Application of Graph Model in Fintech and Risk Management
Tens of millions of consumers and businesses around the world rely on Intuit to deliver financial, accounting, and tax preparation software and services. Knowledge Engineering, Knowledge Graphs, and Machine Learning are the foundational technology for Intuit to transform into an AI-driven expert platform.
“We have moved from isolated individuals to a linked, more clustered world and graph analytics has allowed us to better understand our customers and provide a superior service”
Dr. Jing Wang | FinTell Inc.
Fintech applications of Graph Network- Anti-fraud, Loan App Classification, ID-Mapping of Natural Person
FinTell’s AI Lab developed a series of graph learning models that applied in fintech and financial risk management, for instance, anti-fraud models for group fraud and propagated fraud, loan app classification, ID-mapping of natural persons. The models leveraged TigerGraph’s graph engine and a series of bipartite graph frameworks to aggregate modeling features from historical and spatial dimensions. Compared with the baseline model, the graph-based method demonstrated a boost for model discrimination power by the graph learning method and capability of TigerGraph. Business impact in financial risk management will be addressed as well.