Banks are, to no one’s surprise, one of the most common targets for criminals. Of course, this poses an existential challenge for the banking sector, especially given all the technology that we have.
Banking fraud detection refers to a set of techniques and processes that are designed to reduce risk. Ironically, financial institutions are some of the most targeted companies by fraudsters. And, due to their immediate access to funds and their ability to transfer them. Also, as such, banks & fintech institutions usually invest in robust fraud detection & prevention solutions to protect their assets, systems and customers.
So, as cybersecurity and advanced technologies become more prevalent, here is a look at some of the most common types of bank fraud and how to prevent them:
1. Credentials theft: It is no secret that pretending to be someone is not a complicated task to accomplish in this day and age. This is why fraudsters acquire sensitive personal information to steal money, etc. While robust passwords are, of course, crucial to preventing the theft of credentials, banks can also offer additional means, including multiple-factor authentication, to prevent such fraud. Additionally, users’ biometric data can also be integrated into the authentication process to ensure only the true user can access their accounts and other banking information.
2. Wire fraud: The act of convincing banks that the source of particularly large sums of money is legal or legitimate is the essence of wire fraud. Given the abundance of new-age electronic and digital tools available, fraudsters can use a variety of tactics to pull off wire fraud. Despite the challenging nature of this fraud, banks can still prevent wire fraud — by letting artificial intelligence do this job for them. Artificial intelligence-driven automated systems can be leveraged to flag risky behaviors as they scan data passing through the system.
3. Money laundering: Any money acquired through illegal means, be it through theft or as proceeds of crime, typically drives the need to clean up the money, i.e. money laundering, bypassing said money through lawful channels. Preventing money laundering or even detecting can be quite a challenging undertaking but that is not to say that there is no way to prevent it. Banks and financial companies can prevent this crime by updating their legacy IT infrastructure with modern systems. More importantly, companies must also ensure that all their systems tie into one unified solution to effectively stop money laundering in its tracks.
4. Accounting fraud: Accounting fraud occurs in the context of business lending, i.e. when companies forge or develop counterfeit data about their businesses to put on the appearance of a better performance than what is true. Machine learning can prove to be quite handy when dealing with this particular type of fraud. This is because this technology can help companies identify any deviations in data as well as leverage data about login location, behavioral analysis, and deep learning models to pinpoint fraudulent or even risky behavior. Put this together with entity analysis and companies can immediately thwart any attempts to collude with fraudsters.
It is clear as day see that fraud in the banking and finance sector has not only become more prevalent but it has also become substantially more sophisticated owing to the easy availability of new technologies and tools. However, as the above discussion demonstrates the world also has ample technologies to offer to help companies operating in the banking and financial sector to capably deal with and prevent such fraud.
Thanks to technologies such as artificial intelligence, data analytics, machine learning, etc., banks can be well-equipped to contend with fraudulent activities in their operations. If you too are looking to integrate such capabilities into your operations, may we recommend that you start looking for a reliable bank fraud detection software development company to help you build the solution that can fulfill your business’s unique needs?