To Maintain Consumers’ Trust, Banks Must Improve Decisioning

According to TowerGroup, consumers are less than satisfied with the ways banks make decisions on how to service them. Moving to more customer-focused, enterprisewide decisioning could be the answer to maintaining their trust and staving off turnover.

Kathleen Khirallah lead analyst, consumer banking, with the Needham, Mass.-based firm, presented her findings on the matter at the annual TowerGroup Financial Services Business & Technology Conference and Exhibition in Orlando last week. Khirallah explained how banks must reexamine their decision-making capabilities and leverage integrated processes that yield relevant customer data to help them make smarter, more informed and disciplined decisions.

"When banks are profitable, making a bad decision here or there can usually be covered up with positive cash flow," she told BS&T. "Now we're at a time when customers are distrustful of banks and there's concern over the quality of the decisions banks are making. Everything is under the microscope now."

Khirallah says she covered decisioning in the areas of lending, deposits and customer service during her talk. Processes such as the ability to look at transactions as they occur and deciding to waive a fee, or being in the midst of a workflow and determining whether something should be routed for manual review are examples of what Khirallah discussed. "Some of these are frequent, low-dollar decisions, such as waiving a fee, and some are more infrequent, high-dollar decisions, like deciding whether to extend a line of credit," she comments.

How well a bank engages in this process is determined by the degree to which its operations are integrated. In many cases, the manner in which different business units make decisions is inconsistent. The tools they use may also be different, Khirallah says. Banks cannot afford to continue operating like this and must adopt a more holistic view of their customers. "Banks have to move from the idea that each decision is made within a line of business and to an enterprisewide view of decisions—not just mechanically, but from an impact perspective as well," she explains.

Banks will often define a customer once within a business unit and may not incorporate as much relevant data about the relationship as they should, Khirallah says. "The data needs to be reviewed periodically and from a more holistic perspective. Customers see an institution, not lines of business," she states.

The technology designed to help banks make good customer decisions has definitely improved, according to Khirallah. "The technology has matured," she comments. "The only excuse today is that someone may not have the wherewithal to do the integration and share the information appropriately. They may be stuck with their existing technology and may not have the IT budgets to replace it."

Yet it's really not a question of technology when it comes to decisioning as it is the actual data and the ability to share that data, she explains. "It's not so much a technology approach as it is a mindset that looks at shared services. Some capabilities are enterprise and some are line of business. It's a technology management issue," she relates.

The first thing banks must do is to create a comprehensive framework to give it visibility into the kinds of decisions it makes. "It's a mapping of capabilities," Khirallah notes. "From there, you take a look and see how you can optimize and leverage what you've got and improve internal processes where needed."

According to Khirallah, there are five goals banks should keep in mind on their journey to effective and efficient customer decisioning:

• Create a decision management infrastructure that is flexible and can change with minimal IT support, especially during economic turbulence that causes changes in consumers' behavior.
• Migrate toward business ownership of strategies, policies, and business rules that support decision making.
• Improve accuracy of decisions, but match the value of the decision with the right data, timing, process, analytics, governance, and infrastructure.
• Embrace a layered approach to customer data management, leveraging data that is maintained at the enterprise level, with specific data that resides in the line of business.
• Provide customer-facing personnel with the necessary data to make appropriate decisions.