Intelligent automation in the insurance industry is used by companies to take care of huge piles of paperwork and makes claims processing seamless. Data entry is always involved in the underwriting claims processing business and there is a margin for human error and inaccuracies when employing manual labor. Streamlining mundane and repetitive tasks is becoming imperative for organizations who are striving to succeed and provide an excellent customer experience. In this post, we will cover the steps involved with claims processing along with an overview of the latest claim insurance automation trends.
Insurance claims processing follows a five step process that leads up to the filing and resolution of claims. Professionals need to prepare the required documents (invoices, receipts, proof of insurance claim ownership, etc.) and gather evidence of the damages incurred in order to get approved for the claim.
Here’s how it works:-
The first step is getting in touch with your broker and forwarding them the collected information. You need to give the details needed and present evidence which will support filing your claim. Once the broker receives this, he will follow up with a claims adjuster to initiate the investigation process
The claim investigation starts where the insurance claims adjuster looks into the matter and sees the extent of damages incurred. He/she will identify liable parties and assess how much coverage your insurance policy provides for the damages. This is the step where you can bring witnesses for investigation and get them to support you with additional evidence.
When the investigation takes place, the insurance policy gets reviewed. You will find out what won’t be covered by your policy and any deductibles you have to pay
The insurance adjuster may hire engineers, contractors, and appraisers to further examine the extent of the damage. Your adjuster may recommend a list of professionals to hire for making repairs which could help you save money during the claims filing process
After a thorough assessment is done, if your adjuster is convinced, he/she will process your insurance claim application and proceed with payments. The damaged items will be replaced and any repairs will be carried out too. You will be contacted again during the settlement of your claim. The time taken for processing your payments for the repairs or replacements will depend on a case-by-case basis on the level of severity.
Insurance claims automation process starts by incorporating data extraction technology for the review and analysis of documents used for filing claims. You can make the process go faster and speed up resolutions by transmitting information electronically via email and other online channels. The way to do this is by leveraging technology such as Robotic Process Automation (RPA), reducing data redundancy through intelligent document processing, and finally, updating legacy systems.
Companies are working on bypassing efficiency limitations and integrating both front-end and back-end office operations with claims insurance automaton workflows. From connecting people, teams, and processes seamlessly, the benefits of automation trends in the insurance industry cannot be understated. Here’s a list of the most popular claims insurance automation trends.
Investments in artificial intelligence were estimated to be valued at $47 billion USD in 2020 alone and AI technology is becoming commonplace when it comes to insurance claims processing. Consumers are looking for tailored solutions when they apply for insurance claims and AI makes it possible to intelligent extract data, analyze it, and make recommendations by reviewing user profiles and creating personalized experiences.
Insurance companies are responsible for ensuring data accuracy, reliability, and privacy when it comes to meeting client commitments. Claims processing goes through multiple layers of administrative, managerial, and functional processes and information is submitted in a variety of formats.
Robotic Process Automation uses automation tools and workflows which automatically extract data from insurance documents. It reduces the need for manual data entry, does membership/validation checks, and streamlines the adjudication process by streamlining application reviews during claims filing. RPA helps companies ensure legal compliance and make claims meet regulatory requirements as well.
Intelligent Process Automation is being used for classifying claim policies, annotating them, and reducing operating costs. Many insurers deal with millions of documents and unstructured data which means there’s enormous amounts of time spent in organizing, structuring, and reviewing them. Intelligent Process Automation collects insights from previous documents and makes machine learning models smarter since algorithms read documents just like humans do. It frees up time for employees, improves client response times, and streamlines knowledge capture processes.
Data entry tasks are labour intensive but IPA in insurance can be used for automating a bulk of the work and applies rule-based data extraction techniques. Where rules don’t apply, claims automation AI and IPA can help users read data intelligently and the technology can interpret a variety of data formats. IPA is also being used for underwriting, claims processing, new customer applications, generating reports with photos, and much more.
Automation in insurance claims processing is mostly rule-based and follows a structured approach of reading and processing information. From omnichannel customer engagement, enhancing revenue growth, improving business operations, and streamlining services, insurance companies are investing in claims automation processing tools for making their jobs easier and boosting customer satisfaction rates.
With the right technology in place, companies don’t have to worry about data privacy breaches and several automation trends in the industry are helping companies take care of it. Furthermore, claims automation processing software is designed to make insurance claims filing efficient and makes it easier to clean up and mine data. You can also collect insights from customer data and see emerging trends during claims processing, do data mining and collect insights from customer data.
If you’d like to use automated data extraction for your insurance claims processing, you can rely on a solution like Docsumo. Sign up for a free demo with us and see it in action today.
In today’s dynamic business world, filing and archiving official documents in the digital form makes it handy, and works wonders in the future or in unforeseen circumstances.
Optical Character Recognition (OCR) is the technology to convert an image of text into machine-readable text. It is the underlying technology for various data extraction solutions including Intelligent Document Processing. However, OCR is not smart enough to figure out the context in a document - it works simply by distinguishing text pixels from the background and finding a pattern. This limitation could cause inaccuracy in captured data that could directly impact the output of your data extraction model.
Accounts payable is a key financial function for any business. Corporations can have thousands of suppliers; even for relatively smaller businesses, the number of suppliers could be in hundreds. All the invoices they receive from these suppliers come in multiple formats, layouts, and templates - some semi-structured, some unstructured. Therefore, firms expend time and resources to capture invoice information through manual data entry and verification of accounts payable. Manual data entry is not feasible in the long run, definitely not on a large scale. Before we talk about how intelligent invoicing solves the problems associated with manual invoicing, let’s discuss the challenges in much detail.
As most of an organization's information is available in an unstructured format, processing it requires an automated system that can handle documents with minimum human interaction. OCR is one such technology, but its scope is limited as it requires human interaction and is highly dependent on the layout and structure of the document to be processed.These limitations are overcome by Intelligent Data Extraction.Using artificial intelligence, the Intelligent Data Extraction technology extracts data from documents and transforms it into useful information through the extraction process. It functions as a singular tool for extracting information from any type of document and aids in optimizing company operations.