Financial Crime World

Swiss Banks: AI-Based Fraud Detection Tools Gain Importance

As attempts to defraud banks continue to rise, Swiss financial institutions are increasingly relying on artificial intelligence (AI) to detect and prevent fraud. According to Joël Winteregg, CEO of NetGuardians, the key to staying ahead of cybercriminals lies in using machine learning technologies that can analyze vast amounts of data and identify suspicious transactions before they occur.

The Costs of Fraud

Globally, the costs of fraud are estimated at around $70 billion annually, with 70 percent of cases involving employees. In Switzerland, a recent case involved a former wealth manager accused of stealing 3 million Swiss francs from customers’ accounts over two years.

External Threats

External threats also pose significant risks, including:

  • Malware attacks
  • Phishing
  • Social engineering

Malware such as “Retefe” continues to evade detection, with over 90 e-banking sessions being diverted daily to fake sites in Switzerland. Social engineering involves criminals using stolen information to impersonate officials or steal identities. Bill swap fraud, which involves manipulating electronic invoices, is another growing concern.

AI-Based Solutions

Banks are increasingly turning to AI-based solutions to stay ahead of these threats. NetGuardians’ CEO believes that proactive detection is possible through profiling and machine learning technologies. By analyzing a customer’s typical transactions, behavior, and other factors, banks can prevent suspicious activity before it occurs.

  • The company’s in-house solution combines multiple variables to reduce false hits by over 80 percent.
  • While AI solutions are highly effective, human intelligence remains essential for making operational risk and fraud decisions.

Implementing AI Solutions

To implement these solutions, banks need to consider data collection and storage carefully. NetGuardians’ technology relies on existing bank data from core and peripheral systems, which can be leveraged to improve machine learning algorithms.

Future Developments

Experts predict that AI-based fraud prevention solutions will continue to evolve, incorporating:

  • Markov chains
  • Additional data sources such as social networks
  • Behavior- based biometrics

As the battle against cybercriminals intensifies, Swiss banks must remain vigilant and adapt their strategies to stay ahead of emerging threats. With AI-powered solutions, they can proactively detect and prevent fraud, protecting customers’ trust and reputation.