Insider Fraud in Banks: The Post- Covid Threat Landscape in a Snapshot

Drawing on primary and secondary research, we've summarised the current insider fraud threat landscape with valuable input from senior banking professionals to understand its consequences for banks, and the best strategies to respond to the challenge.

For banks globally, Covid-19 and the mass shift to remote working have created the highest rates of insider fraud in recent history, calling for long-term strategies to address the threat landscape.

Although insider fraud is typically linked to financial theft, it is not the only threat worrying organisations

The Fraud Triangle

A trifecta of rationalisation, opportunity and pressure

The pandemic has exacerbated many drivers of the Fraud Triangle, creating a perfect storm of conditions for insider fraud.

Rationalisation

A lack of company loyalty and harboured frustrations with leadership stemming from a poor company culture may heighten internal fraud risks through rationalisation.

Opportunity

The lack of direct supervision has introduced new barriers to monitoring employees

40% reference the lack of end-to-end visibility as a challenge in insider fraud and collusion detection.​​​​​​​

Raising concerns as 52% of fraud cases are discovered by employee whistleblowing.

Proximity-based detection, such as whistleblowing, is unreliable in today's work from home and hybrid environments​​​​​​​

Pressure

Many companies are demanding their employees deliver ambitious targets and meet bonus thresholds, pushing employees to take desperate measures to fulfil company demands

26% saw financial strain and uncertainty as key in driving the increase in fraud under Covid-19.

Consequences of Insider Fraud

Here's how our survey respondents ranked insider fraud consequences from most to least concerning

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Best practice

There's no silver bullet; instead, insider fraud mitigation efforts must be layered with several different techniques.

73% said a combination of tools – including artificial intelligence/machine learning, network analytics, and network monitoring is best.

In addition, here are two key considerations to bear in mind when approaching insider fraud strategies.