Transaction Fraud Prevent Fraud and minimize losses
DETECT AND PREVENT FRAUD IN REAL-TIME
Our approach focuses on transaction data that can, if available, be augmented by non-monetary data such as IP address, device ID and more.
This method provides accurate fraud detection in environments where limited data is available while simultaneously reducing false positive alerts.
Key benefits
Detection of unusual transaction patterns
Real-time processing of transactions
Reduce investigations with automated decisioning

Fight Fraud and improve AML compliance with a holistic view
By combining Fraud and AML (FRAML) efforts, Fraud professionals and AML compliance officers can combat crime with a consolidated system.
- Minimal migration and integration effort (<4 months) due to the most modern tech stack, offering unlimited scalability in any cloud environment
- Better Fraud and AML detection due to a holistic customer view from Customer Screening, Customer Risk Rating, AML Transaction Monitoring, Fraud Detection, and Payment Screening
- Reduced investigations with automatic AI decisioning utilizing a smart and self-learning system to decrease manual reviews. Our intelligent AI models learn from customer context and past operator decisions
SPEED UP INVESTIGATION WITHOUT TRADITIONAL SILOS
Transparent data in natural language, augmented by graphical explanations of AI models and risk indicators, helps fraud and AML analysts investigate cases faster.
Information presented in a single interface, rather than traditional data silos, reduces time spent per case, reduces regulatory risk and increases employee satisfaction.


REDUCE CUSTOMER FRICTION THROUGH AI-BASED FALSE-POSITIVE REDUCTION
Blocking legitimate transactions is a key friction point in the customer journey.
Hawk AI uses traditional rules augmented with AI to reduce false positives, leading to fewer upset customers. Our AI models are constantly retrained with operator feedback and cross-institutional learnings, understanding normal customer behavior and effectively identifying falsely alerted cases.
In the instances where transactions are blocked, real-time response ensures customers and analysts are fully informed.

THE MOST EFFECTIVE WAY TO SEARCH FOR KNOWN FRAUD & MONEY LAUNDERING PATTERNS
AI powers rule-independent detection of known fraud typologies to deliver well-explained, comprehensive fraud alerts, immediately stopping any type of suspicious transaction.
Our Pattern Library contains a wide variety of pre-trained, off-the-shelf AI models for complex fraud typologies. We make new patterns available to all customers immediately, without additional costs.

BEHAVIORAL ANALYTICS DETECT DEVIATIONS FROM EXPECTED BEHAVIOR
Behavioral analytics flag deviations from expected behavior. Our models learn customer transaction patterns, allowing for detection of fraud without the need for fixed thresholds.
- Catch deviations from normal customer behavior in the context of similar customers in their peer group
- Detect and prevent new, emerging fraud patterns to stop payments in real time
- A key safety net that considers deviations on all data points, finding unknown events pointing to suspected fraud

Self-Service Configuration
Fine-tune the algorithm and conduct what-if analyses based on real data in a sandbox, committing changes only when you are ready.
Configure user management, roles and workflows yourself at any time with our no-code configuration manager.
Do you have a question, RFI/RFP or demo request?
Our teams are happy to assist with any questions you may have about our products, our mission or the AML surveillance industry.
To ensure a fast response by the most relevant team member, please fill in all the form fields and leave us a detailed message.
Get in touch for a demo
Discover how HAWK:AI helps you efficiently comply with transaction monitoring goals.






Further solutions
Payment Screening
Screen counterparties against Sanctions and Country lists in real-time. Cleanse data and tune name-matching.
Customer Screening
Screen customers against Sanctions, PEP, watchlists, and adverse media during onboarding and thereafter.
Customer Risk Rating
Dynamically score customer risk using internal and external data. Add behavioral analytics for richer context.
TX Monitoring
Monitor any transactions for red flags using a comprehensive set of rules in combination with Behavioral Analytics.