The insurance industry has a history of rigidity that explains its efforts to blend consistency and tradition. However, insurance customers are increasingly becoming tech-savvy and digital natives. This trend is being majorly observed after the COVID-19 pandemic. Over the last couple of years, the customers’ expectations are continuously evolving and they are more inclined to get served digitally. Hence, the insurance domain has been taken with a digital transformation whirlwind. The many traditional, time-consuming insurance processes are undergoing a digital makeover. Quote generation is one of them. It involves several time-consuming steps that need to be performed manually.
The quote generation process is also grappled with manually handling the flow of information and calculations across several systems that can have human errors, and thus risks in compliance and tracking. The list of challenges doesn’t end here; it includes:
Challenges in Quote Generation
- No updated data is available: The spreadsheets and documents used to create and maintain price lists, contracts, and important data increase the chances of passing on the older versions of the data across systems. Basically, keeping a solid record of updated voluminous insurance data is challenging. This leads to miscalculations of prices that reduce profitability.
- Leads to erroneous output: The data seem to be decentralized in an insurance organization which increases the chances of errors. Wrong data entries, price discrepancies, and other blunders make the manual quote generation process more complex rather than creating a getaway to bring in new customers. These errors end up making customers pay for wrong pricing and increase client attrition.
- Never-ending quote generation process: Quote generation is a lengthy process that includes necessary reviews and approvals that add to the pain points of the quote generation process. Well, this is not all, too much back-and-forth communication raises potential conflicts in the process.
- Missed selling opportunities: Manual quote generation shifts the focus of sales professionals away from selling opportunities. These insurance experts are mostly seen correcting errors in miscalculated quotes and running for verification and approvals. This way they lose time that otherwise can be used to maximize the sales impact.
How Does Automation Transform The Quote Generation Process?
In the automated insurance quote generation process, technologies like WhatsApp and Email automation capture customers’ details. Next, RPA, OCR, ML, and Intelligent Document Processing Solution scan, verify, and process the digital documents of customers. Meanwhile, AI and Automation bots look for missing information. Lastly, Generative AI in insurance generate quotes and statements and renew policies or create new ones.