Current Applications of RPA Implementation And AI in Insurance
RPA (Robotic Process Automation) has revolutionized the niche of insurance by automating several processes over the years. Deployed for use-cases in claims, processing, and underwriting in the insurance industry, RPA mitigates risks and speed up the long process of paperwork to ensure faster business decisions. Enterprise Insurance firms are inclined toward Artificial intelligence for the sole purpose of reducing the prolonged and redundant process of manual data entry.
The difference between AI and RPA is further discussed from the perspective of various forms of AI use with an RPA software document digitization. The use-cases for RPA are shown below.
Claims Processing can be a lengthy procedure manually and document-intensive. The collection of information from various sources such as claimants, police, hospitals, and other insurers in order to check whether to pay out a claim involves copying the data from one source to another. Data or incident needs to be translated to a digital record of the insurer. RPA facilitates speeding up of process in case of auto insurance, life insurance, health insurance, and they are verified by claim adjusters on various government websites.
RPA applications help in the underwriting of the sources. For example, verifying if the driver was insured previously, is considered beforehand for an auto insurance policy. The potential risk based on this data is calculated and later assessed.
CLUE: RPA can assess a particular CLUE report by logging and navigating into the system while translating information found on the Comprehensive Loss Underwriting Exchange (CLUE) database for checking claims filed by the customer with previous insurance carriers. Eligibility of policy, criminal records, convictions, arrests on charges and motor-vehicle-related accidents can be quickly sought and verified.
RPA Software Implementation:
Usual navigation to applicable internal and external data sources when altered would need RPA reprogrammed. Diagnosing the reason when the RPA software stops working may involve asking whether a change in the website or enterprise system was responsible or the change in the form that was intended to scrape data.
Protocols have to be set up in advance to minimize the downtime while reprogramming the software if not will affect the performance of multiple departments and their ability to execute jobs.
RPA system doesn’t stand alone. Legal systems, IT infrastructure, and other systems allow the process of RPA system to run effectively. Adapting to changes mostly allowed in the best interest of the insurance enterprise or the software.
Understanding the Difference Between RPA and AI:
RPA is not essentially artificial intelligence. It lacks the ability to learn and make strategic improvements or add strategic value to the enterprise. This limitation can be a drawback to an insurance carrier. On the other hand, AI and Machine Learning can adapt to new data sources, changes in enterprise, and thus wouldn’t need reprogramming. The functioning of AI is based on natural language processing (NLP), trained to find data, collect, copy on the form, which improves the scalability of the application.
Data Preparation for RPA and limitations of Document Digitization in Insurance:
Insurance claims are filed by staff manually into the digital claims form followed by RPA software filling the data at required places into the insurance carrier’s system. For several decades, document digitization has been available, and insurance enterprises have been witnessing the tremendous change in technology but with limitations of OCR.
If a handwritten text is illegible, then the traditional OCR software that matches a particular set of pixels to a text letter, programmed to “seeing” fails to translate it.
The resulting incorrect translation because of the “if-then” kind of software is a limitation to digitize specific types of forms. In such a case, an OCR solution procured for the company needs to be used by the staff to enter other forms manually.