For financial services firms, speeding up effective product delivery and customer service means deploying process automation strategies.
Customer delight levels the playing field between financial institutions (FIs) and financial technology (fintech) companies. Customers increasingly expect near-instant, convenient, and personalized service in banking as in all things, and their demands are driving financial enterprises of all sizes to re-think paradigms that inspire customer loyalty.
Half of the 749 business managers surveyed by Harvard Business Review Analytic Services noted that their overly complex processes were harming their ability to deliver customer satisfaction, stay strong against the competition, and innovate their business in the digital age.
Fintechs constantly optimize the way they deliver to the customer as a central tenant of their eco-structure. To stay competitive, FIs must capture the customer request journey constantly—this means that processes have to be examined end-to-end, bottlenecks have to be identified and resolved, and tangible surges in productivity and service must be delivered.
Looking past RPA
When many corporations think about process streamlining, Robotic Process Automation (RPA) automatically comes to mind. For their part, FIs have made tangible inroads into digital banking by RPA to save costs of up to 40 percent. As per Gartner, by FY19, 50 percent of FIs will adopt RPA to focus on labor cost reduction.
RPA, along with artificial intelligence and machine learning, has proven effective in automating certain well-defined tasks, completing them faster than traditional methods involving human interaction. A business case cited in a McKinsey article noted that one insurance organization was able to automate several tedious steps in processing premium advice notes, bringing the turnaround time of processing 500 notes down to 30 minutes from two days.
While RPA can be valuable as a cost-cutting measure, it is only one of the tech interventions for streamlining the way institutions can optimize their services to customers. In many cases, it may offer a reasonable amount of cost savings, but it has its limitations, particularly in its impact on customers.
For instance, the application processing and disclosure generation of a complete mortgage process takes about two hours to complete. Though RPA can potentially cut this time in half, it only brings down the total time of processing a mortgage application from 45 days to 44.6. To the customer, that still means 45 days.
Rather than automating just because that is the lowest hanging fruit or the most visible action, FIs must make decisions based on data about what will help them achieve their strategic objectives. And if the objective is to provide the quickest and best service to customers—which it should be—FIs have to closely examine their own systems and processes to find what is holding them back.
Taking a hard look
If a patient came to the hospital with a broken leg, a doctor wouldn’t just slap a cast on him and send him on his way. The doctor would first X-ray the leg to confirm that there was indeed a break, find where it was broken, and decide on the best way to heal it and treat the patient’s pain.
Process mining is like an X-ray into your organization’s IT system. It allows discovery to identify “pain” points that increase operating costs and prevent the kind of service that delights customers.
To improve customer experience, the process must be evaluated to determine whether it is relevant, efficient and effective from a customer perspective and if it meets the business objective.
You examine the process “as-is,” to find the activities that are slowing you down from delivering to the customer. If they are too complex, you simplify them: sometimes this means automating with RPA; sometimes this means a simple Six Sigma solution; or other times it means a different intervention completely, such as machine learning solution or an application modernization.
There are as many solutions as there are problems, but FIs will never know which one will work for them until they examine their processes thoroughly and exactingly. If your strategy is to give the fastest turnaround time, you have to know what’s slowing you down.
Institutions have classically delved into their processes through manual interviews and workshops. This time-intensive approach suffers from too much human subjectivity and a potential for incomplete process flow capture.
In the world of here and now, process mining lead transformation can bypass the human interview process and use event logs and transactions stored within IT systems, to provide a view of the “as-is” in minutes. System logs can capture when and how long steps, like document analysis, take. Then institutions can ruthlessly question status quo to identify areas with maximum impact on the customer and form a transformation strategy based on data.
Case in point — most people seeking a loan would consider shorter throughput time on processing loans. Since customers prefer shorter throughput time, this enhances their user experience. Quicken Loans, the high-profile FinTech, has risen by completing loans with a lightning-fast turnaround. For FIs trying to stay ahead of their competitors, eliminating a few hours in the RPA process would be of moot value to the end user. However, reducing the loan processing time from 45 days to 35 days would be of much higher value to the customer.
Examining the mortgage processing steps would show that less than 10 to 15 percent of the 45 days it takes to pull through a mortgage application is actually spent processing work items. Banks spend 85 percent of the time waiting on customers or third-parties to send title, appraisal, insurance and relevant documents. Analyzing the collection flow to understand the delay in receiving documents is imperative to speeding up the process.
There could be many reasons for those delays, including customers sending a wrong or stale document. However, because multiple teams have passed the documents around for validation and analysis, it can take three to six days for customers to find out that they are invalid.
Process mining can reveal such bottlenecks. If your strategy is to give the fastest turnaround time, you have to examine every step to know what’s slowing you down. You can’t just say you want to change the process from 45 days to 35; you have to measure it, and then you can fix it.
Finding the “why”
Once you have established what already exists, you must ruthlessly question the status quo and shift focus to understanding the “why” behind the activities within the process.
Finding the “why” is done through asking a set of questions: What is the process objective? What is the purpose of each activity in the process, and are they still relevant? Where is the maximum amount of time spent within the process, and is there potential to improve that through automation?
The answers should give you a view of bottlenecks within a current process and propel you through the “what ifs” that reveal the areas where optimization can help achieve your strategy objectives, allow workers the freedom to innovate in other areas, and awe customers with smoothly efficient service.
The dire consequences
Once FIs have drilled down to the deepest pain points in their processes and know what needs to be optimized, they can keep moving toward their digital transformation. But to fully compete against the agility of FinTech’s who are making optimization a core part of their operation, FIs must make sure every step is made with customer delight in mind. FIs should make strategic, data-based decisions to know which interventions—whether RPA, machine learning, or a simple business shift—will keep customers coming back.
Cutting costs and increasing efficiency is a necessary aim, but even if it makes life easier for you and your workforce, your goal is not accomplished until it makes life easier for your customer.