Robotic Process Automation powers digital Transformation in Insurance Industry
The era of robotic process automation (RPA) coupled with deep learning is here. From back-office functions to customer solutions, it has effectively turned processes around on their heads. Leading banks, hedge funds, and asset managers have successfully leveraged RPA tools not only to streamline standard processes but also to save money significantly.
Juniper Research on automation in the insurance industry says that almost half of all insurers will invest in RPA by 2024. Another study from McKinsey on digital disruption in the insurance industry found that AI automation can cut the cost of insurance claims processing by up to 30%.
Robotic Process Automation (RPA) helps in dealing with these back-office activities, managing operational challenges. Companies can streamline their processes, paving way for digital transformation, by leveraging analytics / Cognitive / ML / NLP capabilities along with RPA.
Automation Potential in Insurance
Insurance Business Processes can be broadly classified under three categories - strategic, knowledge-based, and transactional processes.
Repetitive transactional processes like data entry of risk and claim information, automated underwriting and claims settlement for simple, standard cases, communication letter generation etc. have a very high potential of automation.
Knowledge-based processes that require some intelligence like underwriting & claims decisions for medium complexity cases, policy change requests involving financials, renewal processing, coverage query resolution, can be partially automated, with limited intervention from generalist underwriters and claims adjusters.
Strategic processes, such as sales, underwriting, and claims decisions for large and complex risks, risk inspection, loss verification, which are intellectually more demanding are best to be done by specialist underwriters and claim adjusters.
Artificial Intelligence (AI) includes a broad set of cutting-edge technologies such as Machine Learning (ML), Deep Learning (DL), Object Character Recognition (OCR), Natural Language Processing (NLP) and so on, that coupled with RPA can enable robots to mimic human judgment, behavior, and rationale.
With AI, robots can learn from legacy and new data, they can observe how humans solve exceptions and learn from them to further optimize processes. While RPA is process-driven, AI is data-driven, when RPA robots are infused with AI technologies they become 'thinking' robots or cognitive robots and are able to perform reliable data-driven decisions across the enterprise.
When RPA robots can understand data and use AI to make decisions, organizations unlock new possibilities that transform the way they automate their business processes.
Use cases of AI-Powered RPA program
According to a 2019 Forrester Consulting report, 57% of executives say that RPA reduces manual errors and increases employee engagement, while 60% agree that RPA enables employees to focus on more strategic aspects of their positions.
Utilize online information to identify claim fraud patterns.
Identify up-sell and cross-sell opportunities based on customer interaction patterns.
Improve customer experience through AI bots with natural language processing capabilities to manage customer service interactions
Analyze sentiments, intent, and behavior to design customized insurance products
Speech analytics to understand customer perception for the brand
Improve efficiency by using machine learning methodologies to identify and repair process blockages
Use machine vision to assess the severity of damage to cars/properties etc., using real-time video footage.
Identify risk attributes associated with customers for accurate underwriting.
Market disruptions by robotic process automation in the insurance industry
51% of financial jobs are prone to be transformed by automation.
Automation in digital marketing campaigns will also see a rise. The system will automatically profile customers and identify their needs.
Operations such as policy servicing and reporting will be affected by automation with highly streamlined digital processes.
Back-office services will drop significantly with the sharpest FTE (Full-time Equivalent) shift and migration.
Roles will be created by the intelligent process automation in claims by leveraging technologies such as machine vision and optical character recognition to assist employees in resolving complex claim cases.
Employee-count in the IT and other support functions departments would decrease because of a standardized and automated process and the potential migration to automated cloud platforms and analytical tools. These drastic shifts will also lead to the creation of more fulfilling jobs in the transformed insurance landscape.
Underwriters and insurance agents of the future will use the tools that work with inputs provided by the cognitive system created by the intelligent process automation.
Insurance companies will need to upskill the different layers of the employee pyramid to re-deploy human resources into more complex, quality-controlled, judgment-intensive roles.
In a nutshell, during this time of enhanced digitization, insurance companies need to react faster to the changes in the market and customer behavior. It will help them reap the benefits that far surpass their competitors, who still utilize legacy systems.
You may already have worked with a partner to automate a few software or processes, but will they be able to handle a large-scale overhaul?
Select your automation partner that can match both your current and future needs.
Artivatic has helped many Insurers succeed and experience measurable business impact by offering business-critical solutions such as automation for sales, marketing, underwriting, to name some.
Reach out to us @ email@example.com to get a free demo.
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