How banks are using analytics to put customers centre stage
There's a lot of discussion about how retail banks need to become more customer-centric.
There’s a lot of discussion about how retail banks need to become more customer-centric. Nevertheless, many banks have yet to swing into action. I often hear executives and managers voice frustration at the lack of a navigable map between lofty industry goals and their own particular business situation.
We have just published a white paper on Customer Centricity: Four Bank Success Stories. Here are some of the stories that illustrate how banks are using innovative analytics to make customer centricity pay off.
Raise Customer Satisfaction by Improving Communications
Customer centricity is not about becoming so focused on engaging customers that we overwhelm them with attention. Rather, it’s about making very careful decisions—whether for marketing, collections or fraud management—about why, when and how to make contact. Analytics and intelligent automated communications are the keys to making these individualised decisions efficiently and consistently across a large customer base.
When customers are contacted with relevant information through the right channel at the right time, most welcome the interaction. Such contact may also increase customers’ perceptions of value and influence their behaviour in ways that drive revenue and profit.
One of our customers, a global leader in credit cards, found this when it wanted to demonstrate its commitment to protecting customer information and assets from fraud. By adding intelligent communications management to analytics-driven fraud detection, it improved the customer experience while also dramatically improving fraud detection performance.
The new automated process, which generates batches of alerts every 15 minutes, replaced a slow, totally manual and very costly outbound dialling process. The system has reduced declines by 32% and point-of-sale referrals by 80%, while resolving 250% more fraud cases — all with zero staff increase.
The bank ran a customer survey following this, and the results were fantastic. Not only were 76% of respondents highly satisfied with auto-resolution fraud checks, but 89% said they had increased confidence in using their cards again. Such strong feedback from customers means it is quite likely that many of these more confident customers will increase utilisation, thus positively impacting profit.
Increase Profit by Managing the Complexity of Customer-Level Decisioning
Making customer-level decisions makes strong business sense, but is enormously complex. However, such complex decisions will become routine for many banks as customer-centric operations become the industry norm. Mathematical optimisation is the key to getting a handle on this intricacy and making customer-level decisioning widely practical. It’s an ideal approach for finding the best balance between different, often conflicting profit drivers.
One regional division of a global banking group we’ve worked with is a leader within its markets for net income, profitability, efficiency and fees-to-expenses ratio, and some of this success comes from making customer-level decisions, including setting global credit limits. To make even more profitable decisions, the bank needed a comprehensive, scientific way of balancing risk with potential reward in four packages of its retail credit products.
With decision strategy optimisation, the organisation set optimal product limits which encouraged improved spend, balance and payment activity. Thanks to decision strategy optimisation and modelling, it reached all of its portfolio objectives while increasing overall profit. Results were so strong, in fact, that the bank was able to achieve project payback in six months and a one-year return on investment of six to one.
Boost Market Share by Stepping Back to Put the Basics in Place
When considering the way towards greater customer centricity, it’s important to acknowledge that every bank has taken a different path to arrive at where it stands today. Some banks have developed in markets that have grown like wildfire, consuming all of their resources just to keep up with demand and win market share. In these cases, banks often reach a point where they can no longer move forward without taking a few steps back to make sure they have a strong foundation in place for further growth.
One example in our new white paper involves a bank that had attained the second largest market share in a maturing growth market only to slide to fourth as economic conditions began to deteriorate and increasing competition made it more difficult to book new accounts and keep good customers. Its executives knew they had to make better decisions to drive profitable growth. Seeing the profit gains achieved by other banks using decision strategy optimisation, they made changes to make the most of the analytics-driven decision applications already invested in for originations, customer management and collections.
Since the bank wasn’t following basic best practices for segmenting account populations and testing targeted treatments on segments, it wasn’t getting full value from its data-driven applications. Another problem, common in growth markets, was that the abundance of new customers enabled the bank to succeed without having to take any real notice of the differences between them. More often than not, all accounts were treated the same, causing underperformance across the customer lifecycle, high acquisition costs and attrition rates for new accounts. In originations, it resulted in incorrect product line assignments and credit line decisions that drove revenues down and losses up. In collections, it resulted in wasted resources, high costs and lack-lustre results.
FICO helped the bank to improve segmentation of account populations at originations, then carry it across decision areas. As a result of these changes alone, it has been able to grow profitably, regaining its position in market share. In addition, the bank now has the operational fundamentals in place to begin using optimisation at the account level, so can expect to achieve additional performance lifts in the range of 10 to 30%.
Customer centricity is a marathon, not a sprint. The most successful banks will be those that are smart about which steps to take next and good at learning as they go, while using analytics to improve customer satisfaction, loyalty and profitability.