How banks can fight generative AI fraud threats

Organized crime networks, state actors and other sophisticated thieves are finding new ways to circumvent the fraud defences of financial institutions. Highly professional criminal groups are using generative artificial intelligence (GenAI) to bypass authentication controls through email, text and phone phishing campaigns. They’re also defrauding banks and their customers using highly believable deep fakes, including AI-generated voices that can undermine speech recognition controls.

The ease with which criminals can access these advanced technologies is creating even more complexity for financial institutions already grappling with a surge in fraudulent e-transfers, digital account openings and cheques. This means that even those financial institutions that recently transformed the way they fight fraud must continuously revisit their strategy to keep pace with the evolving threat landscape.

GenAI is clearly creating new threats for financial institutions. But it’s also bringing unprecedented promise to how they detect, investigate and prevent fraud.

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Building a human-led and tech-powered foundation to detect and prevent fraud

Many banks are already exploring how GenAI can enhance their transaction monitoring capabilities, spot emerging threats and bolster their defences. But there are risks in moving too fast without putting critical tools, capabilities and skills in place. At the same time, going too slow can leave organizations vulnerable—especially when first movers are already using the technology to increase their effectiveness, reduce costs and enhance their customers’ experiences.

Finding the solution that’s the right fit for your organization is crucial. But fighting fraud requires more than technology and the skills to deploy it. It also takes human ingenuity, understanding and problem-solving capabilities. Pairing new tools with deep industry and functional expertise helps you develop a solid understanding of the challenges you’re looking to address and builds trust in the outcomes you’ll achieve.

Gaining clarity and confidence in a crisis

When fraud occurs, financial institutions need to take a thorough, professional and independent approach to their investigation. Our forensic services team uses its extensive experience with data analytics tools and forensic technology to collect and analyze evidence, gather intelligence and conduct interviews—providing you with credible advice you can be confident in.

By uncovering facts and bringing clarity to the situation, we help you quicky respond to and recover from a crisis. We can also help you address issues found during an investigation, including control gaps, regulatory matters and governance improvement opportunities.

How financial institutions can get ready to combat fraud using GenAI

Prepare your data for GenAI

Using GenAI at scale requires a modern data architecture that integrates, standardizes and synthesizes information from various sources. Many organizations will need to review their data governance and management practices and explore the quality and availability of their data.

But as criminal attacks become even more complex, it becomes even harder for financial institutions working on their own to know which risk factors are most important. Looking beyond your own company’s walls by collaborating, networking and using consortium data helps manage this complexity. Additionally, working with an outside advisor that takes an intelligence-led approach to fighting fraud gives you better visibility into the distinct risks facing your wider industry and helps you rapidly incorporate new threats into your fraud scoring models.

Create controls that lead to smart decisions

Designing effective controls is a powerful precursor to using GenAI to automate some of the manual processes that many banks use to detect fraud. For example, consider the disputes management process. The considerable and growing volumes of fraud and non-fraud disputes, as well as the labour needed to process these cases, are significantly increasing operating costs in this part of a bank’s business.

Creating a baseline level of controls that guide time frames and align to a bank’s risk appetite lets organizations apply an artificial intelligence overlay that supports straight-through processing. This lets you set a defined level of risk, reduce costs and resolve matters faster for affected customers.

Implement responsible GenAI principles

GenAI can make connections and find patterns that may not be obvious. But unstructured, unreliable and incomplete data introduces noise and creates gaps that a large language model may try to fill in ways that could introduce unintentional risks.

It’s important to understand these risks by taking a holistic and multi-dimensional view to GenAI from the get-go, rather than looking at it as a tech-only decision or process. Designing a responsible approach to GenAI at the very beginning of your journey helps you define opportunities to use the technology to create business value without risking your reputation.

Align your workforce and technology strategies

GenAI raises significant workforce questions for companies. Financial institutions that use artificial intelligence to automate case creation and evidence management processes will face pressures to align their technology roadmap with their workforce strategy. They’ll need to consider how GenAI will affect areas such as learning and development, performance management, rewards, recruitment and onboarding.

One specific area to consider is the strategic redeployment of staff previously tasked with manually collecting data from various sources to assess potential fraud cases. These employees will now have more time to spend on value-add activities such as performing assessments to understand what happened and identifying growing volumes of fraud. Organizations can also use this additional capacity to train and coach their teams to better assess potential areas of fraud.

Crucially, employees will also have more time to communicate with affected clients—providing customers with more details about what happened, how they’re affected and the next steps. These difficult conversations can mitigate the traumatizing impact of fraud and help preserve a bank’s reputation.

A new approach to fighting financial crime

Highly organized criminal groups are finding ways to overcome established approaches to fraud prevention and detection. But we’re seeing promising GenAI applications that can help financial institutions effectively and efficiently keep pace with the evolving fraud landscape.

Combining human ingenuity with the right technical tools can help you prepare to use the power of GenAI to prevent and detect fraud. Companies that collaborate and share information through strategic ecosystems and relationships, build the right data foundations and nurture in-house talent can pinpoint previously overlooked patterns and anomalies while reducing the time agents spend aggregating case information.

This enhances the experiences customers have with your brand beyond reducing the risk of catastrophic financial losses. Customers can use your services with greater confidence, knowing your staff won’t block their payment cards unnecessarily and will swiftly resolve any suspicious transactions. This helps you build trust while delivering sustained outcomes that create value for your organization and its customers.