Robotic Process Automation (RPA) Technology

Published by Nilofar Pathan on


Robotic Process Automation (RPA) is a new technology that aims to create software robots (bots) that mimic human behavior. Transitioning to RPA, enterprises aim to reduce labor costs, increase productivity, reduce error rates, and improve customer satisfaction. Increasing average cost of workers around the globe enterprises adapt the RPA technology very fast in the past few years. RPA has become one of the most trending technologies in many industries.

Robotic Process Automation is a technology that aims to reduce human involvement in computer applications, especially in repetitive tasks that vary very little in each iteration.

This technology is suitable to replace simple and repetitive manual tasks such as data entry in applications. This means that employees have more time to focus on other branches of value for the company such as decision-making or improving customer relations.

It is a relatively fast technology to implement and can therefore bring immediate benefits to a company through time and cost savings. especially if it can be applied to the bottlenecks of certain processes.

The term RPA can be dated as early as the mid-2000s, although the underlying technologies such as computer vision and workflow automation have been developing for some time before. While RPA is still considered a developing technology, it still relies on artificial intelligence (AI) technologies.

Screen scraping, and workflow automation and gets these technologies to a new level, advancing their capabilities in a significantly improved way. Rather than being dependent on code as is required for screen scraping, RPA software provides tools for users to build workflows in a visual way that can be entirely independent of coding knowledge.

Also, unlike many web scraping tools, some RPA software makes use of optical character recognition (OCR) technology to adapt to changing websites without requiring intervention from a human employee.


Robotic process automation (RPA) integrates automation with artificial intelligence (AI) to automate processes through the deployment of custom applications. The use of AI is about manipulating intelligent algorithms to resolve inefficiencies and drive enhanced customer experience at every point of interaction.

An RPA solution emulates human actions to automate the tasks that require human intelligence, without challenging changes to the underlying systems and processes. RPA is about employing software robots with the ability to replicate human actions to eliminate inefficiencies in the processing of information or data. Simply put, RPA calculates a virtual workforce with skills comparable to that of human beings.

The commoditization of financial services has spurred banks to improve front-end services and customer experience. Backend operations, however, have not received as much attention. and offer tremendous scope for improvement. Backend processing typically involves high volume, rule-driven. repetitive tasks that are labor-intensive, and therefore, prone to errors.

When automated using RPA. these tasks will not require the constant intervention of skilled human resources who can thereby focus on higher value-adding activities. The investment is minimal as RPA does not need any changes to the underlying legacy IT infrastructure.

At the same time, it speeds up core processes, significantly enhances productivity and accuracy, lowers costs, and cuts time-to-market for new offerings.


Robotic process automation’s workflow efficiency benefits have been of great value to financial services organizations.

Bots can perform repetitive, clerical tasks such as processing customer applications and responding to basic customer queries faster and more accurately than human workers. Bots also behave more predictably than people.

They do not depart from their programming so they will not make mistakes or avoid processes. Accordingly, RPA is a powerful risk management resource that many institutions already use to monitor compliance and create audit trails.

RPA is an enabler of new digital financial technology (fintech) that enhances the quality of service and convenience for employees and customers alike.

RPA can be used to bridge integration gaps between legacy software. For instance, RPA can act as an integration mechanism that integrates legacy solutions into newer IT systems.

This allows banks and other financial organizations to expand their fintech footprint gradually and with minimal interferences to existing processes. Rather than uprooting and replacing existing legacy tools, bots can push and pull data between new and old applications.

Robotic process automation can also reduce the testing surface of new custom developments and fintech applications. Software robots, which have roots in software QA automation, can be used to validate the output of new custom developments. Consequently, new financial services can be developed with tentative aspects of wealth management.

Human financial advisers supply qualitative consultations. This is a perfect example of adding value to a customer relationship by liberating human workers to focus on judgment-based services.

The Internet of Things (IoT) is expanding the scope of financial technology services. Customers can now link their financial data to wearable technology and even household appliances. Software bots’ ability to interface with the front ends of many application types can help automate the real-time movement of information between systems.

Likewise, RPA is an enabler of blockchain technology. Blockchain uses a distributed digital ledger system to verify data inputs through a consensus. No single source controls the ledger, which makes it difficult for anyone contributor to commit fraud.

For this to work properly, financial organizations will need to continuously record data entries and attributes such as time stamps, geo-location, and more from many disparate APIs and IT systems.

The benefit of RPA bots is that they can operate as fluidly as humans can across IT infrastructure. This means RPA can effectively bridge multiple disparate systems to the blockchain.

Robotic process automation may also be important for blockchain security. financial services organizations will still need to prove the validity of their blockchain applications. Auditors must answer important questions such as “Who controls the blockchain?” “Who gets access and “Who monitors activity?” Rather than manually auditing the blockchain.

We are automating these verification processes. And just as RPA can be used to validate data for compliance purposes, we anticipate that it will have a role to play in auditing the blockchain.

Many businesses are already using bots to enable fintech innovation. But like we said at the beginning of this post, most financial organizations have only skimmed the service of RPA’s potential.

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