Intelligent RPA in Banks- Bet your bottom dollars

Mar 20, 2019 Naman Negi

A slow economy, further stimulated by a do-more-with-less culture is compelling enterprises to introspect and devise methods to boost productivity. Financial functions are under significant pressure and within the BFSI sector, there is a continuous evolution due to high competition.

Banks are under pressure to

  • optimize costs
  • cut personnel costs
  • acquire skilled resources
  • increase productivity

All this lands us at the door step of Robotic Process Automation or RPA or just bots as these automated systems are frequently called.

Drivers for RPA Transformation

  • Clients– The commoditization of financial services has triggered the banks to enhance their customer experience. Getting the latest digital experiences, is a common expectation for the far-sighted and tech savvy clients.
  • Competition– It’s mandatory for the financial institutions to be digitally disruptive in terms of technology adoption, due to stiff completion from other Fintech players.
  • Cost– The need to reduce cost using smart technologies and invest more into innovation and customer experiences
  • Compliance: Compliance and Risk Operations backed by monitoring, and reporting processes are error-prone, labour-intensive and repetitive in nature.

RPA as a solution

  • Credit Card Processes– Many core processes such as straight through processing, automated activation, auto dialler for customer and issuer contacts etc. can be automated using RPA. Turnaround Time (TAT) reduced by 30 to 35% and significantly improved accuracy, increased productivity by 20%, and sizeable reduction in FTEs.
  • Anti-Money Laundering– The anti-money laundering investigation being mostly manual ,takes anywhere between 30 to 40 minutes for every alert depending upon the complexity, bank’s standards, availability of information in the various systems, etc. Most of the effort, close to 75%, goes into data mining and another 15% into data entry. RPA can help automate these standard tasks, leading to more than 50% reduction in time and save human hours spent at laborious manual activities. Further, any new regulation is easy to re-configure in a Bot with assured accuracy, making the process change faster with minimum glitches.
  • Regulatory Monitoring and Data Collection – Financial institutions are required to adhere to stringent regulatory protocols, which involves large scale data collection at various stages of customer interaction.  According to industry experts, human intervention accounts for 2%- 5% of total errors per 100 task, which leads to re-work, slowing down operations, and leading to noncompliance and fines. Tasks such as report processing can be slashed up to 90% with 30%-50% reduction for an average process.
  • KYC– An average financial firm spends US$60 on KYC compliances and customer on boarding.  IT spending for compliances is expected to increase by 20% in next couple of years. Some labour-intensive activities related to KYC that are good candidates for RPA adoption include customer information gathering from disparate sources, data entry into CRM, validating existing customer information, and compiling and screening those data. RPA can help reduce manual costs by 70 % with electronic identity verification It can also lead to increase in staff productivity and service levels by 35%- 50-%.
  • Mortgage Processing- The mortgage industry has always been process oriented, engaging with numerous players like loan officers, processors, underwriters across fraud checks, appraisal orders, title orders and so on. Using RPA, tasks like MERS verification that are critical to the completion of the underwriting process can be initiated seamlessly. Customer documents like credit check report, income statement or tax returns can be easily compiled and processes resulting in freeing up 20%-30% of underwriters time.

Future of RPA

Majorly, RPA deployments till now are at the basic level of automation. Cognitive RPA is the real game changer for BFSI, where cognitive technologies, Machine Learning models and Artificial Intelligence (AI) are combined with RPA.

According to a report by Interactive Data Corporation (IDC), following are some of the benchmarks worth noticing:-

  • Costs savings in the range of 30–60% can be achieved through RPA
  • RPA Implementation usually ranges from 6 to 12 weeks
  • Break Even Point for RPA investment can be easily recovered from 10 months to 2 years

Regulatory Compliance

The regulatory dispute around RPA technologies is way too simple—if an organization has designed its processes in a way that complies with regulations and the bots actually enact those procedures within the compliant parameters, then the liability of a regulatory breach disappears. And no deviation from predefined rules ensures the chances of a regulatory breach is significantly less.


Clients, competition, cost and compliance are the biggest drivers for RPA adoption by most financial institutions. And RPA has offered quickly implementable solutions for all these core concern areas.

Connect with Us to understand how we have helped some of the biggest financial institutions and how we can do the same for you too!


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Naman Negi

From Lucknow to Kolkata and then onto Bangalore, I have been exploring India and my career alongside. Market understanding and research pertaining to disruptive technologies like RPA, AI and IoT fascinate me endlessly. Music and long rides take up the rest of the while.