Capitalize on the Transaction Data we have Today to Prevent Banking Fraud Tomorrow

For someone familiar with the name ‘Frank Abagnale’ and having seen the movie Catch Me If You Can countless times, the question that always comes to my mind when watching the movie is how the fake physical checks were undetected when he presented them to be cashed.  

While it was easy to become distracted by the charisma that Frank always projected, what additional information would the person on the teller line have needed in order to determine the validity of the checks?  

Checks are a Fraudster’s Favorite
While check volumes have declined from the high of 40+ billion a year in 2000 to nearly 15 billion today, they are still the favorite payment instrument of fraudsters. And because of this, it’s hard to believe that check fraud detection is still a problem across the industry, without many safeguards in place to identify the fraudulent checks until much later in the remittance process.  Catching an exception at this point in its lifecycle is not only expensive but it also has repercussions, such as a negative reputation for the business and financial institution.  

Even though fewer checks are being written today, the value of these checks has increased, as evidenced in the Federal Reserve’s 2018 Payments Study Annual Supplement (see table 1 below), making check fraud attempts more attractive.  

Table: Annual growth rates of checks reported by the Federal Reserve

With the technology and vast amounts of data available today, payment fraud is an attractive target that continues to increase without any signs of abating soon.  Even though fraud prevention is top-of-mind for many, and controls and measures are implemented to restrict the occurrence of such activity, there seems to be extra focus on how to resolve issues.  

Barriers and Challenges to Prevention
Research by Information Security Media Group, published in The 2019 Faces of Fraud, shows the main barriers to improving fraud prevention are:

• Technical barriers: the systems through which a payment is processed do not “talk to each other.”
• Customer experience: the survey responders said that they did not want to add new anti-fraud controls that might, in any way, impede the customer experience within the organization.

The industry now faces a couple of challenges, as well.

• How do we take the vast amount of data that is being generated today and utilize it to our advantage to stop or spot the potentially fraudulent activity before it effects the individual or business?  Although there are many solutions in the market being developed for detecting card or wire fraud using artificial intelligence (AI), not many pay much attention to the “old kid on the block,” checks.
• There are quite a few solutions available today, especially for check fraud, that are standalone applications and have no feedback mechanism to tell the solution where the check originated.  The challenge here becomes how we can collate information from multiple systems and analyze it to spot behavioral trends that can help to detect fraud earlier in the lifecycle of the check.

Another problem is that businesses and financial institutions still rely on the controls that were implemented years ago to fight fraud.  The 2019 Faces of Fraud survey found the top three types of anti-fraud controls deployed today are: 

• Fraud and monitoring systems.
• Enhanced customer education.
• Positive pay, debit blocks and other limits on transactional use.

A Steady Increase in Incidents and Losses. What Now? 
Regardless of the fact that these are the systems in place today, we need to ask questions about the effectiveness of the tools if nearly 80% of the survey respondents see a steady rate or increase in fraud incidents, and about 70% see steady or increased fraud losses. In addition, most of the processing systems in the market still follow the old regimented workflows and don’t provide the flexibility to incorporate new processes easily.

With the variety of deposit channels available to customers today, check fraud is more likely to occur away from the financial institutions’ branches, making the need of the hour to provide newer solutions that: 

• Take advantage of the plethora of data that is being collected with each check deposit and build systems that help identify anomalies in deposit behavior.
• Incorporate newer and better mechanisms to evaluate the image of each check to spot a potential fraudulent item.

Alogent is committed to helping its financial institution partners fight check fraud across all points of presentment with AI and machine learning modules that are tailored to the specific channel of acquisition. By combining technology with the FI’s own business rules, the organization gains a customized fraud review workflow.

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