What Is Bank Fraud, and How Can Financial Institutions Deal with It?

Nowadays, the long-term stability of companies offering private financial services or those that integrate direct banking-like features into their internal platforms is influenced by the complexity of the security measures taken to prevent banking fraud. Are you the manager of a private institution that offers banking services to private clients? Are you a FinTech, and does your activity take place in the United States or the EU? In such a scenario, according to the active legislation for firms in your field of activity, you will need to implement comprehensive anti-fraud measures and report suspicious transactions to the national authorities.

What is bank fraud? In a nutshell, it is the total amount of processes implemented by external bad actors to illegally obtain financial assets either from private clients or national financial institutions. Bank fraud has many forms and can be perpetrated through social engineering as well as through complex credit card or wire fraud. Therefore, in recent years, and with the AI revolution, the use of anti-fraud applications that leverage machine learning algorithms has become common practice, at least with firms conducting their financial activities at a national level.

What Techniques Are Used by International Fraudsters?

Bank fraud comes in many forms and can affect both financial institutions with impressive turnover and private companies that are just starting their professional activity and do not yet have the budget necessary for implementing complex anti-fraud systems. What are the most common types of bank fraud used internationally? For starters, one should mention identity theft. With the help of social engineering, fraudsters can steal the personal security information of already registered clients and perform transactions, such as financial withdrawals, directly from online financial platforms.

Account takeover attempts are difficult to stop because, in 99% of cases, the actions through which fraudsters gain access to user accounts are unrelated to the financial platforms they use. However, there are measures through which private financial institutions can mitigate the impact of identity theft and account takeover. By leveraging AI algorithms, anti-fraud systems can identify suspicious transactions before they are approved and look for patterns in the analyzed transaction data that may not have been visible in manual checks.

On top of identity theft, fraudsters can cause significant financial losses to private financial institutions through check fraud, phishing, or wire transfer fraud. The last scheme is of particular importance, as wire transfer fraud is usually utilized in money laundering operations, and not stopping them could put your institution in breach of AML and KYC regulations, such as those laid out in the BSA Act. Financial institutions that do not comply with these measures and fail to protect their user’s data can come under the scrutiny of FinCEN and be fined with amounts comparable to their turnover. Such penalties can and do happen frequently. For example, Capital One was fined no less than $80 million in 2020 for a data breach that leaked the personal addresses of 100 million US citizens.

“What Is Bank Fraud?” A Better Question Is, “What Are the Risks?”

In the US, failure to implement appropriate anti-fraud measures can have both legal and financial repercussions. Are you an institution active in the economic sector, and are you conducting your operations both internationally and domestically? Then, you must comply with the provisions of the BSA Act, follow the guidelines laid out by the OCC, and respect the GLBA. Have you failed to secure your client’s financial data, and have you been hit by a cyber-attack that caused significant economic damage? Then, you could come under the scrutiny of FinCEN, FTC, or even the Federal Reserve.

Is your activity taking place in Europe? In such a scenario, you will need to comply with the provisions of the General Data Protection Regulations and report any breach of your internal systems within a maximum of 72 hours. Moreover, you will have to keep in compliance with AMLD 4, 5, and 6, respect the provisions of the PSD2 directive, and be aware of the requirements of national regulators. For the most part, the agency that checks the utilization of anti-fraud applications for institutions active in the EU market is the EBA. However, in Europe, companies that fail to implement AML, KYC, and anti-fraud measures are often fined by national regulators.

Deutsche Bank was, for example, fined €13.5 million in 2020 by the German Federal Financial Supervisory Authority for failing to adhere to strict anti-fraud measures and report fraudulent activities. In the EU, the enforcement of anti-fraud, AML/KYC measures is usually carried out by national regulators such as the FCA or AMF. However, most financial investigations are initiated by the EBA, which can offer recommendations regarding the economic sanctions applicable to private institutions that violate international financial regulatory practices.

How Can AI-Based Anti-Bank Fraud Applications Help?

What is bank fraud is a question on the lips of an increasing number of people, as its effects have become increasingly visible in the last five years. Advances in the field of artificial intelligence represent a double-edged sword for financial institutions active in international markets. On the one hand, bad actors now have more complex measures available for fraud attempts. On the other hand, by leveraging machine learning and NLP models, AI-based anti-fraud applications are now more accurate than ever and can detect any type of bank fraud attempt before damage to a client’s data is done. How do these applications work?

For starters, the machine learning algorithms of AI-based anti-banking fraud programs analyze multiple internal and external data streams simultaneously, looking for anomalies or patterns that can indicate a fraudulent financial transaction. By leveraging SVMs and autoencoders, AI-based programs can identify outliers in the analyzed data with significantly higher precision than conventional applications. Moreover, through NLPs, AI can look for suspicious phrases and protect financial institutions from phishing attempts. Not least, the program you choose will utilize GNNs to map interactions between analyzed accounts, RNNs for detecting patterns in sequential data, or predictive analysis techniques aided by the utilization of reinforcement learning.

A Reality of Modern Times

What is bank fraud? Ultimately, it can be a significant hurdle for firms active in the financial sector that want to expand their business to new levels of profitability. Financial institutions that do not implement comprehensive anti-fraud systems can come under the scrutiny of national or international regulatory bodies and get hit with significant fines, which in some cases can be synonymous with the end of professional activities. Moreover, a successful fraud attempt could destroy your company’s reputation, affect your sector’s growth, and make you liable for civil cases.

Bank fraud has many forms and can have a devastating effect on institutions active in the financial sector. However, the good news is that the measures implemented by fraudsters, regardless of their complexity, can be entirely mitigated with the help of comprehensive AI-based anti-financial fraud applications. Sure, no program, regardless of complexity, can be 100% accurate. However, with the help of federated learning and continuous feedback loops, AI applications are close to perfect, and their accuracy increases depending on the volume of data they access. What is bank fraud? A nagging phenomenon that represents a nightmare for both customers and private financial institutions. Nevertheless, with the right tools, it is also entirely preventable.