The Banking and Financial Services industry has undergone an enormous transformation over the last decade. Changing regulations heightened scrutiny by regulatory bodies, heavy compliance costs, and hefty fines were a few reasons behind that transformation. The increasing operational demands and obligations led the traditional banking institutions and startups to look at cutting- edge technological innovations to start looking for answers to their problems.
The Rise of FinTech and RPA in Finance
FinTech emerged and became the new mainstream in 2016, causing disruption in the Banking and Financial Services industry. It brought a fresh perspective to such business challenges through the use of innovative technology.
Robotic Process Automation (RPA) is one such innovation.
RPA has helped financial institutions automated several manual tasks by replacing humans with digital machine labor. RPA provides organizations with digital speed and greater operational efficiency, freeing up skilled labor to perform complex decision-making tasks.
RPA’s potential is grabbing the attention of IT consulting and advisory firms, outsourcing providers, and enterprises alike.
Initially, when this “robotic” software is configured, it captures and interprets the actions of existing applications employed in diverse business processes. Once it has been trained to understand specific processes, it mimics how an employee would process transactions, manipulate data, trigger responses and communicate with other systems when necessary. It manages rules-based and repetitive tasks, allowing human workers to focus on more valuable, customer-facing customer-facing roles.
RPA is finding widespread application in the Banking and Financial services world, especially in Retail and Investment Banking space. Let us now have a look at a few of the functions where RPA is finding its relevance.
Identifying Use Cases and Implementing RPA in Finance
Analysts has identified the following pre-requisites for identification of a use case for an initial RPA implementation as follows:
- Identify a rule-based process which does not involve decision making or judgment
- Make sure that the process should be initiated by a digital trigger and supported by digital data
- Confirm that the process is performing its desired function and is stable
- Check whether the process involves a high volume of executions
- Check whether the process leverages the key systems of the firm so that it can be used as a proof of concept
We have a simple 1-2-3 formula to implement RPA:
- Identify the processes which can be automated with a robot
- Take a suitable process and automate as a pilot in the development environment
- Implement in production and scale
A classic example of a process where RPA could be implemented is KYC Compliance.
Many organizations across the globe use manual and time-taking tasks for checking identity information of prospective clients against numerous watch lists and public databases of law enforcement agencies and collect and integrate the necessary data from external sources and internal systems.
There are obvious challenges to carrying this out as a manual process: keeping this manual makes it hard to keep up with the ever-increasing and evolving regulations. Onboarding remains slow and impacts revenue realization. Increased costs of compliance along with steep fines for violations have paved the way for organizations to embrace RPA.
Organizations that have implemented RPA or are in the proof-of-concept stage of discovery have reported that RPA implementation:
- Reduces cycle time and improves operational efficiency by up to 90%
- Reduces manual costs by close to 70%
- Increases staff productivity, service levels and capacity by 35-50%
- Frees up knowledge workers for strategic assignments
- Association with multiple tool vendors that makes us tool-agnostic in order to implement the relevant tools based on clients’ requirements
- Strong domain expertise and a team of experienced professionals to ensure a smooth transition
- Successful RPA implementations across the industry for multiple clients (across several domains, including healthcare and logistics)
- including implementation of 100+ process robots for automation of routine tasks
- Well defined solution framework and time-tested delivery model that consistently helps clients improve operational efficiency