Streamlining operations, increasing efficiency, reducing costs, and continuous product innovation have been standard operating procedures for insurance organizations for decades, but the pace has increased since insurance quoting went online.
Expertise in marketing, claims processing, and underwriting are no longer unique competitive advantages, and insurance companies are looking for new ways to operate. As a result of this trend, they are embracing AI, big data, and the cloud, and focusing more on automation for insurance, all to create and grow their competitive advantages.
Automation for insurance can start with a variety of processes but automating quote delivery is one of the lowest hanging fruit.
The first step of any automation project is to analyze the existing process to determine exactly what can be automated. It’s critical to get the insurance analysts involved from the very beginning. Not only do they hold the institutional memory for how things are done, but their experience leaves them full of ideas about how to do things better.
During this process, standardized criteria for each insurance policy and rate will need to be determined. Also, the various data sources required to implement automation for insurance need to be mapped out. They may include the CRM, the mainframe, and/or the cloud.
The key to automating quote delivery is using a business rules engine for insurance within a business process automation platform to allow for the creation of automated analysis and comparison of insurance data to streamline quote creation. Furthermore, automation for insurance using business rules reduces manual processes and eliminates errors while simultaneously accelerating quote creation.
The business rules engine is in use from the beginning of the quote process to the very end. Using a rules engine, the business analysts can author and maintain business rules. They can add or change products and process complex dynamic pricing requests in real time.
The business rules engine for insurance is used to define the various criteria necessary for determining the quote. If we’re using auto insurance as an example, it may range from initial qualifications like age, eyesight, and years of driving to the make, model, and frequency of usage. Also defined during this process are the systems from which the comparison data will be pulled, such as the CRM, the mainframe data files, or cloud-based data.
The customer-facing, dynamic form is created within the same business process automation platform, with specific formats predefined, automatically alerting the potential customer when the format isn’t followed. Once all the standardized data has been entered, the workflow containing the business rules engine for insurance kicks in.
If customers are approved, the workflow sends approval messages, further details about the quote, etc. If customers aren’t approved, the “alternate” workflow sends an update to the customer, clearly delineating the reasons for disapproval, such as the information was not correct, they haven’t been a licensed driver for long enough, etc.
The main benefit of quote automation for insurance is flexibility. As market conditions change, the business rules engine for insurance can be changed as well. Using a no-code business automation platform allows the changes to be made on the fly.