Introduction

ACH which stands for Automated Clearing House Network is a common money transfer technique that most financial institutions (FIs) use to manage checks, cash transfers, direct deposits, and bill payments between individuals and businesses. Until recently, ACH was not thought of as a high-risk payment method. This is primarily because frauds have historically been focused on wire transfers and checks. However, recent data suggest that ACH fraud is increasing. Payments fraud was slowing down in 2021 according to the 2022 AFP Payments Fraud and Control Survey. However, the percentage of respondents reporting payments fraud through ACH debits has been increasing.

Unfortunately, it is very simple to execute an ACH fraud. All one needs is an account number and a bank routing number. Once culprits have this data, they can utilize it  initiate payments to make purchases and also pay off debts.

What is ACH Fraud, and When Does it Occur?

ACH fraud occurs when money is sent through the ACH network from one bank account to another where the transaction is illegitimate. Generally, this occurs when the sender does not intend to send the money. The money transfer occurs, because of some form of manipulation or hacking of an account to perform an illegitimate transaction. Such frauds can also occur when the sender himself opens an illegitimate account and transfer money from one illegitimate account to another in their control.

How AI/ML Can Help

ACH fraud is continuing to evolve and grow. Depending on traditional and inefficient processes leads to ineffective fraud programs. Fraud detection and prevention are mired in the restrictions of data from one financial institution. Without early prevention from rising fraud threats or the data essential for effective machine learning — customers face a greater risk of fraud loss. Financial institutions that adopt innovative approaches can bypass such restrictions eventually preventing losses, and establishing their overall fraud program.

One of the best advantages of AI/ML for financial institutions is the usage of these technologies for identifying and preventing fraud. Of course, this benefits customers too, and not directly the banks themselves. A more sensible approach would be to invest in AI/ML technologies to address the growing fraud problem. Cybercriminals are applying the latest techniques to make attacks. Fortunately, many tech organizations are rising to the challenge.

Impacts of ACH Fraud on Organizations

Various negative consequences affect financial organizations that fall victim to ACH fraud. The first relates to liability, and the second relates to reputation.

ACH Fraud Liability

One of the key differences between other payment methods and ACH is that ACH is one of the few types where the receiving financial institution is financially liable when they receive a return. When an institution is the receiving party of an ACH, you may face financial liability if a customer uses the funds before clearance.

Reputational Risk

Besides the risk of being liable in case of a return, FIs that face ACH fraud also have to deal with the risk of a bad reputation. For example, if a neobank is a victim of a large-scale ACH fraud attack, then the organization will be at a loss of reputation,

Conclusion

While ACH fraud is on the rise, it is preventable with appropriate controls and measures. Having the right AI/ML tools to help your organization fight against fraud is crucial. This demands that the efficacy level of the AI/ML tools is high as well as cost-effective. These two demands have only recently been attainable with the growing AI/ML technologies, along with the people who can create the solutions.