“Our CIO thinks he’s a chicken. We’d like to get him some help but we need the eggs.” Therein lies a serious pain point for many traditional life insurers when it comes to data innovation: there’s agreement that change is necessary, but the cost and complexity of replacing ingrained back office processes is too high. On the surface it can seem easier and cheaper to deal with the same old eggs — even as they’re getting more rotten by the minute.
Is the underlying problem with treating data as a high-value asset one of cost, complexity, or both?
According to Susan Holliday, Head of Reinsurance Strategy at Swiss Re, “everyone loves new channels and distribution options and offering customers the option to purchase products on the web or through an app is fantastic. But in my view, the industry has not really addressed many of the back-office challenges that come with having a huge amount of in-force business.”
With that comment in The Insurance Innovation Imperative, a KPMG report, Holliday touches upon one of the greatest challenges in the life insurance sector. In the U.S. alone, an enormous amount of in-force business is being generated by 75 million baby boomers as that generation gradually diminishes. Along with strategizing how to win prospective customers born in the digital age, insurers also must be able to apply the speed and connection that all customers are now demanding, regardless of age and technical acuity.
Meeting existing demands may add enough strain for some firms to take major innovations off the table, at least for the immediate future. Here’s how the analysts at KPMG see it: “With so much change already underway across the sector – not just from innovation, but also from new regulations, new customer demands and new expectations – few insurers seem to have the time or bandwidth to take on new projects.” Seventy-nine percent of respondents to their most recent global insurance survey admitted to “already running at full tilt just keeping up with their core requirements.”
In the same survey KPMG asked, “what are your organization’s biggest challenges for the next two years?” Sixty-five percent put regulation at the top of their list, with 45 percent citing the cost of change.
This week’s episode of The McKinsey Podcast featured analysts Nimal Manuel and Bill Wiseman sharing insights on the ways analytics can drive productivity. Wiseman, who works primarily with industrial firms, highlighted issues that touch fintech as well. “The biggest thing I see actually has nothing to do with data science or mathematics or data storage, it has to do with legal and governance frameworks,” he said. “Most of the clients I work with are multinational. They’re dealing with different legal domains across countries. They’re dealing with different issues of consumer protection, different levels of employee protection.”
Wiseman added, “just having a legal framework around what data they can use and what they can’t, and how they can process it and what they’re allowed to do with it—it’s a massive challenge, just getting your head around the legality of what you’re allowed to do with the data that you have, what consumers are allowing you to do with it, what employees are allowing you to do with it.”
In their June 2016 insurance report, Empowered for the Future, KPMG identified the two biggest disruptions to the industry: on the operations side, the need to balance growth and increased efficiency against tightening budgets is causing the most agitation. On the business model side, it’s governmental policy compliance and enforcement.
All insurers strain beneath the constant pressure of regulatory compliance. Those who take on data innovation projects – from first movers to fast followers and those in between – must keep the realities of constant change at top of mind. Analysts from Wolters Kluwer (WK) have seen the impact of resistance, and in a May 2016 survey, note that “while the reporting requirements of any given regulation are effectively set in stone, the data needs of firms’ business lines, and finance and risk departments, are anything but. Firms need flexibility of data to support their many and varied activities. It’s therefore clear that firms are facing a significant data management challenge that can’t be addressed by an inflexible data model.”
WK’s analysts were also quick to point out the lack of standardization amongst regulatory bodies. As a consequence of that hindrance, insurers are “reporting across different financial centers, asset classes and activities all requiring slightly different nuances of data.”
On a national scale, regulators may have similar intentions, but requirements may be just dissimilar enough to require their own set of specific data points. “As a result, there is much duplication of effort not only across the industry but also within institutions as firms are forced to increase their efforts to source, integrate and report the correct data sets and reports to ensure compliance with the broad range of regulations they face.”
In their most recent update on the top market conduct actions for U.S. insurers, published in late 2015, Wolters Kluwer revealed the consequences of relying on the same old eggs in the back office. Consider the top three actions, taken verbatim from the report:
1. Failure to acknowledge, pay, investigate, or deny claims within specified timeframes
2. Improper/incomplete documentation of underwriting and claim files
3. Failure to pay claims properly in accordance with policy provisions and requirements
Regulatory requirements are a constant, as is the discomfort of dealing with change. One constant life insurers can’t afford to maintain is the failure to recognize, manage and leverage the value of their existing data. Insurers need a better chicken to deliver better eggs – or whichever comes first.
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