Modern banks sit among the largest users and beneficiaries of artificial intelligence. Most have spent recent years developing powerful capabilities such as credit scoring systems, automated loans, and more. And they continue to invest heavily in data-driven AI-based solutions. Why the focus? Because banks appreciate that technology is the future of the sector.
In this article, we’ll present the three most important AI solutions every commercial bank needs to remain competitive and attractive.
“The aggregate potential cost savings for banks from AI applications is estimated at $447 billion by 2023.”
1. Make Accurate Product Recommendations
There’s no better indicator of a customer’s preferences than their past transactions. These insights allow banks to determine the customer’s needs and then decide which kind of product to offer them next.
But to enable personalization, bankers, customer service representatives, and tellers need machine learning-based solutions. They can then use these same applications to guide marketing strategy, interpreting customer data to target customers with select offers, and improving the effectiveness of campaigns.
Elsewhere, banks can use AI to operate more efficiently by adapting to changing preferences. What do we mean by this? Well, banks often struggle to satisfy every customer’s need because needs change over time. And banks have to adjust to keep creating relevant offers. Let’s clarify the point with an example.
Suppose you’re a single student who likes to travel. You’re probably not looking for a family home loan at this moment. But a student loan — or a foreign currency card with travel insurance — could be right up your street. When you start a family, your needs will change. And the bank will have to adapt its offer.
Thanks to machine learning, it’s easier than ever for banks to track where you’re at in life and tailor offers to your specific needs.
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2. Maximize Customer Satisfaction
Businesses know that keeping current customers happy is as important as attracting new ones. The question is: how can banks offer the best customer experience to existing customers? The answer? They can use AI-based solutions to identify dissatisfied customers and avoid them switching to a competitor.
Customers switch banks for several reasons. They may find a better interest rate. They may be upset with customer support. Whatever the reason, machine learning can help identify at-risk customers who may be looking elsewhere. Once identified, you can implement a plan to retain — or win back — flight risks.
Data is also crucial to ensuring maximum ongoing customer satisfaction. And banks have huge datasets, covering everything from actions on websites to conversations with support. If someone is struggling to log into their account, or if a user is having problems with an online transfer, machine learning can not only identify the issue quickly. It can solve it before the user gets overly frustrated.
See also: The value of good intent detection
3. Eliminate Fraud
Every bank has to contend with fraud. And it’s crucial to fight to eliminate it. AI sits at the forefront of this battle and can help banks take action while minimizing the impact on — or irritation of — honest customers.
Banks record a lot of important information. And this detail can become the cornerstone of anti-fraud models, using advanced AI-based tools to predict if a cheque is fake, a point-of-sale transaction is fraudulent, or a loan application is based on identity fraud, among countless other crimes.
In truth, AI-based solutions could save millions every day by preventing all kinds of fraud, even blocking events in real-time.
There’s plenty more that AI can do for the banking world. If you’re looking for ideas, schedule a 15-minute call to learn how AI could benefit your organization.
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