Aureus Analytics implemented PULSE to help Aegon Life improve their overall NPS process.
Learn how Aureus implemented predictive analytics to help predict the probability of a claim being fraudulent.
Learn how CRUX improved the persistence score for a mid-sized life insurer by 2 - 3%.
The key challenge for Tata AIA Life was to bring together all customer feedback and reduce the time required to analyze NPS feedback.
This client had been suffering from claims fraud which has impacted their revenues. Additionally, they wanted to make cross-selling more accurate and effective.
Aureus helped this insurer make accurate predictions to target the potential lapsed policy base.
This client was trying to reinstate customers whose policy renewals had lapsed.
This Life insurer was have difficulty identifying the right product for the right customer.
Aureus helped this major insurer develop a better cross-sell model.
Aureus helped this insurance carrier improve their persistency score.
Aureus implemented predictive models to identify customers who were at risk of non-renewal.
This client needed help identifying policies that may lead to an early claim.
Policyholder or customer retention is a direct reflection of loyalty and customer experience.
AI technologies can quickly identify policies that need to be reviewed to identify customers who are at risk for non-renewal.
See how household analytics can help you understand the portfolio dynamics at the household level.
Sentiment and predictive analytics can help in determining cross-sell and upsell opportunities.
Join Jackie Vergne and Frank Sentner of
Join Jackie Vergne and Kurt Thoennessen from Ericson Insurance Advisors to learn how Sentiment Analytics can help your organization pro-actively identify issues so they can be resolved to improve the customer experience of your policyholders.
Learn how data stream-based integration can easily bring all of your different datasets together.
Learn about some of the business factors that influence
the main stages of model development.