Faster, More Accurate Fraud Detection
ACI’s incremental learning techniques make your fraud prevention work both harder and smarter. Developed by ACI’s expert data science team, this patent-pending technology takes machine learning to a new level by:
- Adapting to changes in fraud and spending patterns in real time
- Increasing the accuracy and lifespan of existing models
- Reducing the resource demands on your internal teams
Incremental Learning Proof Points
Tests carried out on data from three major retail customers revealed that, while standard self-learning
or adaptive models began to degrade after three months, ACI’s incremental models maintained their
performance over the full 13 months of the test.
See how incremental learning differs from self-learning.
Leverage Data to Prevent More Payments Fraud
These machine learning techniques leverage global consortium data to build complete customer profiles, spot emerging fraud signals and combat fraud threats.
New to machine learning? Check out this infographic.
Machine Learning Models Geared to Your Industry
ACI offers a range of machine learning models for banks and merchants, which can be developed and trained on a single customer’s data or using consortium data gathered from a group of customers.
Strengthen Your Fraud Solution with Unparalleled Expertise
ACI’s Data Science team continuously monitors the performance of our machine learning models and reviews shared intelligence to stay one step ahead of fraudsters. These data scientists are supported by ACI’s global team of risk analysts and fraud consultants, and work closely with our customers and partners across the payments ecosystem.
As part of our commitment to the continued development of data sciences, ACI is a proud sponsor of the European DatSci & AI Awards.