Data Action Layer July 22, 2021
With data volumes multiplying, new regulations being imposed, and competition getting fiercer, financial services firms are under extreme pressure to re-envision their business processes through digital transformation. Moreover, the pandemic also contributed to the current urgency by disrupting operations and magnifying uncertainty for the financial sector around the globe.
While leveraging technology to increase agility and resilience is now top of mind at financial institutions, many firms lag in the execution. For example, 97% of financial institutions report having a digital strategy in place, but only 30% are currently implementing it. However, 77% of firms plan to expand their investments in digital technologies over the next year, so look for a surge of transformations to happen soon.
Of all the emerging technologies that can help, workflow automation allows financial institutions to boost efficiency, reduce costs, and increase productivity—all while helping them meet compliance mandates. Because of this, the workflow automation market will see a 5.8% compound annual growth rate (CAGR) over the next five years.
Here are several trends in workflow automation that financial companies, in particular, should be aware of.
With AI-related technologies playing a more prominent role in workflow automation, we see a surge in computer vision, cognitive automation, natural language processing, and other innovations being applied to workflows to boost efficiency. According to a study by Salesforce, 78% of companies either currently use or plan to use AI in their workflow automation initiatives. The biggest obstacles? Lack of trained talent and competing priorities. But if financial institutions can surmount these obstacles, they’ll be able to dramatically increase value for customers.
Combining workflow automation with AI means that the software can be programmed to perform manual tasks and go beyond rule-based tasks to account for some of the non-standardized steps that previously required human intelligence. Pairing computer vision with machine learning technology to isolate meaningful information in unstructured data formats—such as images or email bodies—is just one way how AI is positively impacting the workflow automation experience. The end goal of smart workflow automation is to streamline the flow of data by eliminating repetitive, error-prone manual tasks and refocusing their employees on strategic, analytical, and value-added work.
Among the doom and gloom of the pandemic, there was some good news. In 2020, financial services firms’ client onboarding processes accelerated to an average of just five days, down from seven days in the previous year. This was largely due to more firms going digital. Only 25% of companies said they still performed onboarding “in-person.” Almost two in 10 (19%) have achieved a fully digital onboarding process, and half of them expect to transform to that status in 2021.
As all financial services firms know, the onboarding process is an intricate collaborative effort between multiple departments, including credit, operations, compliance and legal, front office, risk, and tax. It’s an arduous process to coordinate manually. Also, regulations can change on a monthly or even weekly basis, making it challenging for financial institutions to keep up with compliance. Workflow automation—especially when coupled with AI (see #1)—can use machine learning to process documents much faster, routing them to the proper departments and people and checking to make sure they comply with the latest regulations.
Particularly demanding is meeting the increasingly stringent requirements related to anti-money laundering (AML) and know-your-customer (KYC) regulations. Banks must complete extensive checks before they agree to handle a customer’s money—otherwise, stiff penalties could be imposed. As a result, customer identity authentication, due diligence, and other onboarding tasks must be accomplished with speed and accuracy. This means AI-based workflow automation.
Financial services firms handle all sorts of data from various sources, not just the structured data that fits neatly into databases with established schema, but the unstructured data stuck in emails, documents, audio files, or other text documents or rich media. And rather than utilizing highly-compensated—and difficult to retain—data scientists or other technologists for search/copy/paste extraction tasks, financial institutions need their business users to be able to extract and analyze that data. Previously, workflow automation solutions lacked the ability to deal with unstructured data. Today, leading platforms liberate the data to power business workflows with clean, actionable information that shortens time-to-insight and adds a competitive advantage for the financial institution.
Financial institutions today must think of two constituencies when considering a workflow automation solution. First—of course—is the customer and the impact of workflow automation on their experience. But running a close second are employees. Workflow automation gives them relief from escalating workloads, eliminating stressful—and unrewarding—repetitive rote tasks that can lead to dissatisfaction and employee churn.
Of course, you want to keep customers satisfied, but why work hard to keep employees happy? Because surveys show that executives who put employee experience as a Top 5 objective achieved a minimum of 10% revenue growth over those who didn’t. What’s more, 70% of them agreed that improvements in employee experience also result in better customer experiences. And 69%—that’s about seven out of 10 executives—say that a better customer experience drives more revenue.
Workflow automation can drive this important value chain forward—if you pick the right solution.
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