How RPA (Robotic Process Automation) Helps Finance Companies Gain Profits
Robotic innovations in Fintech are in their early stage. However, the leading consulting companies issue reports about the future success of RPA in banking services, while big-name financial institutions are investing in the technologies to win from their benefits in the long run.
What is standing behind this optimistic approach to RPA development in Fintech?
Key Highlights about Robotic Process Automation in 2020
In July 2019, Gartner issued its Magic Quadrant for Robotic Process Automation Software. It reported that though the RPA market is still relatively small – in 2018 it generated around $850 million – it is maturing and consolidating at an impressive speed. Moreover, Robotic Process Automation in finance is the fastest-growing enterprise software subsegment today, with year-over-year growth of more than 63% in 2018.
At the end of 2019, Gartner issued another report regarding RPA’s potential, called “Predicts 2020: RPA Renaissance Driven by Morphing Offerings and Zeal for Operational Excellence”.
RPA doesn’t substitute the human workforce
Robotic Process Automation is not a synonym for humanoid robots from sci-fi movies. Specialists see it as “an invisible automated hand”, taking over repetitive yet labor-intensive tasks: simple request processing and handling, reporting, data entry, and so on.
This is how Gartner defines RPA development: “RPA involves developing integration scripts that get information in and out of other systems”. In other words, RPA development tools understand organizations’ business processes and automate them with dynamically generated scripts, or robots.
However, in 2020 they can’t automate everything: Robotic Process Automation tools learn and replicate what people do – but can’t fully replace them. Human participation is still needed to validate business process maps, optimize inefficient process routes and cope with the exceptions that RPA scripts can’t handle yet.
Finance Process Automation is a long-term journey
Given the infancy of RPA technologies today, dynamically generated scripts are marginally better than those created by humans. However, backed up with ML advances, the scripts will improve dramatically and become commonplace by 2024. So businesses which are thinking about launching RPA-centric automation initiatives, shouldn’t expect instant returns, but focus on the long run plan.
RPA in finance will be getting more complicated
Today’s RPA tools are mainly task-based offerings, which are best suited for simple, well-defined and highly repetitive processes. But they are evolving into more complex projects, automating decision-driven and exception-heavy processes, able to self recover and self learn. RPA development companies will soon be expected not to solve specific pain points with Robotic Process Automation tools, but discuss the rearrangement of the overall existing processes.
Robotic Process Automation in finance will rely heavily on complementary technologies
To handle a growing number of use cases, RPA initiatives will be augmented with complimentary technologies: process mining (also referred to as process discovery or e-process mining), ingestion engine (OCR, computer vision, etc.), analytics, user experience and Machine Learning. Gartner refers to the collective functionality as CoRPA.
Misunderstanding of the RPA role in the enterprise
Though RPA is already influencing multiple sectors, many businesses, mainly including banks and financial institutions, still underestimate the complexity and global impact of robotics tools. They jump into RPA initiatives – and fail if this is done without proper analysis, planning, defined strategies and the overall IT and architecture redesign.
Benefits of Robotic Process Automation & Real World Use Cases In Fintech
Today’s RPA tools in financial companies and banking institutions focus on 2 major types of core benefits.
Augmented process automation is one of the key initiatives across multiple sectors today. Gartner’s study published in June 2019, showed that approximately 44% of customers were planning to use ML and natural language processing (NLP) functionality to automate business processes.
Robots, which leverage both ML and NLP technologies, can be applied in Fintech for multiple reasons:
- Cutting operating costs. Robotic Process Automation substitutes and augments the human workforce, allowing to achieve more in less time with fewer resources. As a result, a financial company gets increased efficiency with reduced staff and a decreased need for physical locations.
- Ensuring compliance with regulations. RPA puts in place tools that monitor all electronic communications of employees and define noncompliant activities.
- Increased efficiency. There are a number of use cases on the Fintech market today, proving the capacity of Robotic Process Automation to effectively automate mundane, routine administrative processes. Here are the stats from the Bank of NY Mellon Corporation: after the bank launched more than 200 bots, to handle repetitive simple tasks such as transferring funds, it reported an 88% improvement in processing time and $300,000 savings.
Another prediction from Gartner: by 2023, there will be a 30% increase in the use of Robotic Process Automation for front-office functions, first of all customer experience.
No wonder: customers are getting more used to interacting with “digital native” brands like Uber and Amazon in their daily lives. This is reshaping their expectations from other industries, for example their banks: now they are looking for the same personalized communication, with requests processed within a millisecond – and all this without setting foot in a branch or talking on the phone.
- Processing customer queries in real time and increasing sales conversion rates. Robotic automation significantly improves back office productivity and operational quality, and as a result increases sales conversion rates.
For example, the Italian Banca Popolare di Sondrio (BPS) bank had typical problems with its contact centre: 500 agents were handling around 650,000 calls a month and spending too much time on follow-up activities after each call, like logging job tickets and call details in relevant databases, filing claim requests, etc. Due to the volume of activities, operatives were frequently failing to meet a five-minute response time target for fraud alerts.
The bank introduced RPA to automate most of the manual post-call activities: the implemented robot draws the necessary information from internal systems and submitted requests, processes it and creates new customer files. In parallel, desktop automation tools have been set up to guide agents through a complicated fraud alert process.
The result is impressive: 100% of requests are processed on time, with average handling time of the wrap up phase reduced by 82% and 99% accuracy in the handling of more than 8,000 fraud alerts a month.
- Eliminated risk of human error. Robotic automation helps put in place a step-by-step instruction which a robot follows whenever it reviews financial documents, issues mortgage approval, processes credit card orders and cost accounting. Human participation will be reduced to a minimum, with experts intervening only when an exception or a force-majeure event occurs.
- Setting the right priorities. As noted by Will Davenport, director at Business Systems Ltd., the average employee spends around 80% of their time on mundane and routine tasks, like data entry, form filling, filing and archiving, and so on.
RPA-ensured tools allow employees to focus on concerns of higher priorities, leaving low priority issues for bots.
Robotic Process Automation in Finance: How to Start the Journey
- Define the global goal. Do you want to increase the back-office efficiency? Get a new source of revenue? Or improve customer engagement rates? Once you know why you are starting process improvement or implementation, it will be easier to determine how to leverage Robotic Process Automation in this process.
- Create a roadmap. When the goal is clear, conduct a thorough study of what hinders its realisation. This will help identify inefficient business processes, detect gaps and gain an in-depth visibility of what must be reengineered and automated.
- Determine the place of Robotic Process Automation within the strategic roadmap. Robotic automation is only efficient when it is seen as part of the overall structure and not a single targeted technology.
- Ensure coordination across different units. As RPA functions across the whole organization, aggregating data from multiple sources, all the company’s departments – IT, security, accounting, etc. – must have a clear understanding of the robots put in place.
- Educate staff on process automation and RPA technologies. Not only should they know about the implemented Robotic Process Automation scripts, but see how these scripts impact their functions, automate certain processes, and leave time and effort for more strategic and creative tasks.
Due to a vast expertise in FinTech and Robotic Process Automation development Itexus will be glad to partner with Financial institutions and businesses as an RPA developer.
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