How insurers can propel their data monetization journey

Every insurer has vast reserves of data from decades of being in business. And the industry’s shift towards digital platforms, wearables, IoT devices and ecosystem partnerships has generated new sources of information that can open up significant insights.

All this data can help insurers understand complex customer behavior patterns. This can then power strategies across customer acquisition, retention, personalization, fraud prevention and more.

It can also enable operational interventions that deliver business agility, resilience and even open up new revenue streams.

Internal-to-External Monetization of Data

Based on the nature of services they offer, insurers manage multiple customer datasets with demographic, financial, health, employee, medical and property information. So over time, they’d have sectoral level data for crucial customer demographics with historical context.

Such data richness can be used for both internal and external data monetization. Internal data monetization is more business-to-consumer (B2C), where they use the data for decision-making within the organization, such as refining underwriting models, pricing efficiency, risk management, etc.

External data monetization is often business-to-business (B2B), where insurers share data with ecosystem players like reinsurance companies, distribution partners and corporations.

Most insurers go through this journey from internal to external data monetization in the following way, demonstrated using a health insurance player as an example.

Stage one: Insurers use the information on the patient's lifestyle, financial interaction, etc., to hyper-personalize offerings and experiences. This makes cross-sell/upsell offers and contextual nudges more relevant to the customer.

Stage two: Insurers incorporate external data from IoT health devices or social media activity to refine underwriting. They use health device data and historical insurance claims data to develop new offers with discounts on premiums.

Stage three: Insurers use aggregated lifestyle data to provide benchmarks or data slices to ecosystem partners like health food companies or health device companies.

Data Monetization Roadmap

A sustainable data monetization system can be achieved by,

Crystallize your vision

Define audacious and measurable goals. Rebuild your business and organizational structure to enable the achievement of that goal.

Set up analytics capability path

Create data and information assets for long term consumption and governance. Take up the role of data intermediary, accessing and using data from across partners.

Evolve customer value propositions

Know what analysis you need and arrive at a clear structure to deliver and price data. Identify the resources and skills you need, including privacy and security expertise.

Define organizational structure

Draw up an effective implementation approach with pilot projects, market tests and development sprints. Establish a formal operations center to build and scale the use-case deployment model. Manage the cultural shift towards data democratization and establish a culture that values data and analysis beyond the team of stats geeks, IT people and computer programmers.

Finally, while you are at it, be mindful of the following pitfalls,

Data Misinterpretation

Not all available data has the depth and detail we need. So, you need to be cautious of misinterpreting data that is missing comprehensive context. For example, a non-smoker who occasionally buys cigarettes for a parent could be identified as a casual smoker and subject to higher premium rates when buying health insurance. Asking fewer and more focused questions will lead to more precise answers.

Data Privacy Compliance

Data privacy is a concern because the information that life insurers have access to – around health, financial, lifestyle and other sensitive information – is highly regulated in countries. At every stage of the data monetization journey, ensure complete protection of customers’ personally identifiable information (PII) and follow global privacy regulations such as the GDPR, CCPA and HIPAA.

Data Quality

While digital-first systems have the advantage of starting with clean data, many businesses use inherited data, systems and policies that need to be treated before being put to use. In such cases, select the right algorithm to provide predictable and auditable results; update the algorithms regularly to ensure verifiability and auditability over time.

Studies predict that the global data monetization market will reach $6.1 billion by 2025 — over 2.5x growth in five years. In the future, the piece of the revenue pie held by data monetization will be on par, if not more than traditional revenue streams.

However, an insurer can only act on their most valuable asset — data — if it is stored, organized, managed and used properly. This is not merely a technology problem but more of a business prerogative.

This article has been written by Davnit Singh, Insurance Industry consultant, Thoughtworks and Nalini Haridas, Domain specialist Thoughtworks