9 Best AI Fraud Detection Software Development Companies in the USA (2026)

TL;DR: Off-the-shelf fraud tools rarely match a bank's or fintech's exact rules, data and analyst workflow. This guide compares 9 AI fraud detection software development companies, with LuMay first as a custom build partner that also brings a ready anomaly agent.

Fraud detection software development is the custom engineering of data pipelines, machine learning models, rules and analyst tools that score transactions or accounts for fraud risk and route suspicious activity to review.

Ranking criteria and disclosure: LuMay publishes this list and places its own offering first. We then compared real-time scoring, explainability, human review workflow, retraining and engagement model, using each company's own pages. No vendor paid for placement.

Quick Answer: LuMay ranks first as a custom build partner pairing ML engineering with explainable anomaly alerts and human review. ScienceSoft and Itransition bring long finance delivery records. RaftLabs offers fixed-price v1 builds. ScalaCode and Citrusbug publish detailed model and latency approaches.

Build vs Buy for Fraud Detection

Packaged fraud platforms are quick to switch on. Custom builds win when your signals, products or regulators make generic models noisy, or when you need to own the models and features.

• Signs a custom build fits
  • High false positives from vendor rules
  • Unique data such as internal ledgers or partner feeds
  • A need to own model IP and explain decisions
• Signs to buy first
  • Small volumes and standard card fraud patterns
  • No in-house team to own models after launch

AI Fraud Detection Development Companies: Comparison Table

Details below come from each company's public pages, checked on 24 October 2026 (IST). Validate team location, references and contract terms directly.

1. LuMay: Custom Fraud Models With Explainable, Human-Reviewed Alerts

LuMay's machine learning development services list fraud detection solutions that flag unusual transactions for manual or automated review in real time.

For faster starts, the LuMay Anomaly Agent sends every alert with its reasoning, with tunable sensitivity per workflow and routing to Slack, PagerDuty, email or webhook.

• Strengths
  • End-to-end delivery from data work to production, then monitoring
    • Automated retraining loops and drift tracking after launch
  • Alerts include what changed, why it is anomalous and similar past cases
  • Financial workflows keep people in control of decisions
• Commercials
  • Anomaly Detection Agents start at $999 per month on LuMay's pricing page; custom builds start with a pilot
• Watch
  • Card-network certifications and chargeback tooling should be scoped explicitly

See how this fits banking and fintech operations on LuMay's AI for finance page, and connect core systems through AI integration services.

2. ScienceSoft: Banking Software and Fraud Protection

ScienceSoft's fraud detection page sits within a broad banking practice that covers fraud protection for banks, banking analytics and LLMs for finance.

• Best for: banks wanting one vendor across core banking projects
• Watch: confirm the dedicated ML team assigned to fraud

3. Itransition: Fintech Engineering With AML and KYC

Itransition's fintech services include ML-based fraud detection systems alongside AML and KYC software and compliance monitoring.

• Best for: fintechs combining fraud, onboarding and compliance builds
• Watch: align scope across these modules early

4. LeewayHertz: Fraud Agents and Copilots

LeewayHertz builds custom AI agents and copilots for fraud detection operations and says it integrates with existing transaction monitoring systems.

• Best for: teams adding generative AI assistants to investigations
• Watch: ask for production references in payments

5. Citrusbug: Full Fraud Platform Engineering

Citrusbug describes building ingestion pipelines, feature stores, risk scoring, alerting and case management, including graph neural networks for ring detection.

• Best for: teams wanting a complete owned platform
• Watch: confirm US time-zone overlap

6. Azumo: Custom AI Fraud Builds for Fintech

Azumo's fraud page stresses that scoring latency, system availability and fallback logic are part of the fraud decision, not only model accuracy.

• Best for: fintechs that need resilient real-time scoring
• Watch: define fallback rules before go-live

7. RaftLabs: Fixed-Price Fintech Fraud v1

RaftLabs builds real-time transaction scoring, account takeover detection and synthetic identity checks, launching a validated v1 at a fixed price.

• Best for: fintechs and payment processors wanting budget certainty
• Watch: define what v2 expansion costs

8. ScalaCode: Low-Latency Fraud Scoring

ScalaCode describes gradient boosted models on Kafka and Flink with Triton Inference Server for sub-100ms scoring at authorization.

• Best for: card and payment flows with strict latency limits
• Watch: confirm who maintains streaming infrastructure

9. ELEKS: Custom Fraud Detection for Finance

ELEKS offers custom fraud detection for finance and says it integrates with existing systems to minimize disruption.

• Best for: institutions modernizing legacy fraud tooling
• Watch: request US-based delivery references

How to Choose a Fraud Detection Development Partner

• Data and labels
  • Confirmed fraud labels, chargebacks and investigator outcomes
  • Feature latency at authorization time
• Decisioning
  • Approve, review and decline thresholds
    • Set by your risk team, not the vendor
  • Fallback behavior when the model is unavailable
• Operations
  • Explainable alerts for analysts and auditors
  • Drift monitoring and retraining ownership

Next Step

Planning a fraud detection build? Book a 30-minute LuMay call to map your data, latency target and review workflow into a pilot plan.