Real-time fraud prevention that your own team controls
IBM Safer Payments scores every payment before it completes and lets your fraud analysts change rules and models themselves, within hours of a new pattern appearing. We implement it, integrate it with your payment systems and stay with you in operation.

What you get with IBM Safer Payments
Decisions before the payment completes
Each transaction is scored in real time, so a fraudulent payment is stopped and not investigated after the money is gone.
One solution for all channels
Cards, online banking and real-time payments are protected together. Behaviour is profiled across channels, which lowers false positives.
Rules your analysts can read
Machine learning proposes new countermeasures as readable rules that your experts review, change and approve. There is no black box.
Updates in hours
New and revised models need far less data than neural networks do, so you react to a new fraud pattern within hours of it emerging.
Any data science you choose
Use machine-learning and AI techniques from any vendor or from open source alongside the built-in ones.
Configured by you
Everything is user-configurable and adapts to your data model. A new data feed is set up in minutes, without waiting for the vendor.
Why a third generation
First-generation fraud systems relied on counters and hand-written expert rules. They are simple, but cannot keep up with the number and complexity of fraud patterns.
Second-generation systems train models on past data, usually at the vendor’s site. By the time a retrained model is back in production, the patterns it detects are old, and you carry the losses in the meantime.
IBM Safer Payments belongs to the third generation. It learns from your own data and turns what it learns into rules that people can read. A custom model becomes affordable even for a small or medium-sized processor, because it needs much less data, and it is tuned to the fraud patterns you actually see.
Tools for the people who fight fraud
- Monitoring of every rule. The system tracks how well each countermeasure performs and points your experts to the ones that are losing effect.
- Simulation. A change is tested on past data before it goes live, so you know its effect on fraud caught and on false alerts.
- Suggestions from the system. New countermeasures are derived from the data and presented to your analysts for review.
What we do for you
- Solution design. A workshop on your fraud prevention objectives, functional requirements and architecture.
- Integration. Real-time and batch integration with your payment systems, switches and channels.
- A day-one model. Rules and models based on known fraud patterns, so you are protected from the first day.
- Go-live. Environments configured for high availability and performance, user acceptance testing and training.
- Operation. Periodic audits of rules and models, data science for fraud prevention and guidance for your analysts.
Legatus
Legatus is our own platform built around IBM Safer Payments. It adds device intelligence and an integration layer for complex payment environments. Read about Legatus.
News, cases and resources on IBM Safer Payments
DIGIPAY 2026: real time is now a regulatory requirement
IBS Bulgaria was again a main sponsor of DIGIPAY, the conference for secure digital payments. Svilen Stanchev gave the keynote Real Time Is Now a Regulatory Requirement.
Read more →IBM Safer Payments 6.10: XGBoost models and faster investigations
The new version trains boosted-tree models on your own history, lets analysts look at an account without opening a case, and gives investigators layouts built around their work.
Read more →IBS and Coliance join forces
IBS and Coliance join forces on integration and financial crime prevention
Read more →IBS Partners with BORICA to Deploy IBM Safer Payments
IBS Partners with BORICA to Deploy IBM Safer Payments Across Bulgaria's National Payment Infrastructure
Read more →AI/ML in IBM Safer Payments
A white paper on when deterministic profiling outperforms machine learning in fraud prevention, when ML adds real value, and what large language models can do in a production fraud operation.
Get the document →Modernizing Payment Fraud Prevention
A white paper on the payment fraud challenges facing financial institutions, payment processors and national payment infrastructure operators in 2026 and beyond.
Get the document →
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