Financial Services
Case StudySMFG

SMFG, the Japanese financial services company, uses deep neural network to analyse credit card transactions and predict fraud with an 80-90% accuracy

SMFG, the Japanese financial services company, uses TensorFlow deep machine learning framework to analyse and identify fraudulent transactions. They claim to be able to predict fraud with a 80-90% accuracy.

Context

"...SMFG is one of the largest financial services company in Japan, who created a machine learning based credit card fraud detection system. Some types of frauds are hard to detect, and manual monitoring requires lots of time and resources to be effective."

The Project

"Instead of manual intervention, the fraudulent cases can be automatically captured with an accuracy of 80 to 90 percent, even for the most difficult cases. For their system, they used a deep neural network to achieve this."

AI Usage

Deep Neural networks monitoring transactions with TensorFlow.

Data

Credit card transactions

Results

80 - 90% accuracy even for the most difficult to detect frauds.

Back to Case Studies
AI Daily Brief — leaders actually read it.

Free email — not hiring or booking. Optional BPAI updates for company news. Unsubscribe anytime.

Include

No spam. Unsubscribe anytime. Privacy policy.