Transforming insurance operations via Master Data Management

By By Dennis DeGregor, VP, Analytics and Bill Faley, Director, Analytics at Trianz
The insurance industry is highly reliant on accurate data sources – it is a data and technology-driven industry, say experts...

Inaccurate data can lead to misquoted insurance policies, which can have devastating consequences on institutions and consumers.

Such was the case with the recent payment protection insurance scandal in the UK, which led to £38 billion ($52.6bn USD) in claimant payouts as of 2020 according to Gladstone Brookes.

This highlights the importance of proper data management in the insurance industry. One way to orchestrate, validate, and cleanse insurance data is through master data management (MDM). MDM is a data management framework that clearly defines the disciplines, processes, and technologies required to guarantee the accuracy, integrity, and consistency of data sources. 

Because it encompasses not just the underlying databases and data pipelines used to ingest data, but also the people and workflows that can lead to data manipulation, many companies are turning to MDM to ensure a steady flow of comprehensive, compliant, and reliable data.

The Foundation of MDM

The reason for establishing a master data repository is to guarantee the accuracy, integrity, and validity of shared data elements across different data sources. This is commonly referred to as a single-source-of-truth (SSOT). It represents the agreed-upon values for critical data domains (e.g., customer or product) across the organization. 

By focusing on the quality and consistency of data in a SSOT or master data source, insurance firms can extend data validation across all departments and services without dramatically increasing the data management burden.

A typical use case for MDM involves checking data ingested from other sources against the master data repository. If it is not identical it gets flagged for review, or cleansed, or systematically adjudicated if automation rules are in place. This prevents data duplication and assists with consolidating fragmented datasets that are related to each other—even if they may be siloed across the organization.

For an MDM system to work effectively for an insurance organization, the business outcomes and values must be clearly defined. In most instances, the value proposition maps to one of two MDM styles: operational or analytical. 

· Operational MDM seeks to improve the data quality and consistency of enterprise data that may be shared by multiple business applications. The single source of truth can then be utilized across underwriting, claims, and re-insurance processing, for instance. 

· Analytical MDM is less concerned with altering data at the system of origin, and more focused on improving decision-making by cleansing, matching, merging, and aggregating critical enterprise data elements for use in advanced analytics and business intelligence (BI) functionality.

Customer Data Integration is Essential for Insurance Leaders

Customer data integration (CDI) goes hand in hand with MDM. The insurance industry is trending away from legacy business models, with greater emphasis on the customer experience (CX) and reinventing product-service value propositions. CDI helps organizations improve the CX and use data-driven insights to reinvent product-service value propositions.

According to ITL, insurance firms spend around 44% of their sales budget on customer acquisition. Simultaneously, only 18% of this budget is spent on customer retention. Customer retention, particularly in insurance, is difficult. Consumers demonstrate loyalty to price and typically seek “barebones” coverage, happily switching between insurance providers if it results in lower monthly premiums. 

CDI enables insurance firms to build a better picture of their customers and deliver more tailored and personalized services. Rather than a race to the bottom through pricing, insurance firms need to add new value to their product-service portfolios to differentiate from the competition and drive customer retention.

CDI enables the creation of new product-service portfolio add-ins while improving personalization and customer engagement to increase customer satisfaction. Better customer satisfaction directly correlates with retention, and more comprehensive product-service offerings cater to a wider set of customer needs leading to greater customer acquisition. 

By applying MDM to CDI workflows, insurance firms can improve the quality of the customer data they hold, leading to more accurate insights and better business decisions.

Insurance firms should also be aware of the data protection requirements with CDI, with regulations like PCI-DSS, HIPAA, and GDPR mandating more stringent data governance policies. In this context, MDM enables insurance firms to know what data they store, and exactly where it is stored. This expedites the processing of data deletion requests such as with GDPR’s “right to be forgotten.”

Similarly, stored data can be tagged as “sensitive” in the master data source, and if this data is found elsewhere in the IT network it will flag and alert a data protection officer (DPO). This prevents the export and distribution of protected data entries, reducing the risk of a data breach or mis-compliance. Since insurance firms handle highly sensitive personally identifiable information (PII) relating to finance, mismanagement and data leaks could lead to hefty regulatory action—not to mention the reputational consequences.

What is the Business Impact with Master Data Management?

Currently, the biggest opportunity in MDM is the ability to organize data in new and innovative ways to enable advanced analytics, AI/ML, and cognitive learning systems. Digital Champions are using MDM architectures to “future-proof” their businesses and avoid disruption. 

Digital Champions use MDM technologies in enabling day to day operations. As just one 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. 

For example, by leveraging 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 

· multiple customer-service systems, 

· Develop a customer level and household level profitability score.

Diving a little deeper, once an MDM solution is in place, insurance firms will enjoy numerous benefits such as:

· 360° Customer View – MDM enables a holistic 360° customer view that greatly improves business insight around customer sentiment and demand. This view integrates back to the master data source, ensuring the validity and accuracy of business insight. The golden record takes innovation in sales, service, and marketing to new levels of creativity and personalization.

· Streamlined CDI – Good MDM practices enable streamlined CDI, reducing the data management burden when updating customer information.

· New Cross-Selling Opportunities – Advanced analytics tools can reveal hidden insights 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.

Source: MDM solutions and the Digital Transformation of Insurance 


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