FOCUS OF WEBINAR
All lines of insurance sales brokers and captive agents are under increasing scrutiny and regulations while simultaneously being asked to increase sales and maximize their current books of business. Industry sectors of P&C, auto, life and annuities are looking for systems that enable real time decision making on key predictors for channel sales health and potential outcomes for the end customer. This has given rise to a new function known as ‘Know Your Customers - Customer’ or (KYC-C). This unique functionality in C360 is able to spot historical trends, customer satisfaction, and also dissatisfaction. The primary goals of using these ML driven systems are to boost new revenue, avoid cost and risk, and at the same time maximize customer satisfaction. These goals pose a unique set of challenges to all areas of the business - from sales, marketing, and policy underwriting to the investigations of claims fraud and payments. P&C, auto, life and annuities and other sectors are utilizing the combination of Machine Learning, Graph & Visualization to drive more revenue, cut costs and to obtain actionable real-time analytics, which aid in preventing churn and devising interventional strategies.
The focus of this webinar is to identify how Machine Learning, Visualization and new technology like Graph can directly increase the accuracy of and shorten process time for ‘Human in the Loop.’ This event is designed in a speed dating format, focusing on key topics for under 15 minutes, in order to maximize the insights. During this online meetup, you'll learn from our experts how Expero can unlock the potential in your organization. We will feature unique Expero business and ML & Visualization technology lightning talks, followed by a short Q&A session.
Key Learning Topics:
- What Are the Key Challenges in KYC-C and C360 in Insurance - Illustrate how Visualization, ML & Graph can help you increase profit, reduce risk and lower costs for maximum accuracy and productivity for customer acquisition, retention and growth
- Methods to reduce churn by 10% - Review ML customer journey analytic techniques with Graph and other platforms to reduce churn signals and proactively intervene
- Increase accuracy of current ML systems - Strengthen and increase system accuracy for Cross Sell, Churn prevention, and connection to Fraud identification with combinations of techniques and technologies
- Creation of Preventive & Predictive analytics - Maximize sales, marketing and new media with predictive outcomes and cross channel capabilities
- Use of Visualization for ‘Explainable’ ML - Show practical uses and methods for root cause analytics to visualize better outcomes in real time
