This client was looking to provide better customer-focused service by having one single view of the customer's journey.
This client wanted to use predictive analytics at the time of policy proposal submission to identify the likelihood of an early life claim.
Our client wanted to know which of their agents would likely generate a new policy in the near future, as well as improve their agent's productivity.
Enhance revenue growth opportunities with existing customers through effective cross-selling.
In this case study our client was struggling to centralize their data across the enterprise to enable a complete view of the sentiment of every single customer.
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.
It was crucial for this insurer to have an accurate understanding of their customers' needs.
This client needed help identifying early life claims.
This client increased their efficiency by improving the percentage of successful agent candidates.
Our client was looking for a way to improve the underwriting decision process and evaluation of proposals.
This client needed an early warning on future surrenders of Life claims.
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
Learn how an AI-enabled single view of the customer can help insurers understand how customers are feeling today to predict the next best action.
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.
Join Jackie Vergne and Steve Mateer from Pitney Bowes to learn how data enrichment can further extend the capabilities of household analytics for insurers, agents, and brokers.
Join Aureus Analytic's Dr. Nilesh Karnik and Jackie Vergne as they review a customer case study where the life cycle of two predictive models were developed for improving policyholder retention.
Join Ewelina (Evie) Mroczek, AVP, Product and Market Research at Lincoln Financial Group and Jackie Vergne from Aureus Analytics as they discuss how new technologies such as voice data analytics can help insurers learn more about their book of business and be applied to developing new products or updating existing ones.
Join Mark Stender, President of Intellagents and Jackie Vergne from Aureus Analytics, as they discuss how, when done correctly, data sharing can be an enabler as opposed to an inhibitor for evaluating and adopting new cloud-based technologies and solutions.
Understanding the sentiment of your customer is not always easy. Customer surveys can provide only so much information. You need to collect implicit feedback as well as explicit feedback. Aureus Analytic's SentiMeter® can help you do this.
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.
View this Masterclass in which Dr. Karnik will explore the applications of artificial intelligence for the non-technical business user. Upon laying the foundation, Dr. Karnik will focus on examples of actual implementations of AI applications that are in production today, followed by best practices for developing and maintaining practical applications in the insurance industry.