Digitizing credit risk trims costs and delights customers

To stand out amid fierce competition from digital entrants and peers, a European bank wanted to offer simple, convenient, and easy-to-use financial solutions for all of its customers, whether they favored mobile, online, or branch channels. The bank also sought to reduce its costs—already among the lowest in the industry—and to simplify and streamline its commercial-lending processes, from risk underwriting and collateral acceptance to compliance. Having exhausted traditional cost-saving levers in previous efforts, it decided to digitize its loans business but keep its large legacy IT infrastructure intact.

The client already operated as a digital bank in some parts of the business. It had lending processes that met market standards with loan approvals for small-and-medium-size-enterprise clients within 24 to 48 hours. Even so, preparing a credit application required a relationship manager to toil through as many as 50 screens, some asking for data that had already been provided. Customers and employees alike were frustrated. Relationship managers and credit officers spent much of their time on routine tasks that squandered their expertise and judgment, ran up high costs for the bank, and left them little time to spend on activities that created more value.

Our team began by helping the client to rethink its lending process from scratch. A digital interface that delivered instant credit decisions to customers would need to be underpinned by completely new underwriting criteria and risk processes.

At the core of the new model was an automated analytics engine that drew on hundreds of data points about customers—from external as well as internal sources—to inform loan-approval decisions. The other key elements of the model were a zero-based redesign of processes and a smart digital work flow, connecting the elements needed for convenient customer journeys and credit decision-making. To provide instant technology delivery without disrupting the bank’s core IT processes, the team adopted a two-speed IT approach, building a layer of new functionality on top of the untouched legacy infrastructure and making maximum use of existing assets.

Initially, the analytics engine and digital work flow handled all credit applications and processed about 40 percent of them automatically from beginning to end, with 70 percent as the eventual goal. For these fully automated applications, “time to yes” was reduced from a window of 24 to 48 hours to just four minutes. If the analytics engine was unable to approve an application, it did not reject it outright. Instead, it referred it to credit officers, providing detailed analysis that helped them make a better-informed decision more quickly than before.

By using the engine to both approve and support credit decisions, the bank could manage much higher application volumes. The more cases the engine handled, the more robust its decisions became.

With much of their routine work automated, relationship managers and credit officers found they were handling more challenging cases. They were also equipped with better tools and data to help create richer and deeper relationships with their customers as they took on more of an advisory role.

Digitization and automation have created a host of benefits for the bank and its customers. The cost per origination has fallen by 30 to 40 percent, with substantial savings across the board in front-office, sanctioning, and back-office processes. Touch time has been minimized, releasing extra time for relationship managers to spend on sales, and average process times from application to sanction in principle have shrunk from days to minutes.

The intuitive new interface for loan applications requires minimal information, with just five screens for data entry and customer advice instead of 50. It also provides new insights for customers through additional analyses, such as assessments of personal risk drivers and peer benchmarking. Overall, the state-of-the-art customer experience has reduced leakage during credit applications, improved customer satisfaction, and boosted revenues.

Moreover, the ease of use and customer convenience has been achieved not at the expense of risk controls but alongside enhancements to them. The bank is able to address credit risk at a portfolio level and not just case by case. Credit-risk managers have access to more data that they can use for additional risk analysis. In the longer term, better decision models will cut default rates and losses and better risk management will reduce the reserves that the bank has to set aside against liabilities.