Fraud detection is a major challenge for merchants that accept electronic payments, acquirers that manage electronic payment networks and for banks that are exposed to various types of financial fraud including money laundering.
Which companies are impacted by financial fraud?
Banks and other companies that receive significant number of financial transactions are at risk of suffering from financial fraud. e-Commerce companies, credit card companies, electronic payment platforms, B2C fintech companies all need to employ software to limit financial fraud.
What are different types of fraud?
Real time risk scoring models are used to score various financial operations to eliminate fraud while managing the impact of false positives.
- Transaction fraud: Fraud committed using credit, debit or prepaid cards in merchants for card-present or card-not-present payments.
- Account takeover: Accounts taken over by hackers leveraging various social or technical vulnerabilities. Analyzing user journeys for behavioral patterns can help detect account takeovers before they cause financial harm
- API fraud: PSD2 introduced a new attack surface that banks need to manage.
How is AI changing fraud management?
Since fraud constantly evolves, it is hard to manage fraud with rule sets. Fraud detection systems should be able to identify new types of fraud which requires detecting anomalies that are seen for the first time. Therefore, detecting fraud is an anomaly detection exercise which is a sub-field of AI application and research.
If you are ready to identify companies building AI-powered fraud detection solutions, you are in luck. We prepared a comprehensive list of AI vendors that have leading edge fraud detection solutions.
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