The Risk Within: How are FSIs Using Analytics and Automated Technologies to Combat Insider Fraud?

Sponsored by Bottomline
Thursday 22 July 2021, 12:30
Zoom

Though data breaches and cyber-attacks might steal the headlines, insider fraud remains an ever-present threat for financial services institutions (FSIs). And while cyber defences might be hard to penetrate from the outside, they often do little to stop opportunistic or disgruntled employees from abusing their privileged user status to siphon off funds and data or violate company policy.

Though most FSIs acknowledge the risk of insider fraud, the increasing complexity of IT infrastructure and the distributed Covid-era workforce means that detection of suspicious behaviour has become an increasingly complicated game of cat and mouse.

Distinguishing between malicious and ordinary activity in real-time with thousands of employees –on an array of personal devices – can test any organisation’s checks and balances. Meanwhile, employees - who may lack proper anti-fraud training- may fear reporting suspicious activity out of fear of reprisals, particularly with the culprits often being respected longstanding employees.

As a result, FSIs will continue to pay heavy price for failure, not just in financial and reputational terms, but also in regulatory action and a loss of customer trust. To tackle these challenges, many businesses are turning to machine learning digital platforms which use automated controls to identify suspicious behaviour.

This digital roundtable with industry peers will focus on the key challenges and opportunities FSI leaders face as they attempt to spot the warning signs of insider fraud before it is too late.


Topics for discussion

• How has the risk landscape for internal fraud changed in the past year, and what new methods of concealing fraudulent activities are FSIs seeing?
  
  
• What are the key challenges for FSIs in detecting and monitoring insider fraud risk?
  
  
• How effective are current methods of identifying multiple-employee fraud and cases of collusion with external actors?
  
  
• What role can automated technologies such as AI and machine learning help to detect anomalous patterns of behaviour and flag potential fraud risk?
  
  
• What kinds of behaviour indicate potentially fraudulent activity and what tools are available to detect payment instruction changes?
  
  
• What are the key challenges for FSIs in producing sufficient evidence to investigate potential insider fraud?
  
  
• How can automated risk detection tools helps to reduce investigation time for potential cases of insider fraud?
  
  
• How are FSIs using automated data platforms and real-time analytics to identify high risk employees and behaviour?

Timings:
12:30 – 12:40   Editor’s Welcome
12:40 – 14:00   Topic Discussion

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