The application of artificial intelligence is to transform fraud identification in the banking and finance industries.
Banks and financial institutions are among the most targeted sectors as they incur billions of dollars yearly in identity theft, transaction fraud, credit card fraud, and money laundering. Banks and other related financial institutions face many difficulties in identifying and deterring fraud. However, with the help of modern developments in artificial intelligence (AI) and machine learning, the banking industry is now equipped with more effective tools to fight fraud.
The application of artificial intelligence in fraud detection involves using complex patterns to screen large volumes of customer information and detect fraud and other illegitimate activities in real-time. These AI systems can, therefore, apply the identified machine learning techniques to detect new fraud patterns and thus prevent fraud from happening. The AI models improve performance through experience as they learn how to process more data.
For example, the program may help identify a specific customer’s general tendencies, such as spending habits and places where he/she frequently uses a credit card. The bank will send it off for review if a purchase is considered a potential fraud because it is outside of usual behavior. Overall, the AI system ranks each transaction based on the fraud level, enabling the staff to work through the transactions that have high-risk ratings. This helps check fraud cases while preventing genuine customers from being inconvenienced
Furthermore, it can analyze networks of activity between groups of accounts to discover money laundering and invisible rings of fraud that a rule-based program cannot see due to its limited set of rules for what to look for. AI's learning capacity also enables it to update its analysis as newer fraud strategies appear.
The USA's JP Morgan Chase, UK's HSBC, and Citibank are among the largest global banks that have successfully implemented AI for fraud control. Initial implications are that these AI tools have helped banks increase fraud detection success rates by more than 30 percent. In the future, fraud detection will become even more complex with the help of AI. Banks are now considering other methods, such as computer vision and biometrics in AI, to combat all kinds of banking fraud. The introduction of new AI technologies in fraud prevention is on the rise because they are more accurate than older rule-based models. This is especially accurate when using AI in fraud prevention, which is proving to be very economical and protective of risks experienced by global financial institutions.
