Anshul Kaushik

• Lead end-to-end delivery of AI and transformation programs for Fortune 500 insurance clients, managing an annual portfolio exceeding $14 million.
• Advise C-suite executives on AI strategy, governance, and business value realization—translating innovation into operational impact across underwriting, claims, and policy administration.
• Head EY’s Data Migration & Conversion (DMC) Studio, integrating AI tools such as Intelligent Data Mapper, Document Analyzer, and Cycle-Up Calculator to accelerate modernization by over 30%.
• Oversee the design and implementation of GenAI solutions, including retrieval-augmented generation (RAG), and agentic AI assistants for underwriting and risk assessment.
• Drive cross-functional collaboration between data scientists, engineers, and business analysts to ensure scalable, compliant, and high-quality AI solutions.
• Develop AI governance frameworks, ensuring transparency, fairness, and regulatory compliance in insurance AI deployments.
• Support presales, proposals, and executive client briefings—positioning EY as a strategic AI partner across the insurance value chain.

• Led system conversion initiatives for multi-line Life Product Policy Administration rollouts.

Delivered detailed business and technical specifications, data mappings, and architecture documentation to enable platform integration.
• Coordinated across product, engineering, and business teams to ensure seamless end-to-end transformation delivery.

• Led enterprise-scale data transformation and policy administration modernization initiatives across Life, Group, Retail, and Long-Term Care insurance products for U.S.-based carriers.
• Designed and delivered the full data conversion lifecycle—including data profiling, mapping, cleansing, transformation, validation, ETL development, and user acceptance testing—ensuring high data integrity and seamless business migration.
• Architected data modernization strategies and target-state data architectures, aligning legacy systems with scalable, cloud-ready platforms capable of supporting analytics, automation, and future AI deployments.
• Conducted deep data profiling and quality assessments using SQL and proprietary tools to uncover data anomalies, lineage gaps, and transformation risks; implemented cleansing routines that reduced exceptions by over 40%.
• Built data governance and reconciliation frameworks to ensure financial accuracy, regulatory compliance, and standardized reporting across high-volume policy, claims, and underwriting data.
• Developed data dictionaries, refined data models, and improved metadata management, enabling consistency and reduction of downstream processing errors.
• Identified opportunities for data reuse, consolidation, and rationalization, streamlining legacy data assets, and reducing operational overhead.
• Collaborated with sales and pursuit teams to shape data-driven solution proposals, leveraging domain depth, modernization expertise, and technology accelerators to convert strategic prospects into clients.
• Evaluated conversion execution plans with client partners, identifying performance, scalability, and schedule optimization opportunities using data insights and automation techniques.

• Created a new end-to-end on-line user experience and underwriting model reducing the
  time of a customer purchase from weeks to minutes, including the electronic delivery.
• Developed a customer-centric product with single session purchase (SSP) capability, implemented with an industry record of policies sold in under 4 minutes.
• Worked as a consultant for the development of a client application/system.