Why connected RPA matters, IT News, ET CIO
By Suyash Dubey
Bob and Zac, two digital employees at Singapore-based Oversea-Chinese Banking Corp. (OCBC), did something extraordinary. Working on the secured loan team, Bob is able to reevaluate home loans in just a minute compared to the normal 45 minutes it would take another employee. With this amazing productivity, home loan restructuring processing time has been reduced by 97% as Bob can process more than 100 home loan restructuring applications per day.
Zac, on the other hand, generates daily sales performance reports in just 12 minutes, which would take over two hours for a human worker. The management team now receives the report every day at 9 a.m. instead of 4 p.m.
Bob and Zac aren’t humans – they’re powered by Robotic Process Automation (RPA), which combines robotic automation with Artificial Intelligence (AI) to automate human activities for large companies. In turn, companies around the world are lining up to deploy these digital workers in their own businesses.
According to Gartner, RPA is the fastest growing segment of the global enterprise software market. RPA software revenue grew 63% to $ 846 million in 2018 and is projected to reach $ 1.3 billion in 2019. Gartner also says that RPA is transforming businesses across industries, but the biggest users are banks, insurance companies, telecommunications companies, and utilities.
There are two main reasons banks and financial services companies pioneered the implementation of robotic process automation (RPA) from the start. First is regulatory compliance; The BFSI industry is one of the most regulated in the world and must thoroughly comply with the myriad of laws, policies, and procedures set by central banks, governments, insurance companies, and other regulators.
Second, paperwork is ubiquitous in banking workflows, which requires extensive and monotonous data entry. When digital workers take on data entry and other repetitive tasks, they not only reduce employee workload and lower costs. but also guarantee 100% accuracy and thus full conformity.
Today, RPA implementation is typically at the center of a modern company’s digital transformation initiatives as the company can take advantage of automation without sacrificing expensive investments in legacy systems. It should be emphasized that multiple existing legacy systems are not only business critical, but are also well anchored as they are used by a large number of employees over several years or decades. So the question arises: Can RPA be implemented without expensive and extensive changes to existing systems?
The answer lies in evolving RPA into what we know as “Connected RPA”, an entirely new approach that is transformative in that it can be implemented quickly and does not require coding. Essentially, Connected RPA is spawning a new generation of digital workers who can access and read the user interface of legacy systems to interoperate and coordinate third-party applications – just like any other employee. For the first time the non-technical user is responsible for an IT project.
The new generation digital workers therefore have universal connectivity capabilities that enable them to learn intelligent automation skills through a broad ecosystem of complementary technologies. In other words, business users who don’t understand IT can quickly train their digital workforce to integrate and use new or existing applications. They can also create automated processes in their existing applications using a visual drag-and-drop tool and pass them on to their digital workforce to run.
Ultimately, Connected RPA enables a company not only to quickly and easily build and deploy a digital workforce, but also to ensure secure connectivity between digital employees and the rest of the people, processes and systems.
The future is autonomous
The integration of Connected-RPA in AI and ML already delivers results in various domains and use cases. Insurance companies are using automated processing and resolution of insurance claims cases, while banks are implementing automated money laundering prevention in conjunction with blockchain technologies and business process management tools. For customer support, the integration of Connected-RPA in AI enables multilingual, automated e-mail processing for incoming customer inquiries. Other companies are testing AI tools to measure sentiment analysis, intensity, and sentiment for customer support. Subsequently, inquiries are automatically forwarded to a customer representative.
Connected-RPA’s ability to work across ecosystems means that well-designed RPA tools can adapt to entirely new business ecosystems based on AI, ML, blockchain and other transformative technologies. In fact, it can be predicted with certainty that connected RPA will continue to evolve, even if it is better to provide autonomous process automation in the future.
The author is Head of Marketing India at Blue Prism
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