Banks and other financial institutions collect a significant amount of data about their customers. Often, a customer will have checking and savings accounts with the same bank, as well as debit and credit cards and perhaps even a mortgage or a car loan. The customer may also use the bank’s website and mobile app. With each of these, the customer likely has numerous interactions with the bank every month. Each interaction produces data the bank can collect about that customer’s preferences, financial status and interests.
This data can be used to help financial organizations improve their services, communications and marketing efforts with customers. However, many banks struggle to make effective use of this information. Artificial intelligence solutions can help. By sifting through the mountains of structured and unstructured data that live on organizations’ various systems, AI tools are helping savvy financial institutions to increase sales and improve customer service.
1. Driving Cross-Selling and Upselling
Tools such as IBM Watson Customer Insight for Banking can help institutions integrate real-time data from all customer channels, including online banking, mobile apps, customer engagement centers and branches. When customer service and marketing teams have access to this aggregated information, they can better target individuals with relevant offers.
For example, a customer who pays his mortgage early every month, never carries a balance on his credit card and is conservative with his money may be more interested in an interest-bearing checking account than a large loan to take a lavish vacation. A bank using sophisticated AI tools could see that opportunity and take advantage of it, promoting products and services more likely to interest the customer without inundating him with offers that are of no interest.
2. Detecting Bank Fraud
By analyzing customer behavior, AI systems can detect suspicious activity based on patterns, rather than rules. This not only has the potential to improve fraud detection, but also can help prevent “false positives” that lock customers out of their accounts for engaging in legitimate behavior.
The more data that banks can process, the more accurately they can guess whether or not a transaction is fraudulent. For example, an attempted ATM withdrawal in China might look suspicious on its own, but is more likely to be legitimate if the customer recently logged in to her banking mobile app from a location in Beijing.
3. Enabling All-Hours Customer Service
Retail customers can buy toothpaste at 10 p.m., or pick up office supplies before the sun rises. But banking services have historically been limited to traditional working hours. Now, AI-powered conversational assistants (or chatbots) are helping banks to engage customers around the clock.
These solutions can field customer inquiries and even make customers aware of additional services and offerings. However, the tools are still emerging, and it’s important that banks roll them out in a way that doesn’t frustrate customers.
4. Improving Customer Retention
Frequently, financial institutions are caught off guard when customers decide to leave. And by the time a customer shows up at a branch to close an account, there may be little a bank can do to keep him or her. AI tools can enable early detection of customers who are likely to leave and help optimize incentives to get them to stay. According to IBM, one financial institution used Watson to cut churn by 66 percent.
This blog post brought to you by: