Financial Crime and Regulation; Where does Artificial Intelligence Fit In?

There is no doubt that Artificial Intelligence (AI) and machine learning are going to be a game-changer in the financial world. One of the purposes of this article is to discuss where AI fits into financial regulation and financial crime. I want you to understand how AI can be used to prevent financial crime, deter the perpetrator and make sure that they don't get away with their actions. In addition, I'll share how AI could help in fighting fraud, money laundering, terrorism financing and cybercrimes related to these affairs.

Artificial intelligence has been a topic of discussion in the financial industry for years. In fact, it was the main topic at The Financial Times' annual digital banking conference in 2018 where executives from banks, technology firms and consultancies gathered to discuss how artificial intelligence could help prevent financial crime.

The fight against financial crime is a complex issue that can’t be solved with just one method. It requires the cooperation of many different parties, including law enforcement, banks, regulators and tech start-ups.

What is financial crime?

Financial crime is any crime which is primarily motivated by the need to obtain or use money, financial assets, or other forms of financial property. Examples include fraud, computer crime, money laundering, extortion, bribery, and theft. It is a very broad concept and can include many kinds of misconduct. Financial crimes are often interconnected and may employ a variety of methods to be committed. For example, fraud may be used to obtain money or assets from a victim, which may subsequently be laundered as part of a larger criminal enterprise. Accordingly, financial crime is often a high priority for law enforcement. There are many types of financial fraud and crime. One of the most common is phishing, which is when fraudsters try to trick people out of their money by sending them emails that appear to be from trustworthy sources. Scams such as pyramid schemes and Ponzi schemes are also very common.

AI and big data for detecting financial crimes

Artificial intelligence has been applied in financial institutions as one of the sophisticated tools to prevent financial crimes. The major applications of AI in financial crimes are fraud detection and money laundering detection. Most financial crimes are committed over the internet or through financial transactions in banks and financial institutions. To prevent financial crimes, financial institutions need to detect suspicious transactions. To do so, they can use artificial intelligence and big data to detect anomalies in transactions and flag them for further investigation. Artificial intelligence can analyse millions of transactions in real time, including the amount of money involved, the individuals involved, and the companies involved in the transaction. By analysing the information associated with these transactions, the computer can detect anomalies in the data. These anomalies may indicate that a transaction is suspicious and should be investigated.

AI and big data for tracing financial crimes

Financial crimes can also be traced using artificial intelligence and big data. Financial crimes usually take place across different countries, and the perpetrators try to hide their activities so they can’t be traced. Artificial intelligence and big data can be used to trace financial crimes by analyzing different financial transactions across the globe. By analyzing trillions of financial transactions, financial institutions can identify suspicious patterns in the data that might indicate fraudulent activities. They can then trace the source of these transactions to detect where the money is coming from and where it is being sent to. Financial institutions can also analyze communications among individuals to identify patterns that may indicate fraudulent activities. For example, if two individuals are communicating with one another and this communication is consistent, it may indicate that they are trying to hide their activities from law enforcement.

Limitations of AI for Financial Crimes

Financial institutions use artificial intelligence and big data to detect anomalies in financial transactions and flag them for further investigation. However, there are limitations in using AI for financial crimes. Most financial institutions have designed a model for fraud detection and a model for money laundering detection. However, there is no universal model for machine learning and security risk models which means it’s less robust and may not detect all kinds of criminal activity.

Conclusion

Financial crimes pose a significant risk to businesses and individuals. However, financial institutions are increasingly using artificial intelligence and big data to detect anomalies in financial transactions and flag them for investigation. Financial crimes can be traced across the globe and across different countries, enabling law enforcement to catch criminals and protect people from harm. For all its benefits, though, AI alone is not enough to detect financial crimes. Instead, it must be used in conjunction with machine learning, big data analytics, and other data science techniques.