The COVID-19 pandemic has created not just a healthcare crisis but also a global recession, and a complete solution, including robust healthcare measures such as easily available testing, will take time to develop. So, insurers need to focus on both a short-term approach, where most employees remain physically isolated and work remotely, and on a longer-term approach, where there is considerable ambiguity on the scope and timing of an economic recovery.
Every insurer needs to urgently examine current business and IT processes carefully and modify these in a secure manner to adjust to this "new normal."
Internal Culture Remains a Priority
Irrespective of the fact that the end or near abolition of physical proximity will require new modes of work, one thing doesn’t change—the importance of providing protection to customers in a cost-effective, efficient and humane way. Everything else must flow around this cornerstone.
Every insurer, as part of its culture, needs to have already addressed these foundational aspects:
- Focus on ensuring the health of employees, contractors and associates.
- Define and implement operational business and IT preparedness.
- Prepare and roll out service continuity and mitigation plans.
- Execute a corporate messaging strategy.
Coping With Uncertainty
There are no historical parallels to the COVID-19 pandemic—the closest approximations are the 1918 flu pandemic, the 1930s Great Depression and the 2008 Great Recession; however, they are only indicative—not equivalent.
We cannot predict with great accuracy the nature of either the slowdown or how the global economy will recover, so we must rely on flexibility and speed.
For example, while many respected analysts feel that specific lines of business such as auto insurance or commercial property insurance will recover quickly, a prolonged slowdown might lead many customers to renew with bare bones coverage, cutting premiums.
On the other hand, you have many U.S. states considering legislation to "retrofit" COVID-19 coverage into business interruption insurance, especially for small business owners in the hospitality industry.
Another uncertainty: How are continued social distancing demands going to impact the high-touch nature of high-value life insurance sales and underwriting?
The possible scenarios across various lines of business are too vast to even attempt to list here. The variety emphasizes that speed and flexibility are vital for insurers. Every insurance company will have to focus on being as digital as possible.
What Will Be Needed?
A clear understanding of the business value and ownership of data is a vital prerequisite for implementing a digital strategy. This understanding must extend not only to data that is created within the enterprise or via business partners but may also involve data that was typically under the purview of telecom providers and national governments—combined in what we can choose to call an "information mesh."
While every government will have differing notions of data privacy, an insurer will need to build a data infrastructure to reliably share appropriate information with the government in an efficient, unobtrusive manner. Witness the reality that the best COVID-19 pandemic control program in the world, Taiwan’s, was based on combining the national health insurance database with cell phone tracking data, etc.
While building such an information mesh, insurers will need to leverage technologies such as digital, cloud and automation in an agile manner—they should not lose sight of the fact that at its root this is all about people owning data and people deciding how to use it in a secure and efficient way.
Data and Technology Enablers
Data needs to be trusted to be consumed effectively by internal and external users across the banking, financial services and insurance enterprise, and data governance is the means to this end. The conventional data governance paradigm of managing data as an asset is failing due to the plethora of architectural data patterns. Instead, we recommend that data governance must embrace alternative paradigms. These paradigms can include a hub and spoke for gateways to trusted data or potable data, like a utility providing potable water, irrespective of the water source.
Architectural data patterns can include data lakes, data warehouses or marts, on-premise legacy systems, data in a public, hybrid or private cloud, streaming data, third-party data from commercial aggregators and public sources, click stream data, IoT data and much more.
The scale and complexity of data governance presupposes that human intelligence, collaboration and judgment be helped by advanced analytics, pattern matching and AI and ML techniques in the long run to achieve these ambitious goals.