Real-time scores, explainable features, and case tooling—fraud stacks that evolve faster than rule-only systems.

Stop fraud before settlement—signals, models, and reviews in one loop

We assemble graph, device, and behavioral features with low-latency serving—scores return in milliseconds with reason codes analysts can interpret. Champion-challenger deploys new models behind shadow traffic; promotion requires uplift on holdout fraud sets without tanking approvals. Case management links alerts to user history and chargeback outcomes—feedback retrains models with governance, not ad hoc SQL tweaks.

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AI Fraud Detection & Adaptive Risk Scoring Platform Development

01 // THE MANDATE

Real-time scores, explainable features, and case tooling—fraud stacks that evolve faster than rule-only systems.

We assemble graph, device, and behavioral features with low-latency serving—scores return in milliseconds with reason codes analysts can interpret. Champion-challenger deploys new models behind shadow traffic; promotion requires uplift on holdout fraud sets without tanking approvals.

Case management links alerts to user history and chargeback outcomes—feedback retrains models with governance, not ad hoc SQL tweaks.

02 // ENGINEERING

Development process

Structured phases—from discovery to launch—with clear ownership and handoff points.

Loss mapping (weeks 1–4)

Fraud types, SLAs, false positive appetite.

MVP (weeks 4–14)

Core features, score API, analyst UI, shadow mode.

Calibration (weeks 12–20)

Threshold tuning; vendor data feeds optional.

Live (weeks 18–26)

Progressive traffic; chargeback feedback loop.

Operate (ongoing)

Retrain cadence; attack response playbooks.

03 // CAPABILITIES

Core Capability Matrix

The building blocks of your solution

Ingest

events; payments; logins optional.

Features

velocity; graph hops; device intel optional.

Models

gradient boosting; deep optional; rules blend.

Explain

SHAP-style summaries; top factors.

Decisions

approve; step-up; block.

Orchestration

3DS; OTP; manual review.

Graph

linked accounts optional.

Reporting

loss curves; alert rates.

API

sync score; batch backtest.

Governance

bias monitoring optional; audit trail.

04 // DELIVERY LIFECYCLE

The strategic roadmap

Milestones and checkpoints—each phase has a clear outcome before the next begins.

Milestone 01Delivery

Weeks 1–4: Label quality review.

Milestone 02Delivery

Weeks 5–12: Offline model beats baseline rules.

Milestone 03Delivery

Weeks 13–20: Shadow scoring on production traffic.

Milestone 04Delivery

Weeks 21–26: Decisioning in production with caps.

Milestone 05Delivery

Ongoing: Monthly model reviews; incident drills.

05 // PRODUCT SCOPING

Choosing your path

Two engagement models—start lean and iterate, or commit to a full platform build from day one.

MVP

Speed & essentialism

Phase 1
MVP: event ingestion, feature store lite, real-time score API, rules + one ML model, case queue, dashboards. Excludes full graph OLAP and autonomous agent investigations. Proves uplift before platform sprawl.
Recommended

Full product

Enterprise maturity

All-in
Enterprise fraud hub: identity graph, device intelligence marketplace, automated narrative reports, regulatory stress testing, multi-product orchestration.

06 // PARTNERSHIP

Why work together

A single accountable partner across strategy, build, and go-live—not a revolving door of vendors.

John Hambardzumian
Direct collaboration

End-to-end ownership: discovery, architecture, implementation, and launch—with clear communication and production-grade engineering.

  • Discovery & alignment
  • Systems that scale
  • Implementation depth
  • Clear comms

07 // CLARITY

Frequently asked

Fair lending reviews for credit-adjacent decisions; monitoring slices defined with compliance.

Ready to start?

Tell me about your product goals and timeline—I'll respond with a clear path forward.