Outsmart fraudsters with generative AI
IBM® Safer Payments helps you create custom, user-friendly decision models so you can adapt to emerging threats faster and detect fraud patterns with greater speed and accuracy, all without vendor or data scientist dependencies.
Clients report high detection at ultra-low false-positive rates after deploying our solution.
Build, test, validate and deploy machine-learning models in days versus months without reliance on vendors.
Monitor thousands of payments per second. Enterprise-grade solution delivers 99.999% availability and high throughput.
With an open platform, import detection models, model components and IP while using a rich interface to build new models.
How it's used
IBM Safer Payments uses data from actual online and mobile banking sessions. Built-in device ID capability, with device behavior profiling and a device reputation database and biometric parameter recognition hardens this channel.
Build, test, and deploy fraud detection models directly on production data without interrupting real-time processing. Combine rules and machine learning to continuously adapt to evolving fraud patterns and improve detection accuracy.
Detect and prevent fraud across digital banking channels in real time by analyzing user behavior, device signals, and transaction patterns. IBM Safer Payments enables accurate detection of account takeover, scams, and unauthorized activity with low latency and minimal customer friction.
IBM Safer Payments is the most open data science platform for payment fraud prevention currently available in the market. Export and import models in portable PMML format and ingest models or feature extractions as Python code.
IBM Safer Payments provides hierarchical multitenancy. It efficiently manages hundreds of tenants, each customized. Inheritance allows maintenance of central models and configurations.
IBM Safer Payments uses data from actual online and mobile banking sessions. Built-in device ID capability, with device behavior profiling and a device reputation database and biometric parameter recognition hardens this channel.
Build, test, and deploy fraud detection models directly on production data without interrupting real-time processing. Combine rules and machine learning to continuously adapt to evolving fraud patterns and improve detection accuracy.
Detect and prevent fraud across digital banking channels in real time by analyzing user behavior, device signals, and transaction patterns. IBM Safer Payments enables accurate detection of account takeover, scams, and unauthorized activity with low latency and minimal customer friction.
IBM Safer Payments is the most open data science platform for payment fraud prevention currently available in the market. Export and import models in portable PMML format and ingest models or feature extractions as Python code.
IBM Safer Payments provides hierarchical multitenancy. It efficiently manages hundreds of tenants, each customized. Inheritance allows maintenance of central models and configurations.
Case studies
FIS fights financial crime and fraud by infusing AI and intelligence workflows.
Learn how the bank delivered cross-channel fraud protection, resulting in a frictionless and safer payments experience.
