A Virtual Workforce in Banking

Banks today continue to be driven by the dual objectives of driving business innovation to deal with the threats created by the Fintech players and the digital only neo-banks, and creating cost optimization through operational efficiency initiatives. In a growth constrained environment, the investments needed to fuel business innovation has to come from the savings generated through the operational efficiencies.

A key lever in driving operational efficiencies and cost reduction has been the deployment of RPA or Robotics Process Automation solutions. A RPA solution refers to the deployment of “software robots” that can be configured to create a virtual workforce that can mimic the human actions needed in many of the banking processes.

The robots need a one-time “training” through a process flow mapping exercise, but once trained can carry out the repetitive tasks in a process at much higher levels of speed and accuracy than a human can. Depending on the complexity of a process, a RPA bot can either perform a process step completely or work like a digital assistant to the human and do the heavy lifting needed before a human can make a decision. The range of activities that a robot can perform include completing forms, data validation and reconciliation, logging into various enterprises systems and carrying out process steps.

RPA solution providers like Automation Anywhere, BluePrism, Ui Path and Pega RPA (earlier OpenSpan) have seen large scale adoption in the banking and financial services industry over the last couple of years. Most of the large banks have hundreds of bots automating a wide range of processes from the front office to the back office. Some of the typical use cases include:

  • Retail Banking: account opening process, KYC checks, account maintenance like address change and beneficiary change, credit card processes like payment disputes
  • Corporate Banking: cash management and loan collections, trade finance processes, forex operations, client onboarding process
  • Investment Banking: trade confirmation matching, trade contracts creation and validation, nostro postings, margin call management
  • Finance & Risk: creation of MIS reports like performance and balance sheets, cash position reconciliation, risk reports aggregation

Making RPA More Intelligent

In the first wave of the virtual workforce adoption in banks, RPA providers and banks have focused on using robots for high volume, repetitive tasks (referred to as deterministic RPA) and freeing up the human bandwidth in the operations departments to focus on higher value tasks. Banks have also been able to handle larger volumes as they grow without having to scale their backend staff. This has resulted in substantial cost savings in their operations.

But as the benefits realization from the deterministic RPA implementations begins to taper out, banks must start looking at cognitive RPA solutions and the deployment of Machine Learning (ML) and Artificial Intelligence (AI) in their process automation initiatives. This new wave of process automation would be focused on increasing the level of intelligence and making the robots more autonomous.

This intelligent virtual workforce would be a lot less dependent on human interference and be able to perform more complex tasks that need decision making beyond the “if-else-then” kind. Cognitive robots have the ability to learn from experience in the way a human operator would and are therefore able to mimic human judgement in making decisions. The longer a cognitive bot performs a process, the better it gets at it.

Some of the solutions that offer cognitive RPA and AI/ML solutions include Workfusion, IBM Watson and Fast Forward Labs.

For banks to realize the full benefits of cognitive RPA, however, they must combine it with technologies such as speech recognition, natural language processing (NLP), machine learning and OCR (Optical Character Recognition) / HCR (Handwriting Character Recognition). A typical use case can be trade surveillance where call monitoring using voice to text conversion first and then using cognitive pattern recognition can be used to detect trade fraud.

Other process areas where cognitive RPA and the related technologies can add a lot of value are the ones that involve many contracts and invoices e.g. Trade Finance and Derivatives Trading. The documents involved in these processes are in various formats (handwritten or PDF) and in differing languages, and manual processing is cumbersome and error prone. Using a combination of OCR/HCR, NLP and RPA technologies can significantly improve speed and accuracy of these processes.

Managing the ROI Conversations

It has been easier to make the business case for deterministic RPA – the cost saving has been a direct function of the reduction in the manual effort spent by the operations staff managing the processes being automated.

As we move into the realm of cognitive RPA and ML/AI solutions, ROI realization would take longer. The business case therefore needs to move beyond just the immediate cost take out. The following are parameters to consider in coming up with the business case:

  • Increased accuracy with lower cost – robots with cognitive ability can play the checker role in addition to the maker role (realized using deterministic RPA) in many of the maker-checker functions in banking operations. This can lead to redeployment of more senior bank staff such as supervisors and therefore higher cost savings eventually
  • Better analytics – using a combination of human + machine capabilities for judgement based processes can drive more informed business decisions and help in detecting fraud
  • Reduced risks – cognitive robots deployed in the regulatory space, for example, can reduce risks related to reporting errors by minimizing the human factor

Cognitive RPA and the use of ML/AI in banking process automation is set to see an exponential rise in the next couple of years. Banks that lead the adoption will see much better ROI benefits. The time to make the virtual digital workforce more intelligent is now!


The article was originally published on Financial Express and is reposted here by permission.

Deepak Atmaram Kinger

Vice President, Banking & Financial Services, Virtusa. Deepak Kinger is a Vice President with Virtusa and leads the Banking and Financial Services business for the Asia Pacific region. He has over 20 years of international experience in financial services across Retail, Commercial Banking and Capital Markets. He has lead business growth across global client portfolios spanning North America, Asia, Middle East and Europe. For Virtusa, Deepak is responsible for the business strategy, client management and sales for the BFS MEA segment with a special focus on innovation. Prior to joining Virtusa, he has held leadership positions with Sapient Global Markets, Genpact Headstrong and Wipro. Deepak holds a degree in Computer Engineering from Pune University.

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