Data Action Layer December 26, 2020
Runners of all levels will tell you the first mile is the most difficult. As you go from a body at rest to one in motion, the demands on your system are increasing dramatically. Muscles are straining to warm up, and you find your body desperately gulping for oxygen.
There's no magical way around it other than gritting your teeth and slogging through that first 5280 feet. Like running, robotic process automation (RPA) can also suffer from a first-mile struggle. Most RPA platforms are slowed to a crawl as they turn unstructured data into something that can power automation workflows.
But unlike the runner’s first mile, there is a solution to help overcome that tedious opening grind.
RPA offers a way to perform routine business processes using robots to mimic what humans can do and follow simple, repeatable rules to complete tasks. Internal audit (IA) departments, for example, use RPA for low-value, mandatory audit testing. Banks use RPA to track and flag fraudulent transactions on customer accounts, move customer data from one system to another, and automate simple credit analysis.
These RPA-enabled processes themselves are often straightforward, routine, and repetitive. Data is anything but. RPA can use structured data from spreadsheets and forms, but it runs into problems with unstructured data such as emails (with or without attachments) or documents that contain challenging formats like tables or charts.
RPA simply lacks the flexibility and intelligence to parse complicated and interrelated text and information. And “good enough” data extraction just to enable RPA processes is highly problematic for financial institutions where data accuracy is not optional. The alternative is a glaringly inefficient manual extraction process, where employees spend most of their day reviewing data and less time using it.
For financial institutions, whose business users routinely use email to pass along company updates, annual reports, prospectuses, account information, and much more, RPA alone won’t get companies to the future state of intelligent automation. That’s a major productivity hit and a significant roadblock. RPA needs an inspired nudge.
Alkymi can deliver a higher ROI for RPA platforms by creating a structure for unstructured document and email formats so that RPA solutions can leverage process-critical data as a workflow trigger or data payload. Many RPA processes are fueled by data that first arrive in emails, attachments, documents, spreadsheets, and PDFs. Equally important, many aren’t.
The cost of breaking this unstructured data logjam has simply been too high until now. For example, an RPA solution might trigger a different operational workflow when a current banking client tries to open a new account versus a brand-new one. Specific workflows require details trapped inside account statements or forms and can take days to process and push into an RPA-enabled internal platform.
With Alkymi, the unstructured data, like account statements, are instantly extracted, converted, and pushed into downstream systems for immediate processing. By eliminating a friction point and allowing RPA workflows to kick off sooner, clients get what they need and banks deliver better service.
RPA alone won't get you to a future state of automation, but it’s highly capable of going the distance once it gets through that first mile of automation. Alkymi is the partner that reliably passes the data baton at just the right time so process-critical data never impedes a winning automation strategy. Need help getting automation to work better?
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