Use CaseLegal and Compliance

Identify and manage potentially fraudulent activity

Determine whether a transaction should be blocked because it involves some kind of fraud (e.g. credit card, identity, etc.). Detect suspicious customer activity comparing to their normal behaviours and also to behavioural norms in their customer segment.

Cost

Cost - Fraud reduction

Description

Linked Case Studies

Case Study

SMFG

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

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Case Study

AstraZeneca

AstraZeneca plans to crack down on online sale of counterfeit drugs in China using machine learning and natural language processing

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Case Study

Paypal

Paypal keeps fraud losses at about one-third of industry average using machine learning and deep neural networks to predict whether a transaction is fraudulent or normal

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Source: kaggle.com · Editor: original-sdg