Insuring a better future with cognitive RPA
It is a truth universally acknowledged that robotic process automation (RPA) is a blessing for the insurance industry that has to wrangle a plethora of data around it. Needless to say, it is a far cry from the manual processing of claims, invoices, customer databases, tax documents, etc. However, if you scratch the surface, a natural question tumbles out.
Is RPA enough for handling processes in businesses?
Source: Everest Group
Remember, of all the enterprise data we have today, only 20% of it is what one would call structured. That is, data that is already organized and ready to be processed, like web pages, simple spreadsheets, CSV files, etc. This area presents the biggest scope for first generation RPA. Here, data extraction is straightforward and it usually results in just 30%-40% Straight Through Processing (STP) and, ultimately, human intervention is higher.
But what about the rest of the 80%? Labelled as semi-structured or unstructured, this lot forms the bulk of data around us. Think emails, images, videos, contracts, financial reports, legal briefs, invoices, complex excels. And the list goes on. Traditional RPA, with low STP and high manual intervention, is incapable of making complete sense of so much disorganized data.
The evolution of RPA into CRPA
To tackle this situation, RPA has evolved (see illustration above) into a branch that is smarter, more intuitive and mostly independent. Cognitive RPA (CRPA) combines the power of RPA with rules engines, AI and ML to transform data into accessible formats. In an effort to bring structure to unstructured data, cognitive RPA technologies like Optical Character Recognition (OCR), Natural Language Processing (NLP), process visualization and analytics, etc. all contribute to an increase in STP of more than 70%, with minimal human intervention.
Cognitive RPA processes unstructured data, recognizes patterns, predicts the categories, and performs the next course of action. It not only results in efficiency gains, increased accuracy and productivity but it also reduces overall costs and processing time. Ultimately, it majorly contributes to retaining the customer base and catering to the modern clients with minimal patience for errors and high TATs.
Rethink insurance with CRPA
Cognitive RPA is a technology tailor made for an industry like insurance. With a continuous flow of incoming data, huge potential of dark data lying around, and a high volume of unstructured data in the form of images, claims, legal deeds, KYC forms, policy forms, etc., the need of the hour for incumbent insurers is cognitive RPA. It has a tremendous potential of unlocking rich insights from semi-structured and unstructured data in insurance across verticals like life, health, auto, etc. that helps leaders take informed and game-changing decisions. Thanks to cognitive RPA, managing areas like claims reimbursement and high-performance workflow automation is easier. The impact of cognitive RPA is also felt in other critical areas in insurance like sales and distribution, underwriting and pricing, policy admin and servicing and accounts (see illustration below).
A new breed of digital-first insurers has already woken up to the wide possibilities of cognitive RPA in insurance and are using it to power their processes. For instance, Snapsheet that specializes in claims management technology automates their end-to-end total loss claims processing with little or no manual operations. Similarly, Tractable helps in assessing vehicle damage in real-time by using image recognition to support triaging and validate repair-cost estimates automatically.
According to a research estimation, by 2026, the global cognitive RPA market is expected to reach $3,620.8 million, growing rapidly at the CAGR of 60.9%. Late movers or incumbents in the industry need to realize the magic touch of cognitive RPA across their portfolio and embrace it sooner.
The ROC advantage
Now, a complex AI-driven automation initiative like cognitive RPA is majorly anchored by bots. They need extensive strategy, support, maintenance and trouble-shooting arsenal around it – in a continuous manner. Process changes, app updates, security patches etc. have a huge impact on bots and involve human intervention. Bot maintenance and governance should be a conscious and well-thought out strategy from day one. Having a Robotic Operations Center (ROC) in place makes the job easier for enterprises betting big on cognitive RPA. Typically in large enterprises, while the bot production happens in automation factories, the governance and maintenance of the bots are handled by an ROC.
Through processes like incident management, problem management and bot governance, an ROC maintains control of the automation activities to proactively recognize gaps, address all possible conflicts and overcome potential downtime. For any business looking at large-scale cognitive RPA implementation, having an ROC in place becomes an imperative.
It’s time to insure a secure and more productive future with cognitive RPA. For more information on the role, impact and implementation of cognitive RPA in insurance, check out our e-book on transforming the insurance ecosystem with the technology.