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RPA and the journey to AI

Tim Ulrich

In his first blog , Product Director at UiPath, Andrew Rayner, wrote about how leveraging robotic process automation (RPA) can streamline risk and compliance for organizations in the Banking, Financial Services, and Insurance (BFSI) sector.

In this blog, Andrew looks at the range of tangible business benefits that can result from leveraging RPA, and how the combination of artificial intelligence (AI) and RPA are set to create the digital workforce of the future.

                                                  Andrew Rayner, VP, Customer Success, UiPath

In my experience, what actually make managers take action to implement RPA are unadulterated results – the old adage “the proof is in the pudding” couldn’t be more apt.

To this end, here are just a couple of examples of how organizations in the BFSI sector have leveraged RPA to deliver streamlined risk and compliance, among other improved business outcomes.

Enhanced compliance for a healthcare insurance company

A service provider for the claims unit of a leading healthcare insurance company serving approximately 70 million individuals nationwide operated a claims management process that was manual, error-prone, and complex. It typically encountered high defect rates, resulting in a lower accuracy of loaded registration data. The process also entailed backlogs and a high turnaround time.

An automation strategy was designed and implemented in less than 15 weeks. Seven robots were deployed, resulting in:

  • Enhanced compliance.
  • 68% improvement in productivity.
  • 95% improvement in accuracy.
  • Risk-free transaction processing for sensitive data

Rapid RPA deployment for a large mutual bank

A large Australian bank automated two labor-intensive processes: rejected direct debits management and the verification of loan application documents. While the first required manually checking paper-printed transaction reports that determine whether the bank would honor or reject the direct debit payment, the latter entailed manually checking documents on different web portals and other data for home loan applications.

In the first process, the automation solution meant that software robots captured the reports using intelligent optical character recognition (OCR) and converted them into spreadsheets. They then took the customer information from the core banking system, analyzed it, and decided for or against paying the direct debits. Robots automated 95% of transactions, increased accuracy, and delivered revenue growth. Digitalizing the client paper-records enabled robots to track records into the CRM system.

In the second process, robots quickly opened the different web portals, verified the information, and sent emails to the employees that needed the documents to reach a decision. The project led to 20 hours being saved per week and a significantly faster time to give clients a decision.

The automation journey to AI

While RPA is battle-tested in risk and compliance-related processes – delivering accuracy, speed, and increased productivity in a field profoundly marked by increased regulations – emerging cognitive and machine learning technologies will be integrated into taking financial organizations to the next level of efficiency.

However, let’s be clear. AI won’t replace RPA. Rather, the two technologies will combine to create the digital workforce of the future. AI needs RPA to deliver to its fullest potential. Although RPA can easily replace manual, repetitive tasks of moderate complexity, an RPA platform with embedded AI tools and capabilities will be able to compete with intricate processes typically specific to knowledge workers.

An enterprise RPA platform like the one UiPath delivers is already able to handle semi-structured data forms. Using intelligent OCR, robots classify, interpret, and extract data from different types of documents, such as comparing bank statements and verifying national IDs or pay slips. With an intelligent RPA platform, these processes are smoothly automated, significantly reducing the time otherwise spent by loan officers.

Machine learning and natural language processing (NLP) combined with RPA also find an equally fertile ground in compliance. Automating processes requiring reasoning, such as risk data quality management, customer credit scoring, and suspicious transaction resolution offers a more accurate predictive analysis, enables employees to spend more time doing a proper review, and helps financial companies take more informed decisions.

Many organizations are enabling employee and customer self-service with the use of virtual assistants (or chatbots). Chatbots use NLP to interpret the human input – be that voice or text – and can have an open dialog with the human, gathering data and clarifying content. Integration with RPA technologies such as UiPath enables chatbots to send the output of the conversation, i.e., the structured data, to the robot to process against back-end systems.

A few final words…

As more and more BFSI companies take the leap into implementing RPA platforms, the compliance landscape is changing radically. With AI, NLP, and computer vision, software robots will become all the more autonomous and will no longer depend on human supervision to take decisions when handling complicated tasks.

Automation isn’t a “plug-and-play” project, but a journey. And we’re only just at the beginning!

To learn about how UiPath’s automation technology contributes to Capgemini’s Automation Drive to deliver new ways of working, drive innovation, and increase business value, contact:

Learn more about how Capgemini and UiPath deliver superior business outcomes

Tim Ulrich  manages intelligent automation and RPA solutions across Europe, helping clients to increase process quality and efficiency, and reduce cost by deploying leading automation technologies.

Andrew Rayner designs and builds large enterprise applications for global companies, driving innovation and helping partners to deliver industry strength automation.