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

  1. 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.
  2. 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.
  3. 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.
  4. 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.

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What Benefits Does Automated Quote Generation Bring to Insurers?

To maximize sales impact insurance businesses should focus on practices that increase profits and promote growth. Automated quote generation replaces the manual cumbersome quote generation and makes room for sales opportunities. Hyperautomation Technologies like AI and Automation, Optical Character Recognition, Machine Learning, Intelligent Document Processing, etc., wipe out the aforementioned challenges in the process, resulting in the following benefits:

  1. Paperless quote generation:

    Technologies like AI and Automation and OCR eliminate any kind of manual paperwork and enable insurers to swiftly process and maintain digital quote generation documents for further verification or approvals. This results in considerable savings in time and cost.

  2. WhatsApp automation is here to help:

    Providing general insurance to the customer is a time-consuming task as it includes collecting customer information in the form of physical document copies and then sharing quotes as per the system. To avoid this time delay, an AI-powered WhatsApp Chatbot and email bots have been introduced by insurance companies. These bots are trained to process customer information and generate quotes. Field service agents fill customer information in the mobile app which is connected to these bots to process and provide quotes.

  3. AI and Automation for effective data processing and customer experience:

    The synergy of AI and Automation guides and trains the AI chatbot integrated into the process to gather the required information to generate insurance quotes. These chatbots can handle customer queries and provide customized resolutions without any human intervention.

  4. Reduced operational expense:

    Technologies like RPA, OCR, and ML look after the end-to-end automated lead generation process. This frees up employees to focus on more productive and sales-oriented tasks. This helps to optimize sales operations and bring out the best in the quote generation team.

  5. Lead generation through enhanced data analytics:

    Technologies like ChatGPT and Communication Mining, take a deep dive into customer interactions and present data insights that can be used to evaluate leads and present them the customized quotes as per their requirements.

Summing Up

The conventional manual quote generation process slows down the process and ceases the productivity of the quote generation team. Streamlining quote generation with hyperautomation technologies saves cost and effort and also provides a competitive edge leading to increased sales and enhanced customer experience.

Are you looking to make your quoting process seamless with hyperautomation?
Get in touch with AutoamtionEdge today! We will be happy to help you!