Generative AI and Insurance – Lessons Learned

David Moorhead has over 30 plus years of insurance technology experience focused on data and analytics across all personal and commercial lines of business. David has led numerous insurance data transformations with a focus on data management operating models, migration, legacy remediation, operational reporting and advanced analytics.David is aligned to EY Insurance AI and Analytics practice and delivered numerous data management, data architecture, reporting and enterprise data warehouse solutions for all sizes o Property and Causality insurers. 

Recent project experience:

David has executed data strategy and roadmaps, analytics innovation labs, and performance management delivery for Underwriting, Actuarial, Product Management,Claims and Policy Operations, and Agent Compensation. '

David created EY’s IntAIke accelerator that leverages traditional AI and Generative AI to automate data ingestion for both Specialty, Reinsurers and Carriers.  

David has developed advanced analytics for claims focused on severity monitoring and execution, as well as fraud propensity scoring. Analytics were imbedded intothe coresystem for immediate adjuster assignment and automated workflow to not only gain efficiencies within claims operations but improve outcomes. 

 Develop a workers’ compensation data management solutions with key performance metrics to improve outcomes for claimants while improving vendor management and case reserve accuracy. 

 As an insurance leader, David develops P&C specific assets on the Insurance Insights Platform. Currently he is expanding insurance analytics use cases for GenAI ,as well as extending our supporting Databricks and Snowflake offerings.

Ryan is a Managing Director in the Ernst Young’s FinancialServices Risk Management Advisory practice. He has over 16 years of experiencein the financial services industry providing advisory services to banking andcapital markets, asset management, and insurance clients.

Ryan has a BS in Finance and Accounting from GeorgetownUniversity and an MBA from Columbia Business School Ryan holds the CharteredFinancial Analyst ( designation and is a Certified Public Accountant in thestate of New York.  Ryan frequently presents at industry conferencesand forums on model risk management topics including events hosted by IIF,PRIMA, Risk.net, and others.

Recent project experience:

Assisted numerous banks and insurance companies in the design oftheir AI/ML governance frameworkincluding designed of AI/ML policy, AI/ML definition, risk tiering, and rolesand responsibilities across,data, technology, and risk. 

Assisted multiple leading global financial institutions in enhancing model risk management frameworks to incorporate AI/ML models including updates to model identification and tiering, standards and procedures for AI/ML model development, design of model development and validation documentation templates, and connectivity between MRM and other risk stripes. 

Assisted leading global financial institution in developing its model risk framework including enhancing model risk policies, procedures, standards and development and validation templates to be consistent with regulator guidance including specific considerations for AI/ML models In addition, subsequently led team in enhancing2 000 model validations. Assisted leading global financial institution in designing target state model risk management framework including performing a gap assessment of existing policies and procedures and drafting materials to articulate target state to bank senior management and regulators.