Insurance payers and providers are now caught in a unique market and business dynamic with goals of driving new revenue, avoiding internal waste & fraud, while trying to maximize customer satisfaction. This set of unique challenges includes all areas of the business from sales, marketing, and policy underwriting, to the investigations of claims fraud and payments. As insurance companies find new revenue and optimize for better profits, fraud & loss contribute to higher premiums. All insurance lines of business: Healthcare, PNC, Auto, Life and others are utilizing the combination of Machine Learning, Graph & Visualizations to drive revenue, cut costs, provide real-time analytics, and prevent and intervene strategies.
The focus of this webinar is to identify how Machine Learning, Visualizations and new technology like Graph can directly increase the accuracy and shorten process time for ‘Human in the Loop’. This event is designed as a 'Speed Dating' format with a focus on key topics for under 15 minutes in order to maximize the insights. During this online meetup, you'll learn from our experts on how Expero and TigerGraph can unlock the potential in your organization. We will feature unique Expero and TigerGraph Machine Learning, Visualization, and Graph technology lightning talks, followed by a short Q&A session.
Key Learning Topics:
- What Are the Key Challenges in Payer and Provider insurance - Illustrate why Visualization, ML & Graph still utilize ‘human in the loop’ for maximum accuracy and productivity
- Methods to reduce false positives by 10% - Review ML combination techniques with Graph and other platforms to reduce false positive signals
- Increase accuracy of current ML systems - Strengthen and increase accuracy for Cross Sell, Churn prevention, Fraud identification with combinations of technique and technologies
- Creation of based ‘data products’ for Preventive & Predictive analytics - Access to different roles from customer success, new sales, fraud prevention and others
- Use of Visualization for ‘Explainable’ ML - Show practical uses and methods for fraud identification, complex dependency and case management
Session 1 (12 min): Why & How Graph, ML and Visualizations are Game Changers for insurance lines of business: Healthcare, PNC, Auto, Life and others
Session 2 (12 min): Use Visualizations to Identify Human Interaction for Insurance - 'The Art of the Possible' Fraud Workflow Demonstrations, Management, Investigations, ML, and Data Practitioner Views
Session 3 (12 min): Details on How Graph & ML Improve Intelligent, Predictive Forecasting and Active Scenario Analysis
Session 4 (12 min): Show How TigerGraph Combined with ML approaches Insurance business dilemmas with connected data in real-time
Session 5 (5 min): Open Q&A