Between the host of regulations introduced in the wake of the 2009 subprime mortgage crisis, the emergence of thousands of fintech startups, and shifting consumer preferences for digital payments banking, financial services companies have had plenty of change to contend with over the past decade.
Transitioning to automated, data-driven processes is the best way for these companies to not only cope with change but also take advantage of it.
Take the institution of the bank branch, a staple of consumer banking for more than 100 years. As customers have increasingly gone online, the number of physical branches has decreased by more than 900 per year1 for the past decade. If the trend continues, some experts believe branches could be all but gone by 2034.
But there’s an opportunity in this shift. Consumer banks can use digital interactions to gather more customer data and apply real-time analytics to expand services and speed up processes. Open banking, a concept that has taken off rapidly overseas, enables financial institutions to expose data selectively to other institutions via APIs to enhance customer experience.
“If you go to a store in Brazil or India your bank can offer discounts and coupons or extend credit because they’ve opened up communication to an ecosystem,” says Cindy Maike, Vice President of Business and Product Solutions at Cloudera. That enhances the value banks can provide customers and positions them to better extend services such as micro-loans to new customers.
Automation can take time and cost out of expensive and slow-moving processes like mortgage lending. The average mortgage requires 280 pages2 of documents to be prepared, verified, and checked, contributing to an average cost of more than $11,000 in production expenses3 per loan in the third quarter of 2022. Maike also states “we’re seeing a trend of ‘bring the branch to digital and digital to the branch.”
The top two causes4 of loan quality processing defects are missing documentation and errors caused by missing documents, problems that can be addressed by moving to fully digital processes. Nearly half of title and settlement companies now offer digital closings5, more than triple the number just four years ago. Adopting “e-closing” technology not only reduces errors and lost documents but can dramatically shorten the time to close a mortgage, giving adoptees a competitive edge.
Risk management is a top-of-mind issue for all financial services firms. Analytics powered by machine learning (ML) lets business leaders assess risk according to a wide variety of variables, many of which are not intuitively obvious.
For example, climate change will have far-reaching effects on the viability of construction projects in many regions as well as the ability of borrowers to repay loans. Banks and mortgage companies will increasingly need to factor these complex forces into their lending decisions. In insurance, the ability of underwriters to forecast the impact of climate change could become a make-or-break issue.
Security and regulatory concerns are also paramount to financial services firms. Streaming data analysis powered by ML can enhance fraud detection at the point of sale as well as enable instant adjustment of credit terms to improve customer satisfaction. A unified data platform also provides a single view of all customer data for privacy protection, regulatory reporting, and adherence to information retention schedules.
Real-time analysis of network traffic coupled with historical data can spot anomalies that indicate that a data breach has occurred. “Data and analytics are critical not only for digital security but also for physical security,” Maike says.
Deloitte has estimated that retail banks can reduce processing expenses by as much as 25% and cut records management costs by up to 70% by eliminating paper. There is still plenty of room for digital innovation in financial services.
Visit Cloudera to learn more about digital innovation.
Business Intelligence, Data Management