How AI can protect against bank fraud scams

We speak to IntelePeer’s Subhash Ramamoorthi, on ways banks can better leverage AI to protect against fraudsters who are continuing ‘to up their game’

AI is an era of rapid proliferation across multiple industries, but is it being leveraged to full effect by banks seeking to mitigate the impacts of fraud and scams? We get the take of Subhash Ramamoorthi, Director of AI Hub at IntelePeer

Why is the need for banks to protect against fraud a growing issue? 

Fraudsters continue to up their game, incorporating more sophisticated and insidious schemes each year. According to a 2023 report from the FTC, US consumers lost US$300m to fraudulent texts last year, a significant increase from US$131m in 2021 and US$86m in 2020.

Moreover, the median loss for individual victims doubled from 2021 to 2022.

The report also found that the most common scam was copycat bank fraud, where bad actors impersonate a reputable FinServ or bank through texts, asking people to verify large purchases. 

By creating a false sense of urgency, the fraudster gets the victim to call a fake bank representative who obtains their information.  

To combat these scams, the financial industry should adopt artificial intelligence (AI), which can detect fraud faster than humans while enhancing communication efforts to combat these deceptive tactics and protect unsuspecting consumers from bad actors.

How can banks intelligently augment fraud detection and protection services?

Perhaps the most beneficial aspect of AI concerning fraud detection is how much faster it is than a human. 

A well-trained AI solution leveraging machine learning algorithms can analyse enormous amounts of data, comparing this information to existing datasets about a user’s normal behavior to spot suspicious or abnormal spending patterns or account activity. 

In fact, the more familiar an AI solution becomes with fraud compared to normal behavior, the faster it becomes at spotting and reducing bank fraud and scams.  

AI can also make sense of data that typically would be meaningless to the human eye. By using AI to integrate data streams from various unstructured sources into warehouses, data analytics solutions can convert this information into usable structured data, allowing for easier identification of fraudulent activity. 

On top of being faster than humans at compiling and analysing data, AI is more accurate. Manual or rule-based fraud detection often results in false positives, meaning that legitimate transactions get mistakenly flagged; however, AI decreases the chances of such errors from occurring.

How can AI power better internal and external communications?

Part of any comprehensive fraud detection and prevention strategy is effective and timely communication internally within a financial organisation and externally with customers and other third-party entities like law enforcement. 

To that end, the automation capabilities of AI can improve and streamline fraud-related communications considerably.

From an internal perspective, AI-powered communication automation will eliminate the need for employees to send notifications or messages manually to various departments or personnel. 

Financial organisations can likewise use AI to automate recurring reports and even remind people to submit fraud prevention budgets on time, saving time and costs while reducing friction. 

Other time-consuming tasks, like risk management and loan underwriting, can be automated through AI solutions, allowing banks to direct their resources and employees toward other high-value initiatives.

Similarly, AI can automate external communications, such as identity verification and two-factor authentication processes. Should a bank detect fraudulent activity, AI can also help deliver automated alerts via email, voice and even the customer's banking app. 

At the same time, AI can automate many processes and tasks associated with compliance monitoring, ensuring banks and financial institutions aren't fined or penalized for not adhering to various regulations.  

Are there any additional benefits of using AI to fight fraud?

Not only will AI help financial organisations (and their customers) save money but also make money. By using AI to increase efficiencies, eliminate false positives and stay compliant, banks can boost customer experience (CX), creating more loyal and trusting customers.

It is more profitable to retain customers than it is to acquire new ones. In fact, it costs up to seven times more to obtain a new customer than to keep a current one. 

Also, 65% of a company’s business comes from existing customers, highlighting the importance of robust fraud detection and prevention capabilities to increase CX. Furthermore, retaining customers means not worrying about them switching to competitors.  

Should AI and communication solution vendors be vetted?  

While many vendors offer effective AI solutions, few have a comprehensive platform capable of seamlessly orchestrating and coordinating various AI solutions and communication tools. 

To that end, banks and financial organisations should prioritise such vendors. Likewise, they should ensure that the vendor's platform can integrate with their existing systems and infrastructure, allowing for smooth interoperability and data exchange.

When selecting a suitable vendor, additional points of consideration include its training and support offerings and scalability and performance capabilities. 

These factors will significantly impact the short- and long-term success of one's platform adoption and AI integration. 

Moreover, it’s advantageous for banks and financial institutions to research a communication vendor’s reputation and to get references from current customers to determine if its AI solutions will be an appropriate fit.

Banks should always vet AI and communication vendors for security certifications, being cautious of those that use self-certification techniques. 

Sending a detailed questionnaire or asking if they have dedicated security teams are helpful ways of determining a vendor’s security capabilities. 

It is also wise to evaluate the vendor's commitment to data privacy and compliance with regulations such as GLBA or PCI-DSS, depending on one’s industry and jurisdiction. 

Ultimately, customers won’t trust banks to protect their financial information if that bank cannot protect itself.

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For more insights from FinTech Magazine, you can see our latest edition of FinTech Magazine here, or you can follow us on LinkedIn and Twitter.
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Please also take a look at our upcoming virtual event, FinTech LIVE London, coming on 8-9 November 2023.


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