The Role of AI in Combating Financial Fraud

AI may be the key to counteracting financial fraud as hackers and scammers develop increasingly advanced tactics. Financial fraud has become a more significant risk over the past several years, largely due to the rapid rise of online shopping. Hackers and scammers are taking advantage of vulnerabilities in digital financial services to steal customers’ data. How can AI help prevent fraud and protect consumers, banks and credit card companies?

Automated Fraud Monitoring

One of the biggest risks in any fraud situation is timing. The attacker usually tries to use stolen bank or credit card information as quickly as possible before the cardholder can detect unauthorized transactions. In that initial window, a fraud victim can potentially lose thousands of dollars.

AI can prevent this type of situation. Banks and credit card companies can use it to monitor every customer’s account activity autonomously around the clock. By analyzing a few key pieces of information, AI can detect potentially fraudulent transactions.

For example, most fraudsters today use their stolen account information for online purchases. AI can spot unauthorized activity by comparing the transaction’s IP address with the customer’s verified location. If they don’t match, the software can automatically block the transaction and send a verification request to the account owner.

This is especially helpful when customers are at a heightened risk of fraud due to high account traffic, such as during the holiday season. Studies show scams are more common during holiday shopping, when customers are making more purchases. There are more transactions on their accounts already, and customers are likely in a hurry or under stress, meaning they’re less likely to notice unusual purchases.

Fraudsters often take advantage of this period of vulnerability to sneak unauthorized transactions onto victims’ accounts. AI has the intelligence and rapid analysis capabilities to differentiate these transactions from legitimate account activity and block them.

Phishing Detection

Phishing is one of the most common ways fraudsters currently steal financial information. Using social engineering tactics and malicious links, they trick victims into giving away their bank and credit card account data, often without even realizing it. AI can help people identify and block phishing messages and malicious websites.

Over the past few years, phishing has rapidly increased in volume and quality. Harmful emails are getting harder to recognize as hackers and scammers improve their social engineering techniques. However, there are still subtle patterns and red flags AI is capable of spotting in malicious messages.

Customers and financial institutions alike can use AI-powered email filters to catch more phishing emails. The technology can identify traits a human might miss at first glance, such as a subtly misspelled email address or odd wording. By rapidly analyzing incoming emails for suspicious traits, the AI can block increasingly advanced phishing messages before a user ever sees them.

Preventing Zero-Day Attacks

Zero-day attacks are among the most pressing cybersecurity risks on the rise. These involve exploiting vulnerabilities as soon as an update, app or service launches — by the time the developer notices the problem, it’s too late. AI can prevent zero-day attacks using automated monitoring, vulnerability detection and automated security updates.

Timely updates and data backups are crucial for patching vulnerabilities before they can put customers at risk. However, the rapid pace of today’s threat landscape makes it difficult for financial institutions to keep up. AI can help fill the gaps by autonomously completing security updates, backing up data and running security scans.

This is most helpful for financial institutions with apps and online services for their customers. However, it can be beneficial for individual users, as well. For instance, some consumer cybersecurity and identity protection services are beginning to utilize automated monitoring tools. Customers can take advantage of these features to update their security software automatically and back up their data periodically.

Cyber Forensics and Data Analysis

Cyber forensics is effectively crime scene investigation for hacking, data breaches and digital fraud incidents. AI can be extremely helpful in the investigation process, particularly when analyzing data from before and during the incident. After all, one of its most effective use cases is data analytics.

Applying AI in financial cyber forensics is particularly helpful today since the cybersecurity industry is facing a growing skills deficit. There’s a shortage of cybersecurity professionals across the board, but especially those with advanced, niche skills. As a result, many teams are struggling to keep up with the ever-increasing complexity of cyber attacks.

AI can help fill the gaps by automating smaller tasks, and helping security teams analyze their data and systems. For instance, it could rapidly analyze someone’s financial and account activity data after a fraud incident to identify valuable information about the fraudster. Data like IP addresses, purchase types and timing can also be vital for recovery after a fraud incident.

Financial institutions can have the software analyze large, company-wide datasets for vital insights and patterns. This information is often useful in security reviews where bank or credit card companies can use it to plan future cybersecurity strategies. Additionally, they can use AI to analyze the quality of existing security protocols and highlight vulnerabilities that might otherwise have gone unnoticed.

Leveraging AI for Next-Gen Financial Security

Financial fraud is on the rise, but AI can help. Banks, credit card companies and individuals can all utilize automation to safeguard their financial data, monitor account activity and prevent unauthorized transactions. AI is also helping financial institutions stay ahead of emerging threats and better use their security data.

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