Intelligent process automation is changing how the insurance industry handles claims. Advanced automation solutions have impacted many industry sectors positively, and it is the case with the insurance sector as well. The adoption of intelligent automation solutions in the insurance sector is a response to the growing purchasing power and changing needs of the buyer. Although businesses are slowly getting onboard with digital transformation, there is still a greater necessity and scope for automation, especially in insurance.
Insurance is a heavily document-dependent sector that relies mostly on manpower to get work done. And the paperwork has only multiplied over the years. What has changed are consumer needs and the demand for products and services being dictated by the buyer rather than the seller. Complex document-based processes in insurance including claims management and reimbursements can take up a lot of time and manpower resources. Claimants looking to get any payouts or reimbursements for the expenses incurred usually have to wait for months before getting any form of relief. Medical claims processing is complex and long. There is a lot of data entry and document processing work required to process a single medical claims form. Also, medical claims handling means a lot of back-and-forth in paperwork and moving files across the department for validation and approvals.
Robotic Process Automation (RPA) has helped insurers mobilize operations to a certain degree, but this technology is limited in its ability to process a large variety of claims forms. RPA is programmed to process claims documents having a certain template structure.
The RPA software bots will know exactly where on a claims document to look for, say, a signature or the claims details and how to validate it, because it is programmed to follow a certain data capture and process automation logic for that particular document. This makes it very convenient to process a large number of claims forms of a similar format or structure, like say, forms from the same insurer or compensation fund agency.
RPA is not useful when it comes to processing a claims form with a format or structure that is different from the standard format for which the RPA bots have been programmed. The RPA software bots do not have the logic to process new claims forms, making them ineffective when dealing with document variability. What RPA lacks is the cognitive ability to process new claims forms.
A more suitable and apt solution would be Intelligent Process Automation (IPA). IPA or intelligent automation combines digital transformation technologies like business process automation, OCR/ICR recognition software, intelligent data capture, AI, machine learning, aling with robotic process automation.
“...data validation is another lengthy process that can involve a lot of back-and-forth between claims handlers and insurers, with the possibility of sifting through tons of paperwork and archived master data folders for cross-checking claims details. Claims processing involves a lot of participants including insurance agents, brokers, claims administrators and handlers, providers, medical practitioners, etc. Collecting and routing medical claims data between these participants for validation and verification, before re-entering the validated data in back-end systems and business applications add to the complexities of claims management…”
The cognitive solutions and powerful data capture software gives intelligent automation bots the capabilities to execute human-like actions to process complex unstructured and semi-structured documents. Intelligent automation has the potential to transform mission critical operations in insurance. The technology supplants skilled workers to accurately and quickly process medical claims forms.
Accelerating claims processing in this way lowers the inefficiencies that come with manual paperwork. Also, intelligent automation helps remove the common challenges that come in the way of servicing the customer in the best possible manner. These challenges are mostly due to manual errors that are common when doing mundane, repetitive work like data entry.
Streamlining document-dependent processes in insurance helps accelerate service delivery to the customer and ensure faster reimbursements.
Intelligent automation supplants human effort to handle complex documentation and data entry work, and enables businesses to easily scale operations.
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Most insurance processes rely on data, and this data, more often than not, comes in the form of unstructured or semi-structured documents. It takes a lot of time and human effort to extract relevant data from these documents and make it available for processes. Also, claims data can come from different channels including emails, fax, FTPs, post, scan, pdfs, customer service centres, etc. Gathering all the documents from these multiple sources, digitizing the documents, and presenting the documents in a format suitable for automatic document processing is difficult without an intelligent capture system.
Manual data entry can become highly complicated, given the myriad of claims details that need to be extracted from complex structured, semi-structured, and unstructured documents. Often, claim details include handwritten notes, foreign language text, beneficiary details, employee benefits information, and compensation requests that may come in highly unstructured document formats. Manually deciphering, translating, and transferring that content into readable material in a company’s database or claims management system for further business use is time-consuming, laborious, and error-prone.
Data validation is another lengthy process that can involve a lot of back-and-forth between claims handlers and insurers, with the possibility of sifting through tons of paperwork and archived master data folders for cross-checking claims details. Claims processing involves a lot of participants including insurance agents, brokers, claims administrators and handlers, providers, medical practitioners, etc. Collecting and routing medical claims data between these participants for validation and verification, before re-entering the validated data in back-end systems and business applications add to the complexities of claims management. Different insurers also have business rules unique to them, and if one is to automate the process, these rules must also be accommodated in the overall claims automation system.
RPA technology is context-based and template-based, making it difficult to process complicated claims forms with varying and unique claims literature that needs to be comprehended before attaching a specific workflow automation to process the data.
A claims processing software with its IPA technology, on the other hand, taps into the embedded ‘self-learning’ capabilities, derived from built-in AI and machine learning technologies. These cognitive powers give IPA bots the ability to process new claims documents, of varying structure or formats. There is no need for a skilled programmer to create a separate workflow automation logc to process every new claims document with a different format. The IPA bots simply emulate human actions performed to key-in claims details from a new document structure the first time. The bots then apply this learning to all subsequent forms having a similar structure as the new document, thereby adding to the capture and process automation logic.
Process automation technology helps insurers shift their agenda from document-based functions and focus more on servicing the claimant in the best possible manner.