Yes, would be the astounding reply to this question. But is it possible to live up to such a tall claim? Insurance industry is undoubtedly one of the most document intensive, and error prone industries in the world. With increasing customer base, insurance providers need to double up and make sure that they don’t err and maintain high standards of customer satisfaction.
The first step in ensuring a hassle-free claims process is to adhere to a bottom-up approach and confirm that the information that is fed into the system is validated and error free. This can involve multiple challenges like signature detection & verification, handwritten text recognition, invoice processing etc which can be managed smoothly with sophisticated Intelligent Document Processing (IDP).
Research indicates that by 2024, over 60% of insurance carriers will adopt some degree of automation to ensure smooth claims processing.s
Automation, or rather Intelligent Process Automation (IPA) that harnesses both Artificial Intelligence (AI) and Robotic Process Automation (RPA) can solve the challenges of insurance document and claim processing by huge volumes of unstructured documents and content in a fraction of the time compared to manual effort. But the key to a successful intelligent automation initiative lies in choosing the right use case.
Let’s take a closer look at feasible use cases.
Claims Processing
Processing claims in a swift and accurate manner is imperative to a competitive edge. Despite this, it is most often a time-consuming, highly manual process that is taxing for both insurance agents as well as the customer. Typically claims processing can take up to a few days to complete because of agents having to verify the credibility of data from multiple sources, such as:
- Medical certificates and reports for health insurance or life insurance claims.
- Photos of damaged baggage and flight boarding passes for travel loss claims.
- Police reports, drivers’ license, and vehicle damage photos in case of an auto claim.
Such processes are highly prone to human error resulting in mismatched data or inaccurate details. By implementing an Intelligent Process Automation solution for claims processing workflow that encompasses claims intake, assessment as well as claims settlement you can eliminate friction, errors and optimize cost. By automating claims processing you can eliminate 80% of manual work as well time taken to do so by 50%.
Policy Management
Another common tedious procedure that insurance companies must deal with is the entire spectrum of policy management that entails issuing policies and their corresponding updates. When issuing new policies pre-underwriting checks must be completed along with several underwriting decisions. Once completed the policy must be issued which means a substantial amount of information has to be updated in internal systems and communicated to customers.
These are document heavy processes that can benefit from the intervention of IPA – AI can automate the processing of unstructured documents while RPA takes care of the feeding information downstream into internal systems and sending updates to customers.
Such solutions can also automate processing of loss run reports, analysis of the statement of value reports, communication explanations of evidence of insurability to customers and other such processes.
Regulatory Compliance
Insurance companies have a long list of regulations that they must comply with. Whenever there are amendments to these regulations it forces insurance providers to reorganize their processes to adapt.
Intelligent Data Processing in the Insurance sector can play a critical role in assisting agents when it comes to processes such as these, because it saves employees from having to go through legions of repetitive, data-intensive manual operations. When your processes are automated using AI & RPA capabilities it can save you from errors and ensure high accuracy of data.
With accurate data you can monitor regulatory compliance in real time with internal reviews and be better prepared in the event of an external audit.
Underwriting
Underwriting involves gathering and analysing information from several disparate sources to determine and mitigate the risks that might be involved with said policy.
- Health risk- When an applicant is a smoker the mortality charges and therefore premiums are expected to go up.
- Financial Limits- If the net worth of an applicant is set at $X then their insurance coverage cannot exceed $10X.
- Duplicate Policies- Does the applicant have a prior policy under their name in place already?
- An applicant credit rating is important as it might be capped by previous agencies.
Some examples of IPA-driven automations for insurance could be:
- Name Screening
- Compliance Checking
- Client Research and Validation of Customer Data
- Customer Data Security Operations
- Regulatory Reports
By identifying the right use cases and automating them, Insurance carriers can create streamlined and efficient workflows for hassle free claim-processing and other insurance linked processes to reduce the two most important components of any business- Time and Cost.
If you are interested in exploring other aspects of IPA that can benefit your enterprise, you can read about Financial Risk Management with Intelligent Automation Alternatively, you can also read Streamlining Mortgage Processing, Banking & Financial Services with Intelligent Automation.
If you’re interested in exploring Intelligent Automation to enhance your firm’s claims processing, Rapid Acceleration Partners would be glad to help. Our next-gen, AI-powered content intelligence platform RAPFlow enables full lifecycle AI orchestration on a single platform. When used in tandem with our RPA tool RAPBot, it provides end-to-end workflow automation capabilities that can be deployed in just weeks. You can even build your own use case and the platform can easily integrate with your existing systems. Book a demo to get a more detailed understanding of how our products can transform your business.
