Many industries are seeing incredible growth due to new automation technology and shifting customer expectations. Unfortunately, the insurance industry has been slower to benefit from these breakthroughs. Today we have “born-in-tech” insurance companies that intelligently and efficiently integrate automation and intelligent technologies into their operational and administrative processes. In this blog, we will be discussing in detail intelligent automation for Insurance business. It is one of the most important aspects of incorporating technology into business operations is automating processes that will save you time and effort while drastically lowering the risk of error. Furthermore, by offering customers convenient solutions, it improves the customer experience.
Automation is the only viable option for ensuring that your insurance company achieves its full potential. Unfortunately, traditional robotic process automation (RPA) and optical character recognition (OCR) achieved minimal success in the insurance industry. Intelligent Automation (IA) can help these businesses adapt their operations to meet rising customer needs and compete more effectively.
Using a combination of digitalization, RPA, and artificial intelligence/machine learning, IA can provide solutions to complex problems in insurance processing by automating not just a single procedure but an entire business function.
Implementation of Intelligent Automation in the Insurance Industry
Use Case #1: Claim Processing in Insurance Business
Insurance firms need to be quick and efficient in processing claims to be successful. But it’s typically a laborious manual process that frustrates both insurers and customers. Claim processing typically takes many days because insurance agents must acquire and verify information from various sources. In addition, human errors, such as incorrect financial data or consumer information, may cause further delays. As a result, there might be customer attrition and financial and reputational damage to the company. The claims processing can be sped up by combining Intelligent Automation with human expertise. Automating claims intake, assessment, and eventually claims settlement, minimizes friction and costs.
For example, when Property & Casualty insurers use AI-powered RPA to process the First Notice of Loss request, an RPA bot would extract the information and enter it into the claims system. Next, a cognitive bot would check the claim’s information and label it as acceptable for payment if it was complete. If data is lacking, the task is sent to an agent to complete, and the bot “learns” from how the agent handles the issue. Finally, when the agent returns the claim to the workflow, the bot automatically submits the verified payment request.
Intelligent software robots can extract meaningful data from unstructured documents received via email, fax, mail, or other sources and enter it into the appropriate systems. These bots can also triage claims using rules, sending them to different workflows depending on their features. These processes could use machine learning or intelligent analytics to reduce claim processing time. Automation can do high-volume, repetitive tasks around the clock, seven days a week, allowing claims professionals to focus on more complex analysis and higher-value work.
Insurers can save costs, eliminate errors, avoid fraud, and improve customer satisfaction by automating the claims FNOL process.
With respect to Paper Claims Intake, the Intelligent Automation system automatically receives scanned paper claims, classifies documents into types, extracts key data points, and pushes the extracted data into core claims systems, thereby automating a previously tedious, low-value manual task that qualified employees took hours to complete.
Automated claims processing cuts the amount of manual work required by 80% and improves accuracy by 50%, allowing businesses to handle twice as many claims with the same employees.
Use Case #2: Policy Management in Insurance Business
Intelligent automation has already taken center stage in policy administration for various businesses, and the insurance industry is no exception. Insurance providers can automate their policy management and take care of policy issuance and modifications to reduce costs and human effort.
Pre-underwriting checks have already been completed at the policy issue, and an underwriting decision has already been made. However, any new policy issued by an insurance company must be conveyed to the customer immediately, and the new information must also be updated in the company’s internal systems. It’s a time-consuming task that’s prone to errors when done manually. Using Intelligent automation(IA) to streamline insurance policy issuance will save time and speed up the internal operations of an insurance company.
Additionally, IA can be used to allow current policyholders to submit various requests for updating their information. For example, policyholders typically submit update requests to change/update their address, bank account information, etc. Machine learning can automate these update requests by extracting inbound changes from voice transcripts, emails, faxes, and other sources and making the necessary changes in the relevant internal systems.
Document-intensive tasks are every day in the most complicated processes of policy administration. Although it is not easy to set up document-intensive operations with automation capabilities, especially in insurance industries, business operations become significantly easier and faster once it’s done. With the correct tools, even the most complex activities can be automated, such as loss run reports and analysis of the statement of value reports.
Take, for example, the Endorsement Request Intake and Routing process. Intelligent Automation with Machine Learning identifies the nature of the change request, classifies supporting documents into types, and extracts key data points from all relevant documents after receiving inbound requests from various sources. Then, the bots convert this data into structured data, which can subsequently be used to update and alter policy systems.
Use Case #3: Intelligent Automation for Effective Underwriting in Insurance
Underwriting is another essential element of the insurance industry that is frequently evaluated for automation. Underwriting is when the insurer evaluates if the risk associated with a customer, which varies based on the type of insurance, is acceptable and, considering several factors, arrives at an eligible coverage amount. Automation makes gathering and analyzing information for underwriting simple. The entire procedure might take weeks. Data gathering, internal system updates, loss runs assessment, customer claims history analysis, and other operations will be considerably sped up by implementing intelligent solutions to automate insurance underwriting. For example, Bots can retrieve underwriting documents from emails, categorize and retrieve the required information, cross-reference external data enrichment sources for additional data, and validate the application for completeness using custom business rules, automating more than 70% of the manual work involved in the New Submissions Intake process, reducing the time taken to process per submission by 75%. In addition, automation solutions that integrate RPA, machine learning, and human-in-the-loop to “assist” AI can reduce underwriting errors to nearly 0%.
Use Case #4: Regulatory Compliance in Insurance Industry
The insurance industry may have the most extensive and complicated regulatory requirements. Keeping track of all the amendments to these regulations becomes increasingly tricky with so many compliances to follow. Insurers frequently have to rearrange their business processes to respond to these changes.
There is no way around these standards and compliances because breaking them might cause irrevocable consequences, potentially harming a company’s operations and even resulting in financial losses. In addition, incorporating the compliance amendments into the process through humans has the risk of errors. But with Intelligent Automation in place, the process changes become more reliable because it’s an AI-assisted system with a human in the loop. It even maintains an extensive activity log for future reference.
The data maintained by the automated system allows you to track your regulatory compliances in real-time through internal assessments, which allows insurance companies to be ready for external audits. Validation of customer data, compliance checking, client research, and screening are all critical compliance tasks that automation can assist with. In addition, regulatory reports and alerts can also be generated using automation.
Use Case #5: Seamless Collection & Aggregation of Data:
Data is a valuable commodity in today’s digital economy if you know how to leverage it for your success. As a result, to fully utilize every accessible data point, it is critical to organize information in the most meaningful way.
Insurance businesses deal with tedious tasks like data collection and data entry. These tasks are time-consuming, but they are also prone to errors. Insurers can benefit from Intelligent Automation in the following ways.
- Without any human interaction, capture leads from multiple sources such as websites, third-party aggregators, social media, etc.
- Data is automatically imported and managed under one roof.
- Distribute leads depending on product type, preferred language, region, and other variables.
- Prioritize data using lead and quality scores to reduce turnaround time.
- To construct a complete prospect profile, use activity tracking to identify prospect intent and have relevant prospect interactions.
Use Case #6: Intelligent Automation for Processing Self-Serve Applications
Customer onboarding is frequently a time-consuming process. Before a policy is issued, it must pass various verifications and validations. Traditional onboarding processes carry several hazards, including delays, interminable documentation, and a vulnerability due to human errors.
To address this, intelligent automation in digital workers will be required. For example, intelligent Optical Character Recognition (iOCR) can recognize the text on paper forms and enter the information into numerous systems. Self-serve forms can also be used as an alternative. Customers can fill out self-service forms on the web or through mobile apps before having their information confirmed by a digital worker.
The use cases that the insurance industry offers for automation are limitless, and so is Intelligent Automation’s potential to help tremendous growth in the industry. Most processes can be automated entirely or partly, resulting in lower operating costs, higher profit margins, and better employee and customer satisfaction.
How can Payoda help?
The rate of digital transformation in the insurance industry is intensifying. Insurers are eager for change and are assessing which technologies will have the most influence on their operations in the quickest period possible. At Payoda, we believe that intelligent automation is a critical tool for Insurers. We go well beyond simply removing repetitive procedures by combining process mining, artificial intelligence, and other advanced digital technologies. This means faster reaction times, cheaper operational expenses, and increased productivity for insurers.
Want to know more about how intelligent automation can help your business in specific? Then, Why wait? Consult our technology experts.