How Can You Use the Benefits of AI in Fighting Financial Crimes?

Here’s what the real issue is when it comes to financial crimes built on technology: the goalposts are always moving. The moment some new solution develops, cybercriminals determine novel ways of stealing the information or resources they want. Compounding this issue is the success of “black hat” cybercrime.

It turns out that cybercrime is about as economically impactful as “white hat” technology every year. In the link, it’s pointed out that by 2025, cybercrime will have a $10.5 trillion impact annually. Today, the global value of the tech industry is half that. So every breakthrough at the “mainstream” level is reciprocated in the digital “underworld”. There are entire corporations built on hacking.

Just as you might find an entire floor of an office building dedicated to some corporation, cybercriminal exploits will have similar space rentals. In Mumbai, Shanghai, St. Petersburg, Orlando, Chicago, New York City, and Los Angeles, you’ll find such offices. Sometimes such undertakings are compartmentalized so only managerial personnel understand the fraud.

The only way you’re going to be able to protect your business is to find ways of using technology that anticipate future issues. Artificial Intelligence and Machine Learning, AI and ML, are key to preventing financial fraud and ultimately safeguarding your business. We’ll explore a few ways AI and ML make such security more tangible here.

1. AI and ML Automate Anomaly Detection and Response
   
   For financial systems, it’s very important to stop any sort of hacking either through social engineering or digitally engineered attempts. Often, hackers hide their identity, but they can’t hide their activity. Unless someone knows the ins and outs of your financial facility’s daily operations, they’re going to do things that don’t fit the general “pattern” of daily digital activity.

Basically, AI can identify when anomalous behavior indicates a given user might not be who they represent themselves to be. Suspected hackers can then be notified with verification materials, or they can be digitally quarantined from network access if they’re unable to prove their legitimacy.

AI and ML can automatically launch such protections, and develop progressively as more data helps inform their activity.

2. Pattern Identification Helps Anticipate Tech Vulnerabilities
   
   AI and ML can recognize patterns in addition to anomalies. They can see where user patterns may result in vulnerabilities cybercriminals can exploit. Accordingly, AI and ML can notify relevant managerial personnel to effect changes or reinforce existing security. 
3. Conversational AI Helps Verify Transaction Legitimacy
   
   A new aspect of AI and ML security involves conversational potential. You’ve likely encountered AI posing as “humans” before. Basically, you go to a website, and while you’re browsing, an Instant Messaging (IM) chat window pops up asking if you need any help. This is a “chat bot”. Essentially, it filters your information to reduce “static” in terms of customer service.

The chat bot can determine if site visitors match certain characteristics which may recommend they get help from one department or another. Similarly, conversational AI can be used to verify whether someone requesting financial information or sensitive data is who they represent themselves to be.

AI and ML can continuously hone such conversational programming to the point where, one, users can’t tell the difference between the digital conversationalist and real people, and two, fewer site visitors “fall through the cracks”. AI and ML do make mistakes, sometimes legitimate individuals are restricted from access. As AI and ML learn, this happens less.

Keeping Your Business as Secure as Possible

Conversational AI can help keep bad actors from fraudulently accessing financial data. Pattern identification anticipates tech vulnerabilities and helps patch them. AI and ML utilize anomaly detection software to help keep cybercriminals from accomplishing their illegal goals. Altogether, utilizing AI and ML for financial security makes lots of sense. It’s worth exploring.