How AI Is Preventing Data Breaches In 3 Major Industries

July 6, 2020 - 7 minutes read

Artificial intelligence (AI) and machine learning are allowing both businesses and consumers to boost their cybersecurity to unprecedented levels. In a recent post, we examined six ways that AI is leading the way towards rock-solid information security. In case you missed it, read it here.

For this article, we’ll take a closer look at how AI and machine learning are letting three major industries safeguard their data better. In each of these sectors, websites not only contain a wealth of sensitive information but also have a high volume of visitors every day. Let’s explore how AI helps to counter any threats that come their way.

1. Finding Fraud and Anomalies in Finance

As its name implies, anomaly detection is a technique that leverages AI development to identify any unusual activity. A prime example of this would be if a bank customer unexpectedly withdraws an enormous amount of money from his or her account. Because this goes beyond the customer’s usual behaviors, AI would flag this action and alert both the bank and account owner.

Credit card fraud happens to be one of the biggest problems for financial institutions. To minimize these threats, AI utilizes a misuse identification technique. In much the same way as our previous example, potential fraud is identified when transactions fall outside the boundaries of previously established customer behavior. For instance, if you live in New York City and your credit card was used to purchase something expensive in Beijing, then this would raise some alerts.

Loan application fraud is another substantial issue in the banking sector. To keep the loan application process efficient, convenient, and secure, banks employ AI to rapidly analyze an applicant’s information, identify any anomalies, and verify authenticity. The smart technology plays an integral role in eradicating fraudulent applications early in the process so that more resources can be dedicated to legitimate customers.

2. Ensuring Accuracy in Insurance

With the immense amount of information that insurers collect about individuals and organizations, it’s no wonder that they’ve become an incredibly valuable target for hackers. To remain competitive in today’s fast-paced world, many insurance firms have digitized their products and pivoted to online platforms. Unfortunately, this shift has sparked the possibility for new security threats.

As in banking, fraud is common in insurance. A noticeable portion of prospective policyholders fabricate information in order to manipulate the rates they’ll receive from insurance firms. Similar to finance, AI plays a vital part in inspecting and validating the data submitted by customers.

AI and machine learning applications are constantly updated to be familiarized with upcoming fraud trends. They’re also optimized for honest customers, too. Besides flagging potentially false claims for further investigation, AI also automatically detects and validates legitimate claims. In turn, this streamlines the processes of approval and payment. As a result, insurance companies can lower their costs, and customers receive reduced prices.

3. Keeping Personal Information Private in Healthcare

Since thousands of employees can now digitally access patient information, privacy and data protection in healthcare has become quite complex. Obviously, manual evaluation of patient data interactions is infeasible; it would take far too much time and energy. Luckily, AI is here to help.

AI-powered medical applications can meticulously scan all patient data transactions and assess the various factors related to each interaction in just a few seconds. This takes into account the area of access, number of times accessed, and the length of time each login remained active. So if a staff member’s account suspiciously accessed thousands of patient files within a minute, AI would definitely pick up on this unusual behavior.

Beyond electronic medical records, AI is also helping to make healthcare devices safer. An array of gadgets like insulin pumps and pacemakers are susceptible to cyber-attacks. But these are used by many people around the world. In a worst-case scenario, a pacemaker could even be directed to shock the patient.

Like in banking and insurance, AI’s anomaly detection prowess comes into play here. The technology can track all activity and identify any abnormal instructions being sent to the pacemaker system. In this case, AI literally makes the difference between life and death.

AI Is Opening up a New Era for Cybersecurity

Believe it or not, this is just the beginning of AI’s use in cybersecurity. Companies in different industries are the world are just starting to understand the benefits of incorporating this technology in their fold. Even tech titans like Google, Amazon, and Microsoft are still in the midst of shifting away from rule-based protocols to machine learning algorithm deployments that can analyze vast quantities of information.

With that said, hackers are incredibly resilient; there’s no doubt that some are already leveraging the capabilities of AI and machine learning for their nefarious acts. It’s imperative to remember that cybersecurity isn’t a result — it’s a process. Adopting new paradigms, updating old protocols, and staying abreast of developments is key to properly protecting your information.

How do you ensure your cybersecurity is rock-solid? Are you utilizing AI in these endeavors? If so, how? Do you think that AI will ultimately be good or bad for cybersecurity? As always, please let us know your thoughts in the comments below!

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