Vertical AI Solutions: Fintech, Retail, Real Estate & Manufacturing

Fraud Detection & Transaction Risk Scoring

Fraud doesn't announce itself, it hides inside transaction volume that's grown too large for a static rules engine or a manual review team to catch in real time. This service builds a machine-learning risk-scoring model trained on your actual transaction history, flagging account takeover, synthetic identity, card-testing, and first-party fraud before it clears, not after a chargeback lands. It's built for payments companies, lenders, and marketplaces where a fixed rules list keeps missing new fraud patterns while flagging too many good customers. The model runs alongside your existing fraud operations, giving your review team a ranked, explainable risk score instead of a flood of undifferentiated alerts. The result is fewer losses and fewer false declines on legitimate customers.

This is a capability we deliver for you as a service, not a role we’re hiring for.

How We’d Approach This

A clear, staged plan, not a black box

These are the service-specific steps inside our six-step process.

1
Diagnose current fraud losses, false-positive rates, and the specific patterns your existing rules miss.
2
Pilot the risk model against a sample of historical transactions with known outcomes to prove lift before it touches live traffic.
3
Review scoring thresholds and false-positive tradeoffs with your fraud and compliance teams before go-live.
4
Launch with a human-reviewed queue for borderline scores, then tune thresholds as real transaction data comes in.

What You Get

Deliverables from this engagement

Trained fraud risk-scoring model with documented feature set
Real-time scoring API integrated into your transaction flow
Explainable risk-score breakdown for every flagged transaction
Analyst review dashboard for borderline and high-risk cases
Monthly false-positive and catch-rate performance report

Six Ways We Could Architect This

Different engagement, different build, pick the shape that fits

There’s more than one way to deliver on this service. Browse a few of the ways we’d structure the work, depending on your speed, budget, and integration needs.

Read all 6 architectures as text

Lean Fast-Start Architecture

Data Input

Historical Transaction Export
Known Fraud Labels

Simple Model

Baseline Risk Scoring Model
Single Risk Score Output

Testing

Backtest Against Known Outcomes
Threshold Set Manually

Rollout

Shadow Scoring on Live Traffic
Analyst Spot Check
Score Added to Review Queue
Weekly Catch Rate Review
Basic Performance Notes
Plan for Live Enforcement

Cloud-Native / Managed Services Architecture

Data Layer

Transaction Stream
Cloud Data Warehouse

Managed ML Platform

Managed Feature Store
Managed Model Training Service
Model Registry

Scoring Layer

Real Time Scoring Endpoint
Explainability Service

Operations Layer

Analyst Review Dashboard
Managed Alerting Service
Model Performance Monitoring
Auto Retraining Pipeline
Monthly Performance Report

Event-Driven & Automation-First Architecture

Triggers

Transaction Initiated
Real Time Event Stream

Automation Layer

Auto Feature Computation
Auto Risk Score Generated
Score Above Threshold

Review Gate

Auto Hold for Review
Transaction Auto Approved
Analyst Queue Entry
Confirmed Fraud
Auto Block and Case Opened

Delivery

Transaction Log Updated
Daily Fraud Trend Report

Enterprise-Grade & Compliance-Ready Architecture

Governance Layer

Fraud Policy Framework
Regulatory Reporting Requirements
Model Risk Management Policy

Secure Scoring Layer

Access Controlled Scoring API
Role Based Analyst Access
Encrypted Transaction Data

Auditable Model

Model Version and Lineage Log
Score Explainability Record
Decision Audit Trail

Compliance Operations

Redundant Scoring Infrastructure
Independent Model Validation
Signed Off Compliance Report

AI-Augmented, Human-in-the-Loop Architecture

Input Layer

Live Transaction Data
Customer Behavior History

AI Scoring Layer

AI Risk Scoring Model
Ranked Risk Score
Explainable Risk Factors

Human in the Loop

Fraud Analyst Review Queue
Confirmed Fraudulent
Escalate to Senior Analyst
Human Approved Decision

Delivery

Transaction Blocked or Cleared
Case Outcome Logged
Model Feedback Loop Updated

Integration-Heavy / Ecosystem-Connected Architecture

Client Systems

Payment Processing Platform
Core Banking or Ledger System
Customer Support Platform

Risk Scoring Core

Real Time Risk Scoring Engine
Case Management System

Two Way Sync Layer

Chargeback System Sync
Compliance Reporting Sync
Finance Operations Team
Compliance Team

Shared Governance

Joint Review with Risk Committee
Published Risk Scoring Architecture
Ongoing Model Performance Review

Ready to get started?

Tell us what you’re trying to get done and we’ll help you find the highest-leverage place to start, scoped small enough to prove itself before you commit to anything bigger.

Talk to us about Fraud Detection & Transaction Risk Scoring

Most engagements like this start as a $500–$2,500 pilot, see full pricing.