Description
Identify fraudulent activity using unusual payment transaction patterns and other data
Technology & data
*** check categry and function
Linked Case Studies
Case Study
OCBC Bank
OCBC bank reduces number of false positive financial transaction alerts by 35% with machine learning
Case Study
Revolut
Revolut reduces bank card fraud using machine learning to detect anomalies
Case Study
Danske Bank
Danske Bank prevents card fraud with the use of machine learning
Case Study
Monzo
Monzo decreased pre-paid card fraud to 0.1% and false positive rate to 25% using machine learning
Case Study
Chime
Chime decreases basis point loss by 40% using a machine learning fraud detection platform
Case Study
eBay
eBay research identifies 40% of credit card fraud with high precision automatically using machine learning
Case Study
Lyft
Lyft delivered a 40% increase in potentially fraudulent users detected without increasing false positives by using neural networks
Case Study
NatWest
NatWest Bank prevents over £7m worth of corporate fraud by using machine learning to detect suspicious invoice payment activity
Case Study
Western Union
Western Union reduces fraud rate to below 1.2% using machine learning models for detection
Case Study
American Express
American Express identifies $2 billion in potential annual incremental fraud incidents with machine learning
Case Study
Danske Bank
Danish Danske Bank increases payment fraud detection by 60% and reduces false positives by 50% with machine learning
Case Study
ClearBank
Clearbank combats fraud and money laundering with the use of machine learning
Case Study
Mastercard
Mastercard achieves 11% increase in transactions approval and a reduction in fraud with the use of deep learning
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Editor: sdg