Key takeaways
- Machine learning finds fraud patterns across accounts and networks that fixed rules miss.
- H2O builds explainable fraud models that run beside the fraud engine a bank already has.
- Every false positive has a cost: a declined card at checkout frustrates a good customer, and every alert takes analyst time to close.
AI transaction fraud detection uses machine learning to score every card, debit and wire payment for fraud risk as it happens, and to find patterns across accounts and networks that fixed rules miss. H2O builds explainable fraud models that run beside the fraud engine you already have.
Your rules catch the fraud you have already seen. New attack patterns sit between thresholds, and by the time a rule is written, the fraudsters have moved to another channel. Every false positive costs you too: a declined card at checkout frustrates a good customer, and every alert takes analyst time to close.