Kyoto Bank develops in-house AI to detect window dressing based on 10 years of financial statements and employee expertise
Kyoto Bank has developed two types of machine learning models called "window dressing detection model" and "fraudulent transaction detection model." This follows an increase in window dressing cases and rising risks of account misuse such as special fraud and money laundering.
Kyoto Bank has developed two types of in-house machine learning models: a "window dressing detection model" and a "fraudulent transaction detection model." The development utilized 10 years of financial statements and the expertise of bank employees.
The background for this development is the increasing number of window dressing cases in financial statements and the rising risk of account misuse, such as special fraud and money laundering. By incorporating the perspective of AI (Artificial Intelligence), the bank aims to strengthen and multilayer detection to more reliably see through fraud.
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