Data Governance and Quality Assurance in Insurance Services

  • Data Governance and Quality Assurance in Insurance Services
  • Germany - Munich

Data Governance and Quality Assurance in Insurance Services

Course Category : Governance

In the era of accelerating digital transformation within the insurance sector, data governance and quality assurance have become critical pillars for building trust and enhancing institutional performance. This training course enables participants to design and implement integrated frameworks for data governance that ensure accuracy, consistency, and compliance with industry regulatory standards
Duration: 5 Days
Level: Advanced.

Starts On

6 - July - 2026

Ends On

10 - July - 2026

Location

Germany - Munich

Language

English

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View Course Introductory PDF

Targeted Audience

  • Data governance managers in insurance companies.
  • Risk and compliance officers.
  • Data analysts and information systems supervisors.
  • Quality assurance and process management professionals.
  • Middle management executives in digital insurance and corporate governance sectors

Targeted Skills

  • Data governance based on international frameworks.
  • Data quality analysis and continuous improvement policy design.
  • Assessing data-related risks within insurance services.
  • Regulatory compliance and privacy standards (GDPR and ISO 27001).
  • Developing intelligent monitoring and reporting frameworks for data quality

Expected Outcomes

  • Understand the concepts and strategic importance of data governance in the insurance sector.
  • Recognise the link between data quality and sustainable insurance services.
  • Apply institutional data quality assessment and analysis methodologies.
  • Design and implement effective data governance policies within insurance companies.
  • Strengthen compliance capabilities and ensure information integrity.

Training Topics Index

  • Definition and importance of data governance.
  • Characteristics of data in insurance environments.
  • The relationship between governance, compliance, and risk management.
  • Key performance indicators for data governance.

  • Elements of data quality (accuracy, completeness, timeliness, consistency).
  • Tools for analysing data quality.
  • Identifying and addressing quality gaps.
  • Continuous improvement methodologies for data quality.

  • International standards (GDPR, ISO 8000, ISO 27001).
  • Compliance requirements in the insurance sector.
  • Privacy policies and data protection practices.
  • Internal controls and information audits.

  • Designing a corporate data governance structure.
  • Defining roles and responsibilities.
  • Managing data throughout the insurance lifecycle.
  • Performance indicators and continuous monitoring.

  • Analysing successful global insurance cases.
  • Discussing operational challenges in implementation.
  • Project management tools for data quality initiatives.
  • Developing an actionable data governance plan.