Back to industries

FinTech

Ship compliant financial products in weeks, not quarters.

We build payment platforms, fraud detection systems, KYC automation, and credit scoring engines for financial services companies. We know the regulatory environment and build compliance into the architecture, not as a patch before launch.

Get a fintech product assessmentSee relevant work
68%

Fewer false positives

85%

Faster KYC

Overview

Compliance shouldn't slow your launch

Fintech software development at 1Raft 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 systems - 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 fast and scramble on compliance, 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 reduce onboarding from 3 days to 11 minutes. Every product launches compliant from day one.

Our approach treats 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

1Raft builds payment platforms, fraud detection systems, KYC automation, and credit scoring engines for payment processors, neobanks, and lending platforms. Our engineering draws on patterns validated across 100+ products in adjacent industries.

68%

Fewer false positives

85%

Faster KYC

Industry Pain Points

What's broken in fintech

01

KYC onboarding takes 2-5 days because identity verification, document review, and risk screening are 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 requires 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

Real-time transaction scoring using behavioral patterns, device signals, and network analysis. Adapts to new fraud patterns without manual rule updates. Reduces false positives while catching more actual fraud.

02

Automated KYC/AML Compliance

End-to-end identity verification: document authentication, facial matching, sanctions screening, and adverse media checks. Reduces onboarding 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 increasing 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, reduces 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/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. Added real-time decisioning with 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/year.

KYC Automation for a Neobank

Problem

A digital bank took 3.2 days 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/PEP screening, and risk scoring. Built 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 Lending Platform

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 signals. Added explainable scoring for compliance and fair lending requirements.

Result

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

Our Approach

How we approach fintech projects

1
Phase 1· Weeks 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· Weeks 3-4

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· Weeks 5-10

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· Weeks 11-12

Launch, Audit Preparation, 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

Pattern Transfer

1Raft's real-time fraud scoring architecture was shaped by anomaly detection work we did for an insurance claims system. Both problems require sub-second decisions on streaming data with explainable outcomes. The domain changed; the pattern didn't.

Services

Services for fintech

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 provide 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.

Get a fintech product assessment
View fintech case studies