Data Governance in Insurance: 7 Ways It Impacts Insurers

Updated September 22nd, 2023
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Data governance in insurance ensures the precise, consistent management of industry-specific data to uphold accuracy and compliance. It also aids reliable decision-making.

It is the process of managing the availability, usability, integrity, and security of data used by insurers. It involves defining policies, procedures, and standards for data management, as well as assigning roles and responsibilities to ensure that data is properly managed throughout its lifecycle.


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In this article, we will explore:

  1. The importance of data governance for insurance companies
  2. How data governance helps bring positive outcomes in insurance?
  3. Best practices for data governance in insurance
  4. Practical case study of implementing data governance in insurance

Ready to explore? Let’s dive in!


Table of contents #

  1. Why data governance is crucial for insurance companies?
  2. How data governance supports positive business outcomes in insurance companies: Practical examples
  3. Data governance in insurance: Best practices
  4. Case study: Implementing data governance policies and procedures at CSE Insurance
  5. Summary
  6. Data governance in insurance: Related reads

Why data governance is crucial for insurance companies? #

Data governance is critical for an insurance company for several reasons, including:

  1. Regulatory compliance
  2. Data quality and accuracy
  3. Data security and privacy
  4. Eliminating data silos
  5. Improved data analytics
  6. Streamlining documentation
  7. Cost savings

Let us look into each of the above reasons in detail:

1. Regulatory compliance #


Insurance is a highly regulated industry, with numerous federal and state regulations that govern the handling of data. A robust data governance framework will ensure that your company complies with all necessary regulations and avoids penalties for non-compliance.

2. Data quality and accuracy #


Accurate data is essential for risk assessment, underwriting, pricing, and claims processing. Data governance helps maintain data quality and accuracy by implementing standardized processes for data collection, validation, and maintenance. This, in turn, leads to more accurate decision-making and competitive advantage.

3. Data security and privacy #


Insurance companies handle sensitive customer information, including financial and health-related data. Data governance ensures that the appropriate controls and policies are in place to protect this information from unauthorized access or breaches, safeguarding your customers’ privacy and your company’s reputation.

4. Eliminating data silos #


Data silos can lead to inconsistent and incomplete information, impacting decision-making and overall business performance. Data governance helps break down these silos by establishing a centralized system that promotes data sharing and collaboration across departments.

5. Improved data analytics #


Implementing data governance ensures that data is standardized and properly cataloged, making it easier to access and analyze. This helps derive meaningful insights, improve business processes, and drive innovation.

6. Streamlining documentation #


Data governance can help your organization maintain consistent and up-to-date documentation for your data assets, which is essential for regulatory compliance, knowledge sharing, and change management.

7. Cost savings #


By improving data quality, reducing duplication, and streamlining processes, data governance can lead to significant cost savings for your organization. In addition, it helps avoid potential fines and reputational damage due to non-compliance or data breaches.

In summary, data governance is essential for insurance companies to ensure regulatory compliance, maintain data quality and accuracy, protect sensitive customer information, and drive better decision-making. By implementing a robust data governance framework, your company will be better positioned to address current challenges and maintain a competitive advantage in the market.


How data governance supports positive business outcomes in insurance companies: Practical examples #

Let us look into a few practical illustrations that show how data governance can help with each of the business outcomes mentioned above:

1. Regulatory compliance #


Suppose a new regulation requires insurance companies to report specific customer data to a regulatory body. With a data governance framework in place, your company can quickly identify and access the required data, ensuring timely and accurate reporting, thus avoiding potential fines or penalties.

2. Data quality and accuracy #


Imagine your underwriting team receives incomplete or inconsistent data from different departments when assessing a potential client’s risk profile. A data governance program would establish standardized data collection and validation processes, ensuring the underwriting team receives accurate, complete data to make informed decisions.

3. Data security and privacy #


Consider a scenario where a hacker attempts to breach your company’s database to steal sensitive customer information. A strong data governance framework would have security protocols and access controls in place, making it more difficult for unauthorized users to access the data and protecting your customers’ privacy.

4. Eliminating data silos #


Let’s say your claims department and customer service department maintain separate records of customer interactions. This could lead to inconsistencies and miscommunication when processing claims. A data governance program would facilitate data sharing and collaboration between departments, improving overall customer experience.

5. Improved data analytics #


Imagine your marketing team wants to analyze customer demographics and purchasing patterns to develop targeted campaigns. With data governance, the data would be standardized and cataloged, making it easier for the marketing team to access, analyze, and derive insights from it, ultimately leading to more effective campaigns.

6. Streamlining documentation #


In a scenario where your company needs to demonstrate compliance with a specific regulation, your data governance framework would ensure that up-to-date and consistent documentation is readily available. This not only supports regulatory compliance but also facilitates knowledge sharing and change management.

7. Cost savings #


Suppose your company discovers duplicate customer records, leading to wasted resources and potential errors in decision-making. Implementing a data governance framework would help identify and resolve data duplications, resulting in significant cost savings, improved efficiency, and more accurate decision-making.

These practical examples demonstrate the various ways data governance can support positive business outcomes and create value for an insurance company.


Data governance in insurance: Best practices #

Implementing effective data governance in the insurance sector requires adherence to a series of best practices. These practices not only ensure data integrity and compliance but also empower insurance companies to extract maximum value from their data.

The following are the best practices that must be followed for data governance in insurance:

  1. Establish clear objectives
  2. Define roles and responsibilities
  3. Develop comprehensive data policies
  4. Prioritize data quality
  5. Secure the data
  6. Maintain regulatory compliance
  7. Foster a data-driven culture
  8. Conitnously monitor & iterate
  9. Invest in technology
  10. Collaborate & communicate

Let’s understand them one by one:

1. Establish clear objectives #


Before embarking on a data governance journey, insurers must define clear, measurable objectives. Whether it’s compliance, risk reduction, or enhancing customer experience, having a defined goal will guide subsequent strategies and actions.

2. Define roles and responsibilities #


A successful data governance strategy involves numerous stakeholders. Define clear roles like data owners, data stewards, and data users, each with specific responsibilities to ensure proper data management and accountability.

3. Develop comprehensive data policies #


Craft detailed policies that address data quality, security, access, and lifecycle management. Regularly review and update these policies to reflect changes in regulatory requirements and business strategies.

4. Prioritize data quality #


Inaccurate or outdated data can lead to misguided decisions. Implement processes to ensure data quality at the point of entry and set up periodic reviews and validations to maintain its accuracy over time.

5. Secure the data #


Given the sensitive nature of insurance data, security is paramount. Implement robust access controls, encryption protocols, and regular security audits to protect data against breaches and unauthorized access.

6. Maintain regulatory compliance #


Stay updated with the latest regulatory requirements, from GDPR to the NAIC’s Insurance Data Security Model Law. Regularly review data practices to ensure they align with these mandates.

7. Foster a data-driven culture #


Encourage employees at all levels to understand and value the importance of data. Regular training sessions, workshops, and communication will instill a culture where data is respected and utilized effectively.

8. Continuously monitor & iterate #


The data landscape is dynamic. Regularly review and adjust your governance practices. Employ metrics and KPIs to measure the effectiveness of your governance strategy and make necessary adjustments.

9. Invest in technology #


Modern data governance platforms and tools can automate many processes, from data cleansing to compliance checks. Investing in the right technology will streamline governance and ensure consistency across the organization.

10. Collaborate & communicate #


Data governance is a collective effort. Foster open communication between departments and ensure that everyone understands the importance of governance and their role in the process.

To sum up, as insurance companies manage vast and diverse data sets, effective data governance is non-negotiable. By following these best practices, insurers can ensure data integrity, comply with regulations, and harness the full potential of their data to drive business success.


Case Study: Implementing Data Governance Policies and Procedures at CSE Insurance #

CSE Insurance is a well-known provider of property and casualty insurance across the United States, but like many other insurance companies, they faced challenges with managing their data.

Their data was siloed across various sources, making it difficult for teams to access and use the information they needed. Additionally, basic definitions and metrics were not consistent among users, causing confusion and inefficiencies. To make matters worse, CSE had to migrate their Tableau governance efforts, adding to the complexity.

To tackle these issues, CSE knew they needed a solution that could ensure data accessibility and usability for their teams. They found that solution in Atlan’s platform, which provided a single source of truth powered by data governance policies and procedures. With Atlan’s help, CSE was able to transform its data culture, creating a foundation that led to numerous awards and accolades.

This case study highlights the importance of implementing data governance policies and procedures in insurance companies. By doing so, insurance companies can streamline their data management processes, improve data accuracy and consistency, and create a more efficient and productive work environment.

Watch these videos for more information on CSE’s experience while implementing Atlan:


Summary #

The goal of data governance for insurance companies is to maximize the value of data as a strategic asset while minimizing risks associated with its use. This includes ensuring compliance with regulatory requirements, improving data quality, protecting sensitive information, breaking down data silos, and enhancing decision-making through better data management practices.

Insurance companies handle a large amount of data, including sensitive customer information, making data governance critical. Data governance helps ensure compliance with regulations, maintain data quality and accuracy, protect sensitive information, break down data silos, improve decision-making, streamline documentation, and lead to cost savings. With a robust data governance framework, insurance companies can address current challenges and maintain a competitive advantage in the market.



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