 10-12

Launch, audit prep, and monitoring

We launch with full audit documentation ready. Ongoing monitoring covers model drift, regulatory changes, and security events. Your compliance team has everything they need for examiner requests.

Deliverables

  • Launch with audit-ready documentation package
  • Monitoring dashboard for compliance, model performance, and security
  • Regulatory change tracking and impact assessment process

Outcomes

Measurable outcomes

85-95% reduction in KYC onboarding time - from days to minutes
50-70% decrease in fraud detection false positives while improving catch rates
30-60% increase in lending approval rates for thin-file applicants without higher defaults
98%+ accuracy on financial document extraction, replacing manual data entry
70-80% reduction in noise from transaction monitoring alerts
Audit-ready documentation from day one - no scramble before examiner visits

Free Tools

Free tools for fintech

Calculators and assessments built from real project data. No signup required.

See all free tools

Pattern Transfer

RaftLabs's real-time fraud scoring architecture was shaped by anomaly detection work we did for an insurance claims system. Both problems need sub-second decisions on streaming data with explainable outcomes. The domain changed - the pattern didn't.

Services

Services for fintech

From the blog

Articles for fintech teams

Frequently asked questions

Most projects range from $60K-$250K. A KYC automation system starts around $60K. A full fraud detection platform with real-time scoring runs $120K-$250K. Compliance engineering adds 20-30% compared to a non-regulated build. We give fixed estimates before work begins.

Next Step

Every day of manual KYC is another day your competitors onboard faster.

One call with a founder. No sales team, no follow-up sequence. If we can't help, we'll say so.

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