$2.90
210%
$14.7 Trillion
Retail Banking
New Applications and Transactions
De-risking Digital Banking
The Challenge
Retail banking services have become immensely more popular due to mobile applications and their associated convenience. Inherent in these apps is an immense increase in risks due to remote access and new technology.
The Solution
Early AI adopters have higher sales growth and profit margins — and the performance gap with the laggards is expected to widen further.
Customizations of models can further expose previously-undetected fraud or optimize for any risk-related outcome. Furthermore, multiple models can be applied to different transaction streams for maximum accuracy and flexibility.
Recommended Products & Solutions
A user-friendly case management portal that allows you to set your own rules and review transactions efficiently and accurately.
Machine learning models are expertly engineered with the nuances of your business and industry already built in.
Visualize your real-time data to extract actionable insights, isolate risk and improve your business processes.
Shield serves as your early warning system by detecting malicious bots, fraudsters and other bad actors as they arrive on your site.
Monitor third-party data sources to benchmark your company’s performance including risk intelligence on payment methods, dark web data, IPS vulnerabilities and marketing channels.
Confirm users credentials through login scoring, multi-factor authentication or out-of-band applications.
To the Victor Go the Spoils
Early experimentation with AI-enhancements in consumer banking is critical. Fraud.net makes the complex process of applying AI in risk-based use cases much easier. With minimal seed data about the transaction, Fraud.net can greatly increase the quantity and quality of the data, automatically test thousands of model algorithms and parameter combinations, and generate an optimized model, helping the bank make better decisions more quickly.
Make Better Decisions
Professional fraud rings have long been attacking merchants, shipping high-value goods to vacant homes, changing neighborhoods and IPs to circumvent existing detection efforts.
Professionals and opportunists can both be quickly exposed using machine learning, collective intelligence and ‘linked-entity’ analyses, all available in Fraud.net’s real-time enterprise detection and analytics platform.