A new press release reports, “NICE Actimize, a NICE business and leader in Autonomous Financial Crime Management, is introducing its Federated Learning capability that will provide financial services organizations (FSOs) with higher fraud detection rates across numerous fraud scenarios by leveraging NICE Actimize’s Collective Intelligence network. With this innovative cloud-based approach that uses machine learning analytics, FSOs can protect their institutions more effectively against multiple fraud typologies, including real-time payments fraud, while improving customer experience.”

The release goes on, “Traditional machine learning approaches require that the entire dataset is centralized. Meaning, there needs to be a specific database where the data resides to give FSOs the ability to build targeted analytical models based on this dataset. However, FSOs are often reluctant or prohibited from sharing datasets from a centralized location. To overcome this challenge, NICE Actimize is applying an innovative method of Decentralized Artificial Intelligence that includes federated learning of models learned in segregated datasets. The models are built for each organization separately, based on its own data, later to be utilized as features in the required context. Through its application of Federated Learning, NICE Actimize has achieved compelling results in improving value detection rates. Using this approach has also proven to be effective in easing the process of model governance. Additionally, since the method is model agnostic, it can be applied across the range of NICE Actimize fraud solutions for different applications.”

Read more at Business Wire.

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