Five Characteristics of a Purpose-Built AI Solution for Commercial Insurance

Artificial Intelligence - April 24 2019

Artificial Intelligence solutions present commercial insurance brokers, carriers, and reinsurers with a huge opportunity to modernize and transform age-old processes, unlock business insights from data squirrelled away in data lakes, and focus on improving the customer experience.

However, investing in the right solution to accomplish these goals can be challenging. There are many general-purpose emerging technologies that include a host of viable features, however, they are often not designed to cater to the lexicon of insurance, the business logic, or unique workflows for commercial insurance-related use cases.

General-purpose or all-purpose solutions tend to require heavy customization and significant capital investment to make them seamlessly integrate with existing insurance-specific front office and back office systems and immense effort to design workflows that support the complexities of underwriting commercial insurance.

When investing in an AI solution for commercial insurance, organizations should consider selecting purpose-built solutions that cater to the business needs of insurance by including domain-specific knowledge, intelligent insurance-related workflows, and insurance lexicon to accelerate deployment, time to market and user adoption.

Purpose-built AI solutions for commercial insurance have the flexibility to scale across multiple lines of business to read millions of documents, integrate with existing document management, rating, and policy administration systems and provide the high accuracy levels demanded by risk-averse insurers.

For commercial insurance brokers, carriers, and reinsurers who seek to reap the vast benefits of deploying an AI solution, they should invest in a purpose-built AI solution for insurance that includes the following key characteristics.

Five Must-Have Characteristics:

1. Named Entity Recognition

Named Entity Recognition is the ability to identify data types such as a person, organization, or organizations, locations, quantities, monetary values, and percentages by applying classification techniques. Purpose-built artificial intelligence solutions for insurance include insurance-specific named entity recognition which can locate, identify, extract, and classify data such as premiums, limits, deductibles, types of coverage, city, state, country, loss run, statements of value, person names, organizations, locations, quantities, percentages, monetary values, etc. and understand the relationship. AI solutions designed for insurance that can extract more than 500 named entities enable insurers to automate and simplify data aggregation during the application intake, quote comparison and underwriting process. Significantly reducing the time human staff are spending on identifying and extracting data. AI solutions can read hundreds of times faster than humans and with greater accuracy. Saving insurers time and money.

2. Domain Knowledge

Purpose-built AI solutions for commercial insurance are built with insurance lexicon and workflows that align with the insurance value chain. They are commercial insurance specific and cater to specialized insurance uses cases in contrast to general-purpose or domain-independent knowledge.

3. Out-of-the-Box Intelligent Workflows

Purpose-built AI solutions for commercial insurance include pre-built and pre-designed workflows aligned with the Insurance Value Chain. Investing in a general-purpose AI solution can require a series of extensive customizations to design specific workflows to meet the needs of target uses cases. Whereas, purpose-built AI solutions for commercial insurance include pre-built and pre-designed workflows like quote-to-bind and submission prioritization to improve underwriting productivity, accelerating time to market and eliminating the need for additional capital investment for customizations.

4. Trained Insurance-Specific Data Models

With purpose-built AI solutions for insurance that are based on Natural Language Processing and Machine Learning, they can identify, categorize and analyze information very fast – in milliseconds. Using supervised and unsupervised machine learning and model reinforcement learning, the machine continues to learn over time, getting better and better. A purpose-built AI solution for insurance is trained to recognize insurance specific terms and compare unstructured data across insurance specific documents such as policies, endorsements, applications, submissions, binders and quotes.

5. Mapping to Insurance Standards

Purpose-built AI solutions for insurance recognize and support industry standards like ACORD and CSIO enabling commercial insurance carriers to easily map unstructured data into standardized formats for integration and consumption with back office systems.

Trying to fit a square peg in a round hole doesn’t make much sense. Nor does it make good business sense for commercial insurers to invest in general-purpose AI solutions that require huge investments in time, capital expense and extensive customization to make them work effectively within the commercial Insurance Value Chain.

Purpose-built AI solutions designed for commercial insurance enable brokers, carriers and reinsurers to augment their workforce with digital workers to automate and streamline high volume, repetitive tasks freeing up their skilled knowledge workers to deepen customer relationships and deliver a better customer experience.

Interested in learning more?

Schedule a product demo of Chisel’s AI Solution for Commercial Insurance Brokers, Carriers and Reinsurers.

Request a Demo

Additional Resources

Novarica’s Jeff Goldberg outlines the advantages of purpose-built solutions:

Novarica research report on Purpose-Built AI Solutions for Insurers:

Browse different topics

Recent Posts