Artificial intelligence has changed how we live. It permeates our everyday lives in countless different ways. AI dictates the playlists on our music apps, the posts in our social media feeds, and the results of our web searches. But it also plays a significant role in bank fraud detection and prevention. If your financial institution is not using fraud detection and prevention methods that use AI, you are putting yourself at unnecessary risk.
AI isn’t just for big banks. It’s for credit unions, community banks, and financial institutions of all sizes. In this post, we take a look at how AI improves banks’ ability to deal with fraud, and then, we look at how AI helps detect specific types of bank fraud.
Benefits of Using AI to Deal With Fraud
AI helps banks deal with fraud in many different ways. In particular, it can improve their ability to detect fraud in real time, and it can reduce false positives which boosts accuracy and safeguards the customer experience. Beyond that, AI can help banks stay compliant with data governance regulations. Take a look at the role it plays:
Real-time detection — AI can decipher vast amounts of data extremely quickly. It can also compare the data to datasets about a user’s normal behavioral patterns. Then, it can quickly detect anomalies in bank app usage, payments, and other transactions. This all happens quickly in real-time, which speeds up fraud detection. This allows you to prevent rather than detect fraud, and it also reduces the risk of ongoing schemes.
Accuracy — Because AI is more efficient than manual fraud detection or rule-based anti-fraud software, it reduces the risk of false positives. This means that it’s less likely than a conventional tool to flag a legitimate transaction as a fraudulent transaction. This improves your fraud detection processes, but it also improves the banking experience for your customers.
Customers don’t want to be the victims of fraud. But they also don’t want to deal with account shutdowns or denied transactions because subpar software has flagged a legitimate transaction as fraudulent.
Machine learning — One of the central advantages of AI is that it’s insatiably curious. AI never stops learning, and machine learning improves your approach to fraud detectioon over time. When the system is wrong, it learns from its mistakes, and it improves its accuracy the next time around.
Regulatory compliance — Around the world, banks incurred over $5 billion in regulatory fines related to data breaches in 2021. Although this was half the amount of the previous year, less than a quarter of the number of fines were levied. This means that, on average, financial institutions incur higher fines now than they did a year ago for lack of compliance in relation to fraud reduction activities.
Most banks have internal compliance teams to help them deal with the maze of compliance requirements. AI cannot replace these teams, but it can help to speed up the process by leveraging deep learning and natural language processing (NLP) to review compliance requirements and improve decision-making.
AI can also support the people in your fraud department. It can flag potentially fraudulent transactions more accurately than humans, and then, request your team to verify if certain transactions are fraudulent or not. It also generates actionable insights which can help strengthen your fraud detection efforts.
How AI Fights Popular Types of Bank Fraud
AI can help improve fraud detection across all of your transactions and banking channels. But its exact approach varies based on the issue a hand. Take a look at how it addresses the following types of fraud:
Identity theft — AI-based anti-fraud tools don’t just focus on fraud at the point of payment. They can also look for signs of identity theft such as a user changing their password and then changing their contact details. This is a common pattern in account takeover. The AI gets to know fraudulent patterns, and it also gets to know the customer’s usual patterns. Then, it crunches all of this data to look for actions that signify identity theft.
Credit card theft — Again, when looking for this type of fraud, the AI relies on patterns. It knows the customer’s spending patterns, and when it sees abberrations, it flags the transation for potential fraud. Many theives are aware of this and to avoid detection, they often stick to the customer’s usual spending patterns. For instance, they may order from the same websites or make purchases in similar dollar amounts as the victim. However, even when the micicry of buyer behavior is well execusted, AI can look for minute variations to spot issues.
Forged documents — Fake IDs and forged signatures are staples of check fraud, but AI can also help here. It gets to know the patterns of a signature and an ID, and it can spot minute issues that are inviibsle to the human eye on its own. Whether you’re dealing with checks in the ATM or the teller line, AI can help you authenticate signatures and spot forgeries. It can also decrease the risk of someone cashing a check with a fake ID.
At SQN Banking Systems, we are committed to helping financial institutions reduce their risk of fraud. We leverage AI in our tools, and our solutions use behavioral analytics and machine learning to protect our clients and reduce their exposure to fraud. To learn more about the role of AI in fraud detection, contact us today. We’d love to talk with you about how our tools can help your bank fight fraud, improve the customer experience, and protect your reputation.