The key to beating fraud: Leveraging collective intelligence

by George Iddenden
Collective intelligence

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What is this article about?

The article discusses the persistent issue of ineffective information sharing in the payments industry amidst advancements in artificial intelligence and machine learning for customer profiling.

Why is this important?

Because there is a critical need for improved information sharing and collective intelligence in the payments industry to effectively combat fraud, emphasising the importance of real-time collaboration, data sharing, and regulatory support to protect consumers and foster innovation.

What’s next?

The next steps for the payments industry involve implementing pragmatic and collaborative solutions, prioritising internal sharing, defining specific problem statements, and gradually expanding cooperation. Regulatory support, incentives, and a focus on iterative improvements will be crucial to building effective defences against fraud while balancing data-sharing concerns and ultimately fostering innovation in the industry.

Despite significant advancements in artificial intelligence and machine learning for profiling customers, a crucial issue remains among industry bodies: the lack of effective information sharing.

Panellists at The Payments Association’s annual Financial Crime 360 conference discussed how leveraging collective intelligence might be the key to unlocking a new defensive mechanism against fraud.

As fraudsters continue to find new ways of defrauding customers of their money, the payments industry has struggled to keep up with the sheer size of the problem. However, it has become clear that industry insiders across the globe have settled on vaulting the barrier that is a lack of collaboration in real-time as a proper means of defence.

Internal collaboration within organisations, exemplified by the sharing of anti-money laundering alerts, has emerged as a fundamental strategy. Simultaneously, a lack of transaction-level sharing and the importance of sharing data at the point of transaction between sender and receiver firms has been recognised as a hindrance to the sector’s efforts.

To make progress in prosecuting fraudsters and to maintain a deterrent against them, the industry must find easier ways of helping the rule of law. Payment Systems Regulator (PSR)’s Jonathan Williams believes that data intelligence sharing doesn’t just stop with the payments industry.

“We have to be in a position where we can package up the evidence that we’ve provided and give it to investigative teams to then go and prosecute those forces,” says Williams.

While many are in agreement that pooling collective intelligence could be a great way of halting the growth of payment fraud, there are some legitimate concerns over how the data could be used and who has access to it during the sharing process.

Data sovereignty will be a primary concern for organisations considering sharing real-time data. Mehtaj Syed, vice president of global client engagement lead at Liink by J.P. Morgan, shares his concerns at Financial Crime 360, “As the owner of the data, do I have control over where that data is being shared, how the data has been shared and who it’s being shared with?”

He points out that an institution cannot be completely sure how data is being used once it’s been transmitted; this is a problem for the wider adoption of more data-sharing practices across the industry.

“Once I decide to share that data outside of my organisation, how securely is it being transmitted to the other organisation and once it reaches the other organisation, how is it being used?”, Syed adds.

Syed claims that to justify the investment in real-time data sharing, financial services firms want to see “immediate customer impact”. Solutions must demonstrate “there is technology out there which ticks all these boxes” from a business perspective.

The need for evidence on just how data-sharing solutions can enable better business outcomes, including insights for customers or helping sales teams is imperative to the progress on the issue.

Syed claims that unless a clear business case is presented to firms, data-sharing solutions will only be seen as “good to have” rather than a “must have” solution.

Williams acknowledges that “clear incentives” are necessary to build out the tech and construct a business case, he says: “I think we’re in the stage where we’ve now got the incentives for the industry to work very effectively on prevention. I just think we need to make sure that the tools are ready and effective to build those out.”

Rather than building out large multifaceted data-sharing frameworks as a first step, organisations should first define the specific problem statement they are trying to solve.

Syed suggests that once this has been identified, organisations should then identify the existing ecosystem of participants relevant to that problem, such as fintechs, payment service providers and banks.

“I think the first step is to define the problem you’re trying to tackle — that problem already has an existing ecosystem.

“That makes a much stronger case for that ecosystem to be involved in data sharing instead of going in the other way, saying ‘I have a large ecosystem, I want to build collective intelligence. Can you please let me start sharing data?’ You have to start with the ecosystem.”

While data sharing presents challenges, there are promising areas to focus efforts that could help make meaningful progress.

Beginning with internal sharing, and then prioritising key counterparties and specific problems, demonstrates value and builds trust for expanded cooperation.

Regulatory support and incentives will also be crucial. Most importantly, an iterative, collaborative approach is needed — starting small, proving solutions, and continually improving.

If industries collaborate pragmatically around real issues rather than frameworks alone, the industry can better protect consumers while enabling innovation.

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