Saurav Basu is Founder and President at Exavalu, empowering digital transformation in insurance, financial services & healthcare industries.
Carriers aspiring to become more data-informed are experiencing an increasing need to trust their data. The significance of high-quality, mastered data is at an all-time high since it serves as the foundation for modernizing insurance platforms and enhancing customer experience.
The segregated structure of the insurer’s application ecosystem makes the integration of multi-domain master data management (MDM), a service my company offers, essential to maintain data quality and uniformity across platforms. MDM is also expected to enable the expansion of predictive and prescriptive analytics in underwriting and claims processing. With this article, I will explore the links between high-quality mastered data and business outcomes and examine some specific use cases.
The Need For Multi-Domain MDM For Insurers
I’m seeing insurers increasingly investing in data and analytics programs to enhance the accuracy and effectiveness of business decisions using available internal and external data sources. However, the erroneous and inconsistent internal data sources make it challenging to obtain accurate and synchronized data.
Multi-domain MDM can address these issues by providing well-governed, high-quality data accessible through APIs. MDM defines the disciplines, processes and technologies needed to ensure data accuracy and consistency across operational and analytical dimensions. Companies typically adopt multi-domain MDM to ensure comprehensive and reliable data for both operational and analytical needs. To effectively implement MDM in insurance, clear definitions of business outcomes and values are crucial in disciplines like data ownership, governance, quality and stewardship.
MDM can be categorized into two styles: operational and analytical. Operational MDM focuses on improving data quality and consistency during operations like sales and customer service, while analytical MDM aims to enhance decision-making through data cleansing, matching, merging and aggregation for advanced analytics and business intelligence functionality.
Exploring Multi-Domain MDM Use Cases
Enhancing Cross-Selling Opportunities
Personalized quoting, buying or renewal experience plays a crucial role in converting prospects into paying customers. To achieve this, having a comprehensive view, known as Customer 360, is essential and relies on connected master data to enable effective account-based marketing (ABM). Using multi-domain MDM, carriers and agencies can leverage customer data through a Customer 360 view, and employing ABM with firmographic data can provide various benefits, including accelerated sales cycles, improved conversion rates, reduced lead generation and qualification costs, and enhanced opportunities for upselling and cross-selling.
Enriching Digital Engagement
Without effective master data management, the presence of redundant, incomplete, conflicting and inaccurate data becomes a major impediment to realizing the carrier’s and agency’s digital aspirations. This becomes particularly significant in areas such as understanding best product fit, consumer communication and risk preferences, or when implementing marketing automation.
Staying On Top Of Regulatory Change
The evolving regulatory landscape necessitates greater caution in data usage for insurance carriers. Privacy and information protection regulations are expanding at the state level, often with increased scrutiny and tighter GLBA, PCI and other consumer data protection needs imposed on carriers and agencies. Comprehending the consumer data’s location and permissible uses and implementing access control measures are crucial components of regulatory compliance.
Enabling Data Management Automation
Third-party master data, when used in conjunction with an enterprise MDM system, enables an organization to not only control its data but also use it to unlock numerous revenue growth and productivity gain opportunities. By focusing on the quality and consistency of data in a mastered source, insurance companies can extend data validation across all departments and services without dramatically increasing the data management burden.
Customer Data Integration: An Essential Element Of Success
MDM can help insurance companies enhance the quality of their customer data, enabling more accurate insights and informed business decisions. It’s also crucial for insurers to adhere to data protection regulations like GDPR, which demand robust data governance practices. MDM empowers insurers by providing visibility into stored data and its location, facilitating efficient handling of data deletion requests such as the “right to be forgotten” under GDPR. Additionally, MDM allows sensitive data to be labeled, and any instances of this data across the IT network trigger alerts for data protection officers.
Getting Started
Implementing multi-domain MDM in insurance necessitates focused strategies:
• Define clear objectives, executive sponsorship and ROI analysis for a solid foundation.
• Understand the domains you need to manage and link your business outcomes.
• Strengthen the base with a robust data governance framework, encompassing data quality, domain periodization and integration.
• Remember that scalability and user training are vital.
As we centralize and harmonize data through MDM, positioning the organization to leverage advanced analytics and data-driven insights effectively will be the key.
The key challenges include data complexity—which is inherently complex due to multiple product lines—coverages, regulatory environment, poor data quality and bridging the gap with legacy systems. Change management in terms of data migration can be very complex, and cost can be prohibitive in today’s scenario. Economic headwinds have not helped the case either.
Implementing multi-domain MDM in the insurance sector requires careful planning, a strong data governance framework and addressing specific challenges related to data complexity, quality and legacy systems. With the right strategy and mitigation measures, insurance leaders can achieve a unified, high-quality view of master data across domains, ultimately improving operational efficiency and decision-making in the insurance industry.
Conclusion
Insurance carriers can drive significant business value if they consider consolidating individual policy data into a customer/household view. This enables the use of advanced analytics, such as AI, for more effective upselling and cross-selling strategies. By reducing data silos, improving governance and enhancing data quality, insurers can effortlessly future-proof their businesses.
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