Job Title: Chief Data & Analytics Officer
Company: Employer's Insurance
Experienced leader of strategy development and innovation across a wide range of problems.Currently focused on advising C-suite executives in the use of data and analytics to improve the quality and efficiency of business decisions and creating game-changing business opportunities that leverage data and emerging technologies.
Very broad knowledge base and extensive experience in leading cross-functional, multi-disciplinary initiatives that address business problems in a holistic manner.
Significant success in formulating, obtaining senior leadership support for, and implementing forward-looking plans and strategies that anticipate and incorporate the rapid pace of technological and societal change.
Define the steps needed to begin a robust customer data management strategy. Evaluate best practices in aligning your end-to-end customer information processes, from collection through to analysis. Contextualizing the right data sets to acquire to serve your business objectives. Establishing the right Data Governance procedures to ensure compliant, secure and ethical use of customer data…. Read more.
Data-enabled startups and tech companies are moving into the space, is Big Data the answer for insurance? Understanding the products that customers want and providing a seamless experience to improve retention. Focusing on customer satisfaction as a key indicator of loyalty and driving product development in this way.
Many insurers are aware that data should be put to good use, processed and interpreted intelligently, but how can insurer’s align their strategy to optimize risk? Experiences in contextualizing data for risk management and market segmentation including claims process digitization insights. Leveraging data and analytics for risk mitigation, impact of predictive risk models and improving… Read more.
From claims to underwriting, where is machine learning most impactful? Defining the steps needed to usher in the age of digital normalization. Leveraging machine learning to reduce customer churn, turn-around times, lower costs and improve productivity.
Understand the potential of data science in improving claims process efficiency by shortening claims cycles and intervening at key decision points. Impact of machine learning, automation and AI on optimizing claims-decision making and likelihood. Assessing the power of data science in better minimizing the impact of macro-pressures on claims and maximizing reserve management. What customer… Read more.