Payment fraud has become one of the toughest challenges facing financial institutions. Attack volumes are rising, criminals are using increasingly sophisticated methods, and the time available to respond has shrunk to milliseconds. Customers demand seamless service, while banks face tighter budgets and regulatory pressure, forcing a rethink of traditional fraud strategies.
SymphonyAI, an AI SaaS platform, recently delved into how to improve anti-fraud strategies.
Fraudsters today are less likely to break in than to log in. Social engineering, synthetic identities and industrial-scale phishing have replaced brute force attacks. Even weak passwords can trigger major disruption, with one 158-year-old firm closing and 700 jobs lost after attackers exploited an employee login, SymphonyAI explained. Despite this, many organisations still rely on outdated rule-based systems, ill-suited to today’s real-time environment.
The cost of fraud goes far beyond financial losses. It can damage customer journeys, disrupt service level agreements and trigger heavy compliance obligations. But overly rigid controls are just as harmful, creating false declines, frustrating customers and generating expensive manual reviews. Striking the right balance is essential.
To adapt, institutions are moving from static rules to adaptive intelligence powered by machine learning and real-time analytics. This allows them to detect genuine threats faster, reduce false positives and maintain smooth payment flows. Making fraud a strategic priority delivers tangible benefits: fewer false alerts, better customer experiences and improved risk management.
SymphonyAI is one firm supporting this shift. Its NetReveal Payment Fraud solution uses behavioural intelligence, explainable AI and real-time monitoring to detect threats such as account takeover and bot activity before transactions are executed. Adaptive profiling helps distinguish legitimate customers from bad actors, cutting losses while reducing operational strain.
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