Cloverleaf Analytics Makes BI More Accessible For Insurers By Launching Natural Language Processing, Chatbot, And Automatic Insights Capabilities

New features significantly reduce the complexity of quickly benefiting from insurance-centric BI

Cloverleaf Analytics (Cloverleaf), a leading purpose-built insurance business intelligence (BI) solution provider, announced natural language processing (NLP), chatbot, and automatic insights capabilities as new features in the Cloverleaf platform.

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“We have seen a strong increase in the number of small and mid-sized insurers that have turned to Cloverleaf in the last year, and we have innovated on behalf of insurers and the insured in launching these new features,” said Robert Clark, President of Cloverleaf Analytics. “By making it easier for insurance professionals at any level of a carrier to more efficiently glean the insights that are relevant to them, we are freeing up time and other resources to offer the insured a more intelligent and higher-quality customer experience.”

The new NLP capabilities enable users to ask natural insurance questions and obtain immediate answers that are visually represented on optimal graphs and charts. The NLP feature is based on insurance-specific intelligence that is not available in traditional horizontal BI platforms serving multiple industries. The new capabilities also eliminate the need for a business user to require assistance from technical teams to parse, analyze, and visualize insurance data. For example, a senior business leader can type in a simple question about what are the five top states for premium in a carrier and receive an instant answer by Cloverleaf understanding and presenting the best information in a graph or chart.

The chatbot capabilities enable a user to interact with the Cloverleaf solution like they would a data scientist. A user can obtain the information they need to do their job more effectively without writing or understanding technical query language. A user can type a desired data function like presenting the last six months of direct premium in addition to the information already present in a visualization like line of business and continuously see new visualizations immediately while making new text-based queries.

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The automatic insights feature provides statistical summaries and forecasting about insurance data from any visualization developed in the Cloverleaf platform. As an example, a user can have more text and visually-based insights regarding claims activities in Cloverleaf visualizations that showcase types of claims, frequency of claims, claims expenses, and the major causes of loss.

Clark added, “With these new features business and non-technical insurance users will be able to better understand how to improve claims processes, capitalize on opportunities for new products, and enhance risk management by benefiting from technologies that replicate having access to a highly-skilled data scientist.”

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