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March 10^th, 2023  |  8 min read

Master Data Management for the Insurance Industry

Master Data Management (MDM) is a crucial process for many industries, including insurance. MDM involves the creation and management of a central repository of master data, which is used to support a wide range of business processes and decision-making activities. In the insurance industry, MDM is particularly important because of the large amount of data that insurers must manage in order to accurately assess risks, underwrite policies, and settle claims.

The Role of Master Data Management in Insurance

MDM plays a critical role in the insurance industry by providing a single source of high-quality data that can be used to support a range of business processes. This includes:

• Risk Assessment: In order to accurately assess risk, insurers need access to a wide range of data, including demographic information, credit scores, and historical claims data. By consolidating this data, insurers can more easily analyze and leverage this information to identify trends and patterns that can help them make more educated underwriting decisions.
• Underwriting: Once insurers have assessed risk, they must decide whether or not to underwrite a policy. This involves evaluating a range of factors, including the policyholder's history, the type of policy being offered, and the level of risk associated with the policy. By using MDM to manage this data, insurers can make more informed underwriting decisions, resulting in more accurate pricing and better risk management.
• Claims Processing: In the event of a claim, insurers must quickly and accurately process the claim in order to satisfy the policyholder and minimize their own costs. MDM can be used to manage all of the data associated with the claim, including the policyholder's information, the type of claim being made, and any relevant documentation. This can help insurers quickly process claims and reduce the likelihood of fraud.
• Compliance: The insurance industry is heavily regulated, with strict requirements for data management and reporting. MDM can help insurers ensure that they are meeting these requirements by supporting data governance policies and procedures, automatically categorizing and masking sensitive personal information and providing detailed data lineage.

What is the Business Impact of Master Data Management?

Currently, the biggest opportunity in MDM for insurance companies is the ability to organize data in new and innovative ways to enable advanced analytics, Artificial Intelligence (AI), Machine Learning (ML), and cognitive learning systems. Data-driven organizations are already using MDM architectures to “future-proof” their business by anticipating customer expectations and streamlining operations.

For example, CX management is the source of organic revenue growth for many insurers, and a modern MDM system can take the art and science of managing customer relationships to new levels. By consolidating data from individual policies and aggregating them into a customer/household view, or golden record, insurers can:

• Use advanced analytics including AI to up-sell/cross-sell more efficiently and effectively
•  Determine customer channel preferences and communicate, service, market and sell accordingly
• Understand the status of claims reported, paid and outstanding at the customer/household level
• Develop a customer level and household level profitability score.

Diving a little deeper, once an MDM solution is in place, insurance firms benefit in a number of ways:

• 360° customer view – MDM enables a holistic 360° customer view that greatly improves business insights around customer sentiment and demand. This view integrates back to the master data source, ensuring the validity and accuracy of the insights gained. The golden record takes innovation in sales, service, and marketing to new levels of creativity and personalization.
• Streamlined Customer Data Integration (CDI) – Good MDM practices enable streamlined CDI, reducing the day-today data management burden and releasing resources to focus on value-driven projects.
• New Cross-Selling Opportunities – Advanced analytics tools can reveal hidden insights previously unknown to the organization. Insurance firms can use this insight to identify cross-selling opportunities and to prioritize specific customers or demographics with tailored sales tactics.

Challenges of Master Data Management in Insurance

Data Quality: Insurance data can be complex and difficult to manage, with a wide range of data sources and formats. While traditional MDM systems have struggled to cope with semi-structured and unstructured data, augmented platforms such as CluedIn are capable of ingesting poor quality data in almost any format in order to consolidate, clean and enrich the data ready for use.

Data Integration: Insurance data is often siloed in different systems and databases, which can make it difficult to integrate this data into a single MDM repository. Historically, this would require significant data mapping and integration efforts. However, more advanced systems like CluedIn can easily cope with hundreds of different data sources.

Governance: MDM requires strong governance to ensure that the data is managed effectively and efficiently. This includes establishing clear policies and procedures for data management, as well as providing ongoing training and support to employees. A popular option for many organizations is to use a data governance platform in conjunction with an MDM system in order to ensure that data is handled in accordance with the governance standards set as well as being easily accessible and usable by business users in various teams.

Cost: Implementing a traditional MDM system is a costly endeavour, requiring significant investments in software, hardware, and personnel. The need to model and map data beforehand also added months to the length of time taken to realize any value from these investments. All of this has changed with the advent of augmented MDM systems which remove the need for upfront data modelling and use modern technologies like Graph to allow the natural relationships between the data to emerge. Contemporary MDM systems are also Cloud-native, which means that they offer the advantages of both scale and efficiency inherent to the Cloud. 

Conclusion

Despite the obvious benefits of MDM, the barriers of traditional approaches have, until now, prevented many insurers from investing in this technology. With many of those hurdles now cleared, the path has opened up for insurers who want to use their data to fuel the insights and innovations they need to remain competitive and profitable. Improvements in business processes, streamlining operations, and managing risk are all vital to the success of an insurance provider, and MDM provides the foundation of trusted, business-ready data that enables them.