This bank set out to strengthen customer loyalty by delivering more personalized service. To gain a deeper understanding of individuals’ needs and desires, it had to analyze masses of customer data.
Using IBM Watson Customer Insight for Banking, the bank can gain a real-time, 360-degree view of each customer across all channels, helping to understand spending habits, customer sentiment and more.
Drivessuperior service, as customers enjoy highly relevant advice and recommendations
Triplesrevenues from cross- and up-selling as offers target customers’ needs and desires
66% cutin churn by enabling early detection of people who are likely to switch
Business Challenge Story
Going for gold
As competition in the industry heats up, global banks need to work harder than ever to defend market share. Looking to sharpen its competitive edge, one major player planned to strengthen customer loyalty by delivering superior, highly personalized service. A spokesperson for the bank begins: “Consumers expect their banks to truly understand their needs and desires. If we want to boost share-of-wallet, we cannot simply send all promotions to all of our customers, because people understandably get frustrated if they are bombarded with offers that are irrelevant to them. “Our vision was clear: if we could gain a complete view of each customer across all channels, we would be able to more accurately determine which financial products might interest them. So if, for example, we were launching a new savings account, we could make sure that we send incentives to only those people likely to be interested.” To tailor its marketing campaigns and product recommendations effectively, the bank required deeper insight into customers’ needs and desires. “In the past, customer data was spread across the disparate systems we use to manage our various channels,” continues the spokesperson. “On top of that, more and more of our data is unstructured, such as whether a customer clicks on an advertisement in an email, which transactions are performed using mobile banking, and how customers use online banking. All of that made it very difficult for us to get a clear, joined-up view of each individual. We set out to find a solution that could combine all of that data and paint an accurate picture of each customer.”
Finding the key to success
To take its analytics capabilities to the next level, the bank deployed IBM Watson Customer Insight for Banking—a powerful predictive analytics solution designed to help banks extract deeper customer insight from their existing data. The solution augments the bank’s existing business intelligence environment, which featured IBM SPSS® Modeler and IBM SPSS Statistics. “We selected IBM over other vendors because we felt that the solution offered the best time-to-value,” recalls the spokesperson. “If we had purchased an all-purpose analytics solution, we would have had to customize it to suit our business. IBM Watson Customer Insight for Banking comes with pre-built statistical models examining precisely the areas that banks are interested in, so it offers faster deployment and time-to-insight. “In addition, the IBM solution is very easy to use, and offers more sophisticated analysis than many competing solutions.” The bank is using IBM Watson Customer Insight for Banking to integrate real-time data from all channels through which it interacts with customers—including e-banking, mobile, call centers and in branches. In doing so, the bank builds up a clearer picture of each customer across all channels—including their spending behavior, which topics interest them and how they feel about the bank.
Unlocking valuable insights
With deeper insights into customers’ needs and desires, the bank can deliver highly personalized service. “If a customer contacts one of our call centers, the agent answering the phone can see which of our financial products the customer has already purchased, and which offers are likely to tempt them,” explains the spokesperson. “As a result, agents can provide more useful advice to customers, take advantage of opportunities for cross- and upselling, and help boost share-of-wallet. “What’s more, we are tailoring our marketing campaigns to include product recommendations that are relevant to each customer, helping them better manage their finances. As a result, we have boosted campaign response rates and tripled revenues from cross- and upselling. “IBM Watson Customer Insight for Banking observes how each customer reacts to each campaign, and uses machine learning to refine its algorithms. We have identified approximately CHF 2.5 billion [USD 2.56 billion] of untapped sales potential—for example, customers who currently do not hold a credit card with us, but would benefit from doing so. So, if we can convey these messages to customers at the right time and in the right way, the potential for revenue growth is huge. “At the moment, we perform our analysis in IBM Watson Customer Insight for Banking, then manually trigger campaigns in IBM Interact, which sends rule-based customer communications. We plan to integrate IBM Watson Customer Insight for Banking with IBM Interact so that we can automatically send highly personalized messages to customers. Customers will gain useful advice and recommendations, while we stand to grow sales and cut marketing costs.” The IBM solution also helps the bank spot ways to adjust its offering to boost customer satisfaction. “IBM Watson Customer Insight for Banking helps us extract insight from all touchpoints,” remarks the spokesperson. “For example, we use the solution’s text mining and sentiment analysis to gain insight into customers’ conversations with call-center staff, looking at which products are mentioned most often, and whether each product is mentioned in a positive or negative context. If we see that customers are dissatisfied with a certain product, we can improve our offering to better address their needs. “Additionally, we use IBM Analytics to analyze different products and areas of our business, looking at profitability and identifying areas for improvement. If we see that any individual products or services are making a loss, we can shelve them.” The solution also enables the bank to study and understand customer behavior in real time. The spokesperson adds: “By examining spending habits, we can accurately predict when and where each customer will next make a transaction, what that transaction will be, and how they will complete it. Using this information, we create dynamic customer segments based on real-time behavior. Many customers move between segments each day, reflecting how their spending patterns change throughout each week and month. “If a customer unexpectedly moves to a different segment—for example, by making an uncharacteristically large cash withdrawal—the IBM solution gives us a notification, so that we can investigate what happened. “We analyze the profiles and behavior of customers who recently switched to another bank to work out who is leaving, when they switch, what motivates their decision and how much it costs us. With that insight, we can pinpoint which customers are at a risk of churning in the near future and take action to prevent it—for example, by offering them a new credit card with an attractive rate. We can even optimize which incentives we offer to each customer depending on their individual tastes, maximizing the chance of them accepting the deal and staying with us. In a pilot, use of targeted incentives enabled us to cut churn by 66 percent—an outstanding result.” The spokesperson concludes: “IBM helps us provide smarter, more responsive service, fostering greater loyalty among our customers and driving greater share-of-wallet. We have only just scratched the surface of what the solution can offer, and we have already achieved remarkable success. We look forward to seeing what the future holds.”
About Large global bank
This major bank provides financial services in over 50 countries.
- Customer Insight for Banking
- FSS: Banking - Front Office - Multi-Channel Transformation
- FSS: Banking - Front Office Optimization - Customer Insight
- FSS: FM - Front Office
- SPSS Modeler
- SPSS Modeler
- SPSS Statistics
- SPSS Statistics
Take the Next Step
IBM is working with organizations across the financial services industry to use IBM Cloud, cognitive, big data, RegTech and blockchain technology to address their business challenges. Watson Financial Services merges the cognitive capabilities of Watson and the expertise of Promontory Financial Group to help risk and compliance professionals make better informed decisions to manage risk and compliance processes. These processes range from regulatory change management to specific compliance processes, such as anti-money laundering, know your customer, conduct surveillance and stress testing.