Fraud and financial crime controls that keep good customers moving
We help banks, processors and fintechs design fraud, anti-money laundering (AML) and risk platforms that combine rules and machine learning (ML) to catch more fraud, decline fewer good customers and stand up to regulatory review.
What our clients are up against
Fraud that outpaces static rules
Fraud patterns shift across channels, and rules written for last quarter's attacks can miss this quarter's.
Too many false positives
Every good transaction declined or flagged costs revenue, frustrates customers and fills analyst queues.
Rising compliance expectations
Sanctions, AML and reporting obligations keep growing, and examiners expect clear evidence of how each alert was handled.
How we cover Fraud, AML & Risk
Detection engines and models
Combine rules and ML to score every transaction in real time.
- Hybrid rule-based and AI/ML fraud detection engines
- Real-time transaction monitoring and anomaly detection
- Velocity checks, geolocation and risk scoring algorithms
- ML model development, training and tuning
- False positive reduction and precision optimization
- Fraud consortium data and negative database screening
Authentication and channel protection
Stop fraud at checkout and login while keeping friction low for genuine customers.
- 3-D Secure (3DS) integration and strong customer authentication (SCA)
- Risk-based authentication (RBA) and adaptive fraud controls
- Card-not-present (CNP) fraud prevention strategies
- Device fingerprinting and behavioral analytics
- Account takeover and synthetic identity fraud detection
AML, sanctions and identity
Build screening and reporting into the payment flow rather than around it.
- AML screening and Office of Foreign Assets Control (OFAC) sanctions compliance
- Politically exposed person (PEP) screening and watchlist monitoring
- Know your customer (KYC) verification and identity authentication
- Suspicious activity report (SAR) and currency transaction report (CTR) compliance
Investigation, disputes and insight
Give analysts the tools to resolve cases and disputes efficiently.
- Fraud case management and alert triage systems
- Chargeback automation and dispute representment workflows
- Fraud analytics dashboards and business intelligence
Ways to work with us
Architecture review
An independent assessment of your fraud, AML and authentication controls with a prioritized improvement roadmap.
Platform design & delivery
Senior architects who design your detection, screening and case management platform and work alongside your teams and vendors through go-live.
Team training
Hands-on programs that bring your fraud analysts, data scientists and engineers onto the same methods and tools.
Build your team's capability
Our fraud and risk modules can be delivered as a standalone program or tailored to your platform and fraud patterns.
Request informationTraining modules
- Real-Time Fraud Detection Frameworks and Architecture
- Machine Learning for Fraud Detection Workshop
- AML and Compliance Analytics Deep Dive
- Risk Scoring Model Implementation Lab
- 3-D Secure and SCA Integration
- Device Fingerprinting and Behavioral Analytics
- Chargeback Management and Dispute Automation
- Fraud Investigation Tools and Case Management
Services, case studies and tools
Should we use rules or machine learning?
Both. Rules are transparent, quick to change and ideal for known patterns and regulatory requirements. ML models find subtle patterns across many signals and adapt as fraud changes. We design hybrid engines where models score risk, rules apply policy and hard limits, and every decision can be explained to customers and auditors.
How do you reduce false positives without increasing losses?
We start by measuring where false positives come from, then improve the data, features and thresholds behind them. Adding device, behavioral and consortium signals, segmenting rules by customer and channel, and routing borderline cases to risk-based authentication instead of a decline usually helps both fraud and approval rates.
Can you help us implement 3DS and strong customer authentication?
Yes. We design 3DS flows that pass rich data to the issuer, apply exemptions where your rules allow, and step up authentication only when risk calls for it. The goal is fewer challenges for genuine customers and a clear liability position on every transaction.
Can fraud and AML monitoring share a platform?
Often, yes. Fraud and AML use much of the same data, entity resolution and case management. We help you decide what to share and what to keep separate, so investigators see a fuller picture while each team keeps its own policies, reporting duties and audit trail.
Let's strengthen your fraud and AML controls
Talk to a senior consultant about your fraud, AML and risk roadmap.