Cloverleaf Analytics says it has embraced artificial intelligence (AI) and machine learning analytics, adding these features to its platform to enable insurers to proactively predict new risks and products with appropriate pricing.

Texas-based Cloverleaf has launched a new Insurance Intelligence platform which it says helps create more flexible, modern insurance products, and positions insurers for stronger growth.

Executive VP Thomas Chesbrough says deploying AI and machine learning amps up the benefits derived to a much higher level.

“Think of it as being at the power of 10 times,” he said. “Machine learning models reduce information that identify things we would have never seen and provides much more granular and in-depth detail.

“When we augment that with third-party data ... that information becomes very powerful – a level at the power of ten in the value it can produce,” he said.

Using AI and 28+ machine learning libraries, Cloverleaf says its new quoting module potentially improves profitability and revenue of every insurance transaction, finding geographic and demographic “hot spots” for quoting.

The new module analyses the number and frequency of quotes to determine the optimal offer while minimising the number of quotes issued.

“We have expanded our platform … leveraging insights from actuaries and data scientists to our latest AI/machine learning, advanced analytics, and data security capabilities,” President Robert Clark said.

Cloverleaf has also migrated its platform to Snowflake, enabling use of its structured insurance data and data of any format, spanning different cloud platforms and regions accessing 1100 data sets from over 240 providers.

Cloverleaf has also introduced online courses, instructor-led classes, a video library and community forum.