Robotics process Automation or RPA is one of the digital levers which is fast becoming a tool of choice for many banks, RPA generally refers to an automation type which mimics human behavior and helps in automation of processes which are standardized, low on the exception and highly manual intensive. Along with the standard benefits which an RPA implementation brings in, it is also helping banks achieve compliances and bring in greater degree of control on EUC (end use computing) processes. The adoption of RPA related technologies is gradually gaining momentum with the investments in the area pegged to touch close to USD 1bn by the end of 2019, 40% (approx.) of which is expected to happen in the BFS area (Banking and Financial services) and 10%  to 15% (approx.) of that spend is expected to be done in the Risk and compliance area.

The Risk and Compliance function in BFS is constantly grappling to contain the compliance costs, gaining better control on processes, maintaining required operational agility to meet compliances and improving system efficiency. The efficiency issues arise mainly due to presence of legacy systems, collating data across multiple LoB’s and presence of high manual processes which are error-prone. In such scenarios, RPA comes as a potent solution which can help banks to

  • Improve efficiency without tinkering with the existing Legacy systems
  • Provide required agility to scale as per compliance needs
  • Maintain better control on processes through required auditability
  • Automate manual intensive efforts and reduce errors.

RPA adoption levels in Banks

In the Banking and Financial services industry especially in the Risk and compliance area, the adoption of RPA is still in nascent stages. Currently, most of Investments are being made by Banks in proof of concepts or POC’s to assess the value or the return on investment it brings to the table. Like any technology, RPA adoption can happen in many forms (depicted in image below)


Figure 1 – RPA Adoption in Banks

Initially many Banks started using RPA for short term and tactical gains, however as the RPA technology and the concept are maturing, more and more possibilities of leveraging RPA for strategic needs too are being explored like for e.g. judgment based tasks, intelligent rule based automations. To achieve the desired state banks have also started looking to integrate RPA with other digital investments in the area of Machine Learning, Natural Language processing (NLP) , Chabot’s etc. and are gradually progressing towards the desired state of Cognitive RPA.

RPA as a Transformational Lever

Initially it was thought that RPA‘s are very tactical solutions, however as the Digital portfolio continues to evolve RPA is slowly evolving in to a transformational lever which without impacting the exiting IT landscape can also aid in carrying out strategic tasks by combining with cognitive technologies like machine learning. The outlook change can also be seen in the Risk and compliance areas where the adoption is gradually moving from simple Risk tasks to judgement based tasks which involve review and decisioning. Also, Banks are investing in RPA‘s at an enterprise level, rather than specific point solutions for RPA.These changes clearly indicate that RPA is becoming more and more strategic investment which is being done by Banks to improve efficiencies and save compliance costs.

 RPA adoption in Risk and Compliance

In the Risk and Compliance area the RPA adoption is still in very early stages. Currently most adoption is happening in areas such as KYC onboarding, Risk regulatory reporting generation etc. where the activities are very standardized and involve Data Collation, Data aggregation , email integration and simple rule-based automations to quote a few.

As the concept is maturing newer adoptions have started in areas like AML alert investigation, credit reviews, risk reconciliation, generating risk reports with high volumes and high frequency like for e.g. Daily LCR reporting, these processes typically involve complex business rules, processing unstructured data, involve macros etc.


Figure 2 – Key Risk and Compliance RPA use cases

The Banking industry is currently envisioning a target state where RPA can be combined with the cognitive capabilities such as machine learning, Natural language processing etc. Many Banks have also started focusing on this and are in the process of identifying use cases which are a good fit. In risk and compliance typically use cases which are judgement based can be good candidates for Cognitive RPA. E.g. Limit breach management, Risk Data Quality management etc. Though many banks are keen to leverage Cognitive RPA capabilities they are also cognizant of the fact that it is not desirable to automate judgement based tasks completely in the Risk and compliance area, due to the nature of the function. Even though some of the banks are leveraging components like machine learning for risk assessment &decisioning, however the output from such cognitive RPA solution is designed to improve the turnaround time for Risk processes and also provide suggestive recommendation to the Risk Analyst. The final authority of decisioning is still resident with the Risk function in the solution.

Enterprise Level Platform based approach for RPA adoption

Banks too have started perceiving the RPA adoption in a more transformational manner rather than a point solution. Initially, when Banks started experimenting with RPA solutions their approach was very much operational in nature, siloed and was very low on reusability aspects. As the concept is evolving more thrust is being given by Banks by adopting RPA at an enterprise level. Banks are now forming dedicated RPA centers of Excellence or CoE’s to manage RPA program at an enterprise Level. The core function of this CoE is generally

  • Establish standards for identifying and assessing RPA use cases
  • Develop and Execute use cases across Lines of Business (LoB’s)
  • Deploy and manage RPA installations
  • Capture and Manage reusability aspects that can be leverage across RPA use cases for different lines on Business


Figure 3 – Typical RPA Adoption Framework

Focusing on reusability

Reusability in RPA is another concept which is fast gathering steam, reusability in RPA means capturing and managing aspects from an RPA implementation and then leveraging the same in some capacity for subsequent RPA implementations, which eventually reduces development efforts. Many Banks have started thinking in this area and are working towards establishing a framework which enables to identify the reusability aspects of RPA implementations. Many 3rd party RPA tools also provide a library space where the reusability aspects can be captured and leveraged for subsequent implementations.

Challenges in RPA adoption

No Change comes without its share of challenges, even in case of RPA adoption the Banks are facing the following key challenges

  • Regulatory uncertainty over the use of RPA solutions. No formal or defined requirements from regulators on use of RPA technology for automation which is making the adoption very cautious
  • Unstable Business Processes – Many Banks have manual processes which are not very well documented or stable which makes it difficult for them to for RPA adoption.
  • Most of the initial RPA adoption has been in silos and the Banks are still in the process of putting in place an Enterprise-wide RPA Adoption and a governance framework.
  • RPA Technologies are still evolving and are fast changing

Road Ahead

As RPA technologies are becoming more and more mature, it is opening up many complex problem statements in Risk and compliance for adoption. The future for the RPA market is very promising as the key aspect which makes an RPA likeable is that it does not interfere with the exiting IT investments and also provides quick and efficient solutions to the business users, this makes RPA an agreeable solution for both Business and Technology.

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