Fraud Prevention Blog Series with Expert Sean O’Malley, IDC

Sean O’Malley, Research Director, Compliance, Fraud and Risk Management, IDC
Fraud Prevention Blog Series with Expert Sean O'Malley, IDC

Recession Impact on Fraud Incidents: The Need for Real-Time Prevention

During the 2009 recession, the Association of Certified Fraud Examiners (ACFE) published a survey (Occupational Fraud: A Study of the Impact of an Economic Recession) and found that 55.4% of respondents said the level of fraud has slightly or significantly increased in the previous 12 months during the recession. The same survey also found that 49.1% of respondents stated the increased fraud was due to financial pressure on individuals. 

Recessions always significantly impact many individuals. In recessionary times, companies will often have to cut headcount to reduce staffing expenses, resulting individual job losses. When job losses increase across the economy, there is greater financial strain on individuals affected, either due to job loss directly, a reduction in wages, or uncertainty about the future. The increase in financial strain, job loss, and uncertainty incentivize some individuals to look for a new job or new ways to make money. 

As increasing numbers of individuals seek new employment—with many looking quite urgently in order to pay their mortgage and keep their home or maintain their lifestyle—the number of employment fraud scam incidents increases. Financial scams also tend to increase during periods of economic stress because some individuals find themselves looking for additional or alternative ways of generating income to either supplement lower income or replace income they’ve lost. 

The connection between increased levels of fraud and economic shifts like recession has been widely acknowledged by fraud industry experts and banks. However, traditional fraud detection methods have limited banks’ ability to reduce the quantity of fraud incidents and losses. One of the reasons for this limitation is the reactive approach to fraud identification, especially when using antiquated technology. 

In the past, many banks processed fraud and financial crime alerts generated by fraud detection technology as a batch process, resulting in delays in identifying fraud incidents. Some alerts were already over a month old by the time they were reviewed by fraud or transaction monitoring analysts, which can further delay the investigation. This process can take several weeks to complete and even longer if the institution decides to file a Suspicious Activity Report (SAR) based on the fraud alert and investigation. 

While this process may be reasonable for identifying and reporting fraud incidents, it’s not particularly effective at preventing fraud. By the time fraud is identified, the transaction is already completed, making it challenging to recover lost funds.   

To reduce fraud losses, there is increasing focus in banking for fraud solutions that enable real-time identification of potentially fraudulent activity. Banks are no longer willing to accept technology that identifies and reports fraudulent activity well after the actual incident. Banks want fraud solutions that provide them with the capabilities of identifying potentially fraudulent transactions in real time, complete with analysis and quick decision-making regarding the transaction(s) associated with the potentially fraudulent activity. 

A significant number of newer fraud solutions that are successful at identifying, analyzing, and therefore preventing fraudulent transactions in real time rely on cloud computing that capitalizes on the use of artificial intelligence and machine learning. The computing power available through a cloud-based solution using artificial intelligence and machine learning enables the processing of large data sets rapidly enough to provide real-time intelligence. 

Based on results of the analysis completed by the cloud computing fraud solution, it’s possible for transactions to go forward and be completed, or for the information and analysis to be sent to the fraud department for additional research conducted prior to deciding on the ultimate disposition of the requested transaction(s). Put simply, banks must have the computing speed to conduct analysis and identify potentially fraudulent activities in real time before the completion of transactions associated with any particular fraudulent activity.

Message from the Sponsor  

NICE Actimize has a long history of working to help banks identify and prevent losses due to fraud. Due to this extensive experience developing and enhancing solutions in fraud detection and remediation, they are in a strong position to help banks both identify potentially suspicious transactions involving fraud and prevent such transactions from being completed, thus preventing fraud. Banks taking an increasingly proactive stance against fraud stand to gain financially, by decreasing financial losses due to fraud, and reputationally, by helping to reduce potentially embarrassing incidents of fraud that could negatively impact the perception of the bank in the eyes of their customers.  

To read more about NICE Actimize’s real-time fraud detection solutions visit this page.

The Future of Fraud Prevention

Fraud loss amounts have been increasing in recent years, and are expected to keep rising, with each year setting a new high. The Federal Trade Commission has reported that about 40 million Americans have been victims of fraud. That’s approximately one in six people in the United States who have been defrauded. Inside the U.S., fraud losses reported to the Federal Trade Commission were $8.8 billion in 2022 and $6.1 billion in 2021, representing an increase of over 40% in one year. [Note: These numbers do not include the $308.6 billion of insurance fraud, as reported for 2021 by the Coalition Against Insurance Fraud.] 

Global fraud losses are estimated to be around $41 billion in 2022 and were estimated to be approximately $34 billion in 2021. Forecasts for fraud losses in 2023 range between $48 billion and $53 billion. With billion-dollar losses comes scrutiny on the processes financial institutions use to detect fraud faster and mitigate risk. 

In banking, the typical process for identifying and reporting fraud has been relatively consistent over the past several years. The process often starts by developing a series of fraud typologies that describe the transaction patterns and financial services products associated with different types of fraud techniques. These fraud typologies are used as the basis to develop a set of rules for identifying potential fraud incidents. These rules are then used to evaluate financial transactions and customer accounts for potential indications of fraud. When there is a “hit” on one of the rules used to identify fraud, it generates an alert. 

The alert will then be entered into a case management system, which is designed to capture all alerts generated and is structured to provide process flow management for alerts. Once an alert is generated and enters the case management system, there are generally two possible options the alert can follow in the case management process. First, the alert can be evaluated and analyzed, typically by someone employed as a fraud analyst and dispositioned as an alert that requires No Further Action (NFA), effectively closing the alert at that point. The second option is to escalate the alert for Investigation.

Alerts escalated for investigation are assigned to a fraud investigator. This individual gathers more documentation and evidence to support the final decision with respect to the Investigation. Just like the two options for alerts, there are typically also two options for an investigation. The investigation can be dispositioned as NFA, closing the investigation, or be escalated to a recommendation to file a Suspicious Activity Report (SAR) with a department within the U.S. Treasury Department known as the Financial Crimes Enforcement Network (FinCEN). 

One of the most significant impacts of the standard fraud identification process is also one of the most apparent: usually where there has been actual fraud, it’s detected after the fact. Using the current standard process, all incidents identified as fraud can be tracked, reported, and quantified, but in most cases, not prevented. 

The fight against fraud is constantly evolving, and advanced analytics such as artificial intelligence (AI) and machine learning (ML) are leading the charge in detecting and preventing fraudulent activities in real time. By identifying fraud incidents based on typology, banks and other financial institutions can detect fraudulent activities earlier in the fraud cycle and streamline their review processes for greater efficiency. This is critical in light of the rising fraud loss amounts. 

The increased use of advanced analytics and real-time reporting has made it possible for banks and financial institutions (FIs) to proactively identify and prevent fraudulent activities. By leveraging cutting-edge technology, FIs can stay ahead of the curve and protect their customers from the ever-evolving tactics of fraudsters. 

No longer is the future of fraud prevention dependent on the tuning, or optimization, of a static set of rules that are insufficient to work in real time. The future of fraud is using advanced analytical solutions capable of preventing fraud before it happens. IDC believes that fraud solutions of the future will be increasingly focused on fraud identification and prevention in real time. Banks and financial institutions who pursue and adopt such real-time fraud solutions will not only increase their profits by reducing fraud losses, but also gain in reputation as leaders of fraud prevention. 

Message from the Sponsor

NICE Actimize has a long history of working to help banks identify and prevent losses due to fraud. Due to this extensive experience developing and enhancing solutions in fraud detection and remediation, they are in a strong position to help banks both identify potentially suspicious transactions involving fraud and prevent such transactions from being completed, thus preventing fraud. Banks taking an increasingly proactive stance against fraud stand to gain financially by decreasing financial losses due to fraud, and reputationally, by helping to reduce potentially embarrassing incidents of fraud that could negatively impact the perception of the bank in the eyes of their customers. 

Rapidly Increasing Risk from Fraudster Scams and Money Mules

Fraudster scams are on the rise. Almost everyone has read about scams, some know people who’ve fallen victim and many have received a suspicious email, text or call that was wisely deleted or ignored. Scams typically target individuals, though the method of the fraud scam varies. In 2022, 2.4 million fraud reports were filed with the Federal Trade Commission (FTC). The top five scam types for 2022 are:

  1. Imposter Scams
  2. Online Shopping Scams
  3. Prizes, Sweepstakes and Lotteries Scams
  4. Investment Scams
  5. Business and Job Opportunities Scams 

https://www.ftc.gov/business-guidance/blog/2023/02/ftc-crunches-2022-numbers-see-where-scammers-continue-crunch-consumers 

The total losses from reported fraud scams in 2022 was $8.8 billion, per the FTC. In 2021, the reported fraud scam losses were $6.1 billion, reflecting a greater than 40 percent increase in fraud scam losses from 2021 to 2022. Consider for a moment that scam losses in 2020 were $3.3 billion. 

This means fraud scam losses increased more than 160 percent in two years. Fraud scams are, unfortunately, a rapidly increasing risk. 

Investment scams, while ranking fourth on the list of most frequent types of scams reported, rank first in terms of scam losses, accounting for $3.8 billion (over 40%) of the $8.8 billion in scam losses reported to the FTC in 2022. The most common fraud scam, for the past two years, has been imposter scams. 

Recent developments in the advancement of generative artificial intelligence (AI) create the potential for fraudsters to have increasingly sophisticated ways of committing an imposter scam. Generative AI makes it possible for fraudsters to duplicate a person’s voice and video screen image. Historically, scam fraudsters have hidden behind their keyboards without a face or a voice. Now, using generative AI, it is possible for those same scam fraudsters to provide a face on the screen and a voice on a call that looks and sounds like the actual person. Given the potential for these new technologies to be used in imposter scams, it seems likely that imposter scams will continue to top the list of scams in the future. It makes me wonder what the scam fraud losses will be in 2023 and 2024 as scam fraudsters will likely look to exploit these newly available tools for their illicit purposes. 

It is clear to see the losses from fraud scams are increasing, but it’s also important to consider one of the most common methods used by fraudsters to launder the money they have scammed. Money mules are commonly used by scam fraudsters. The money mules will receive the proceeds of the fraud and then forward those proceeds to the fraud perpetrators, often to overseas accounts. 

The problems with money mules are pervasive enough that the Department of Justice, the Federal Bureau of Investigation (FBI), United States Postal Inspection Service and five other federal law enforcement agencies have a Money Mule Initiative to help identify the networks through which fraudsters obtain the proceeds of their fraud schemes. 

From the perspective of the money laundering process the money mules play a critically important role. Money laundering consists of three stages: 1) Placement, 2) Layering and 3) Integration. The role served by money mules, from a money laundering perspective, is both placement and layering. Placement is the introduction of illicit funds into the financial system. The initial deposit or receipt of illicit funds into a bank account is a good example of placement. Layering is the movement of illicit funds with the intent of obscuring the origins of the funds. 

The money mule is involved in placement because they receive the illicit proceeds into a bank account that they control. When the money mules move the proceeds from the bank account they control to a bank account controlled by the scam fraudster, they are involved in layering. The transfer by the money mule to the scam fraudster is the first step in obscuring the origins of the illicit funds, so after subsequent transfers those funds can appear to be legitimate and ready to be integrated back into the economy by the scam fraudster. 

As losses due to fraud scams seem likely to continue to grow rapidly in the near future, it will be an increasingly important risk for banks and financial institutions to address and seek solutions to help mitigate exposure to losses. The risk exposure to fraud scam losses is based on the transactional nature of the fraud. The fraud begins with a transfer of funds from the victim to the money mule, so there will be a focus on solutions that can help identify potential scam transactions in real-time, so as to prevent the victim, a bank client, from being scammed and save the bank from any negative financial or reputational impact. 

To effectively combat fraud risks, banks must implement comprehensive fraud controls covering the full spectrum of financial activities. This includes implementing fraud controls from customer onboarding to continuous authentication, mule monitoring, account takeover detection, and transaction monitoring. By implementing layered controls, financial institutions can leverage multiple points in the fraud lifecycle to identify and prevent fraud before any losses occur. The implementation of fraud controls at each stage of the process ensures a holistic approach to fraud prevention, safeguarding the financial institution and its customers from potential financial losses. 

NICE Actimize has a history of working to help banks identify and prevent fraud. Due to this experience developing and enhancing solutions in fraud transaction monitoring and customer screening, they are in a strong position to help banks both identify potentially suspicious transactions involving scams and weed out money mules prior to account opening at the bank. Banks taking an increasingly proactive stance against fraud scams and money mules stand to gain financially, by decreasing monetary losses due to scams, and reputationally, by helping to eliminate suspicious fraud-related transactions by money mules seeking to use their institution to transfer illicit funds.   

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