Your Data Is Vital to You, But Do You Know How Much It’s Really Worth?

By: | October 30, 2018

Dr. Henna Karna is a data scientist and Chief Data Officer of Bermuda-based multinational insurer AXL XL, a division of AXA, which recently unveiled DEEP, the industry’s first Digital Ecosystem & Engagement Platform. Karna can be reached at [email protected]

As companies across all sectors evolve into digital enterprises, there is an increasing need to value a company’s data as a tangible asset on the balance sheet. While data appears to meet the formal criteria of a business asset, current Financial Accounting Standards Board (FASB) accounting practices prohibit organizations from capitalizing it.

This may need to change.

For businesses that are information-rich, like financial services, data is the feedstock for pricing products, making it the primary asset of value. For other companies, data can become a separate revenue stream offered as a new product line or separate income stream. Insurers, for example, could provide benchmarking information on workers’ compensation claim trends across different occupations in disparate geographies to customers or third-party companies for a fee or as a free service.

Insurance has always been a data-focused business, albeit a historical one. By integrating historical information with more real-time sources of data and leveraging predictive data analytics, machine learning and other cognitive computing technologies, insurer capabilities will expand. By capturing and analyzing a vast array of structured and unstructured data, carriers can create new commercial insurance products and unique insurance coverages customized to a client’s specific demands.

Insurance has always been a numbers game; now the numbers have more meaning than ever before.

Once data is digitized, a computer can capture, search, exchange and integrate different data elements. Digitalization — a company’s use of this digitized information to optimize its business and operating workflows — then follows. The next step is digital transformation, which calls for integrating the organization’s digital footprint with partnering businesses and customers in a collaborative and transactional digital ecosystem.

As companies move forward in this three-step journey, they will capture and access both historical and real-time structured and unstructured data for analytical purposes. The bonus is that the semantic layers of this data are being mapped at a faster rate to offer even deeper insights. Semantic data is crucial to making tomorrow’s business decisions as it represents data in common business terms. Users can access the data they need by using familiar business words like “product,” “customer” or “revenue” to obtain a unified, consolidated view of data across the enterprise.

Our own digital transformation is focused on Dense Data — basically Big Data in which different pieces of information on a particular subject are distilled to provide greater business context.

Using Dense Data, we will be able to continuously enhance the customer value of our products, dramatically increasing their value and lifespan. Like all products, insurance policies are not evergreen. If they’re not continually improved, they’ll die out like a five-year-old smartphone.

Asset Valuation

These examples of the exponential growth increasing and business value of data all point to a future where data is valued on the balance sheet as an asset. The challenge, of course, is how to determine the value of different types of structured and unstructured data. Without this capability, boards of directors, analysts and investors cannot easily and dependably compare the accurate value of one company’s data to another’s.

Accurately valuing data is an uphill climb, but it’s not impossible: Dealmakers in the M&A environment are constantly putting a value on information assets, particularly when the target acquisition is a data-rich business — like when Microsoft acquired LinkedIn. Companies can begin to assess the business value of their data by leveraging the insights of their data scientists and engineers about these information assets, where these reside and how they produce business benefits.

In our company, the enterprise data team is entrusted in partnership with the heads of finance and operations to begin the process of valuing our data.

Each time a data element is used in one part of the organization (say claims) to produce a particular insight, and the same element is subsequently reused by another part of the business (like underwriting), this reuse capability not only brings down the marginal cost of data, but it also creates a metric for monetary return. How often this particular data element is reused can be a means of calculating its value as an asset. As time goes by and the data element is reused less and less, its value would correspondingly decrease.

That’s just one idea and there are likely others. The point is that digital transformation is a nonstop locomotive, in which many businesses are still just beginning. For those of us in the insurance industry, this journey is well underway and it is both scary and exciting.

Insurance has always been a numbers game; now the numbers have more meaning than ever before.

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