Written by: Deeba Kamran
Deeba Kamran is a tech reviewer and writer obsessed with finding the best tools for the modern world. From hardware to SaaS, she delivers clear, actionable insights into the products and services shaping our digital future.
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This Article is a part of
AI Applications & Use Cases Guide

Artificial Intelligence

Your customers trust you to keep their financial information safe and secure when they do business with you online. Imagine going to the grocery store and watching the cashier read your credit card number out loud over the intercom. Of course, no company intends to give away their customers’ most valuable information in that fashion. However, failing to be prepared for the many ways cybercriminals can steal it can have exactly the same effect.

Financial institutions increasingly rely on machine learning technologies to improve fraud detection, automate risk analysis, and deliver personalized banking experiences for customers.

This Article is a part of
Machine Learning Resource Center

Understanding the Threats

Just as a simple padlock is not enough to keep a determined and experienced thief out of a building, many companies don’t have strong enough protection when processing their customers’ financial data. Today’s criminals have a number of sophisticated and not-so-sophisticated tools they can use. For example, knowledgeable hackers know where to find and how to exploit weak spots in misconfigured systems. Although yours may appear to be locked down, finding a way into one of these gaps can be easier than you suspect.

Even a well-configured system still can fall victim to user error. One of the most frequent examples of this is employees using weak passwords. Using “12345” or “password” may save a worker a few moments when logging in each morning, but it exposes the employer to a world of risk. Another example of how unwitting users can open the door to crime is through phishing schemes that utilize false emails and website portals to trick someone into giving away their credentials without knowing what they’re doing.

The rise of AI-driven trading systems powered by machine learning has transformed financial markets by enabling predictive analytics, automated trading strategies, and real-time investment decisions.

How Artificial Intelligence Can Help

Hacking is a 24/7/365 threat, one that sounds almost impossible to manage. Fortunately, however, security that includes artificial intelligence (AI) is always watching for and prepared to deal with these dangers. With a robust solution that incorporates this technology, you can rest easier knowing that the sensitive information your customers give you will always be in good hands.

Artificial intelligence is being adopted across nearly every major industry, from healthcare and retail to finance and cybersecurity. Our broader AI applications and use cases guide provides a wider look at how organizations are using AI to solve practical business problems.

For instance, AI can identify and react to potential phishing emails. Utilizing algorithms to spot anything that looks suspicious, it can flag them and remove them from your server before they ever make it to an employee’s inbox. This kind of software also has the ability to spot anyone attempting to access your systems without proper authorization. In doing so, it can shut that user out from the specific area or content until it can be determined whether or not the request was legitimate. Another area of concern that AI can deal with is keeping data encrypted even while it’s being analyzed. This limits exposure and prevents any unauthorized personnel from sneaking a peek during analysis.

Security is another major concern for financial organizations because banks and financial platforms process highly sensitive information and large volumes of transactions. Technologies covered in our guide to AI in cybersecurity can help organizations detect suspicious behavior, identify anomalies, and respond to emerging digital threats.

Today’s ecommerce landscape means there’s always a chance that someone will try to take advantage of you. Having a security solution that’s working around the clock to protect the information your customers entrust you with is crucial. Artificial intelligence works tirelessly to ensure that there’s always a watchful eye looking out for you and the people you serve. For more details about the threats you may face and how AI can mitigate them successfully, take a look at the accompanying resource.

Infographic created by Donnelley Financial Solutions, a financial consolidation software provider

Financial institutions also rely heavily on customer data and personalized interactions. Technologies used in AI in CRM, including customer segmentation, predictive analytics, personalization, and automated support, can be applied to improve how banks and financial companies understand and serve their customers.

Related Posts:

  • Modern banks and fintech companies are implementing AI and machine learning in banking software to improve operational efficiency, strengthen security, and enhance customer engagement.
  • Many organizations in the finance sector now understand why financial services companies need machine learning to stay competitive, reduce manual processes, and support intelligent financial decision-making.
  • The financial sector isn’t the only industry where AI is transforming data-intensive operations. In healthcare, artificial intelligence is being used for medical imaging, diagnostics, patient monitoring, drug discovery, and clinical decision support. Explore our dedicated guide to AI in healthcare to see how these applications are changing modern healthcare.