5 – Graph AI to Combat Fraud in Fintech and Insurtech
09 Nov, 2021
Especially given its dynamic nature, fraud is a major area of concern requiring significant time and resources to isolate from high-volume transaction data. We have developed an innovative new composite AI-based solution with graph-supervised learning coupled with explainability. Alberto De Lazzari LARUS Business Automation Alberto is a passionate technologist who always keeps up with the latest patterns, methodologies, and frameworks. In the past 10 years, he has worked in very different industries, from automotive and fleet management to insurance and banking. Since 2007, Alberto he has been working on legacy and cutting-edge systems as well as a wide range of internalization and integration IT projects. Graphs have been Alberto’s passion since the university, where he wrote a thesis on clustering algorithms and neural networks. He is a contributor to official Neo4j projects, including [APOC](https://github.com/neo4j-contrib/neo4j-apoc-procedures) and [ETL](https://github.com/neo4j-contrib/neo4j-etl-components). Surya Josyula Director, Fujitsu Ltd. Surya Josyula is Director of Marketing at Fujitsu Research of America where he works on outbound initiatives for new innovations including technology incubation and co-creation with customers and partners. Prior to Fujitsu Research, Surya spent 15 years at Sun Microsystems in various engineering and marketing roles.