Improving Banking Customer Experience with Standardization and Robotic Process Automation

 How process standardization and banking robots accelerated commercial-lending operations, saving labor while enhancing customer experience—a case study

By William Heitman 

Banks of all stripes and sizes have long labored to optimize back-office operations. At the same time, they strive to improve customer experience. Nowhere do these two challenges overlap so strikingly and advantageously as when it comes to automating “the last mile” of banking operations via robotic process automation (RPA). 

In this article—comprised of a mashup of The Lab’s experience with different banks and credit unions—we address stumbling blocks which often cause these “two-bird” opportunities to go overlooked. Then we show how The Lab automated one—in less than six weeks!

End-to-end process analysis at the minute-level task detail 

The first step to standardizing and then automating banking operations—or any knowledge-work process—with RPA is a deep-dive process-mapping exercise whose scope spans the entire organization. At The Lab, we document the employees’ daily, minute-by-minute, and even keystroke-by-keystroke (if we have zeroed in on an RPA use-case) work activities for all end-to-end processes.

While this might sound like a year-long task, if performed over a series of one-hour “low-touch-time” increments with a cross-section of individual staff, the time commitment from the organization is actually minimal.

With this detailed view of the business complete, we then engage in a process we call a Map Fair. This is where the actual branch and back-office employees mark up, further contribute to, and comment on huge workflow printouts. 

Upon completion of the Map Fair, all standardization improvements (typically 200+), RPA use-case candidates (60+), and analytics dashboard candidates (40+) are summarized, databased, and meta-tagged by the business unit and process they nest under.

Prioritization: Drilling deep to find the most value for RPA

At this bank, The Lab then performed a quick, sift-and-sort of the top service tickets; this revealed a high number of short-term extensions for existing commercial lines of credit. A further, casual investigation indicated that these were stopgap documents issued to compensate for delays that resulted when account managers failed to notify their credit-line customers of pending renewal deadlines in a timely manner. That’s the insight that led to identification of the loan renewal-notification robot in this case study. 

Standardization + Automation (RPA): Developing RPA bots in six weeks

This story features a few principal players: In the “front office” there’s the loan officer, who is the person who originally sold the line of credit to the customer. The loan officer is supported by a loan assistant (“LA”) for help with administrative tasks related to the loan. In the “back office” are portfolio managers or PMs. 

Every month, the PM, as the manager of the book of in-force loans, would get an updated “Renewal Pipeline Report”—basically an Excel spreadsheet, which the PM would sort by expiration date, to see which lines of credit were coming due soonest. The loan officers and their assistants would see this report, too. 

For these humans, several mind-numbingly-repetitive (i.e., robot-friendly) work activities bogged down the process: For each contract in the report, the PM needed to manually look up what documentation was available, which items were current, and which would need updating, in order to review with the customer, agree and renew the line of credit. Next, the PM would alert the loan officer—with sufficient lead time for the loan officer to personally contact the borrower, advising them exactly what was needed, item-by-item. 

So far, we’ve just talked about what the PM does. All of that work then gets dumped on the loan officer—and much of that gets dumped, in turn, on the loan officer’s assistants or LAs (“Get me their tax returns from this year; I only have last year—and I need them yesterday!”). 

Standardizing the Process and Designing the Bot’s Tasks 

First, The Lab mapped and documented the bank’s existing end-to-end business processes and work activities, as described earlier. This took about seven weeks. 

Second, we simplified and standardized these processes. That’s because, despite RPA vendor claims, bots can’t be productive “straight out of the box.” The sub-process “RPA candidates” can’t be automated unless they’re first made “bot-friendly:” simple, standardized, and repeatable. So The Lab rationalized and standardized that reporting-process map into a single, best-practice version. This alone yielded a 20-percent savings—without any technology at all. 

Third, The Lab developed an inventory of the core IT systems and peripheral applications (spreadsheets, email, websites, etc.) that the bot would access—essential for information security, creating a development environment, and documenting the as-built bot. 

Developing the Bot

Finally, we were ready to develop the bot; imagine creating flowcharts of sub-activities (keystrokes and mouse clicks) with icons that execute various basic tasks: open, copy, drag, drop, send, and close. 

Now, the bot does part of what the PM used to do—only faster, without procrastinating, getting tired, taking breaks, or making mistakes: 

• It opens the Renewal Pipeline (RP) Report.

• For each loan, it captures the loan number. 

• It then goes to the relevant files in the imaging system and looks for what’s needed.

• It returns to the RP Report and populates the appropriate cells (“Annual Financial Statements,” “Interim Financial Statements,” etc.). 

• It calls out what’s missing/needed. 

• It updates the RP Report and saves it to a shared server. 

The next morning, the PM (and the loan officers, and even the LAs) can simply click the shared server to see the flawlessly-updated report. Simple as that. Then it’s just a matter of using it as a “to-do list” to preemptively contact the customer.

Customer-experience or “CX” Benefits: Better, Faster Renewals

After the Knowledge Work Standardization® (KWS) described above, it took The Lab just three weeks to design and build the renewal-notification bot. And the results seemed like a miracle to the bank, its employees, and its customers: 

• Fewer Extensions: While it’s hard to influence customers who, say, fail to submit paperwork when requested and thus create delays, you can reduce the percentage of renewal extensions which are effectively the bank’s fault. Prior to robots, The Lab’s client was at fault for issuing avoidable extensions for roughly 20 percent of its yearly renewals pipeline. With RPA, that number has dropped to the two-percent range—a reduction of 90 percent. 

• Lower Lapse Rate: Loan-renewal lapses for customers—due to the bank’s negligence—are similarly down. And loan officers hardly hear a word of righteous indignation from customers about these anymore.

• Shorter Cycle Time: Thanks to the increased speed and capacity, renewal cycle times were cut from 30 days to an industry-average of 14. Customer perception: “My bank got faster.” 

• Fewer Errors: More PMs and loan officers manage to review and submit completed renewal packages right the first time—three times more often than ever before. This means fewer callbacks to customers.

• Proactive Response: These critical reductions deliver a vast improvement in the customer’s “optics”: No longer must the loan officer humbly ask for documentation when it’s already too late. Now, the PMs and loan officers are preemptively responsive—helpful—to their customers.

• Customer Satisfaction Gains: Net Promoter Score (NPS) and Customer Satisfaction rates, routinely measured in the contact centers prior to the bots, have both increased measurably from this single improvement—more than 10 points each.

Operations Benefits: More Productivity, Higher Employee Morale

• “Freed Up” Capacity: The sheer number of hours saved is staggering: In the credit group, each PM was previously spending about 80 hours a month doing this work (i.e., the bot’s) manually. The resulting savings in employees’ hours alone has freed up capacity sufficient to absorb two years’ worth of targeted growth—without new hires.

• More Sales Uptime: Since there are fewer avoidable extensions, the loan officers spend less time working on them—and more time selling added business during renewals.

• Employee Satisfaction: The bots also delivered morale-boosting benefits at the employee level: Those PMs in particular are delighted to get that tedious work off their plates. Now they get to oversee sales and service performance, which is what they’d been hired to do in the first place. 

• Less Wrangling Time: Sure, there’s still wrangling required to coerce documentation from customers. But PMs and loan officers had been spending anywhere from 35 to 70 hours a month chasing customer documentation. That’s now slashed by two-thirds.

About the author 

William Heitman is the founder and managing director of The Lab Consulting. A renowned thought leader on non-technology improvement, Heitman is the author of The Knowledge Work Factory (McGraw-Hill).