The evolution of insurance carrier claims capabilities is unlocking immense value while simultaneously creating an ever-widening gap between leaders and followers. It comes as no surprise to tenured insurance executives that their organizations are sitting on a gold mine of Claims data with the potential to generate serious long-term value and market differentiation. Leading carriers have already demonstrated proven tangible advantage using oft overlooked trove to feed a number of related efforts from pricing to product development to subrogation, arbitration, etc. The data in question, and the means by which it is captured has spurred investment as well. One large global insurer, for example, uses data extracted from drone-captured images to investigate and assess damages. The subsequent effects have been 3-4x accuracy of claims evaluation and a 50% sustainable reduction in claims assessment costs. Given the latent short, medium, and long-term benefits, it is strategically important that carriers go further, investing in resources necessary to connect the dots between policy characteristics, exposure details and granular claims data.

How are these benefits simply overlooked?

To understand why many insurers are unwilling or unable to advance efforts to exploit the true potential of claims data, let’s first more deeply examine the prospective benefits. Advanced claims analytics, for example, is enabling better customer satisfaction stemming from faster turnaround times. Related analytics models substantially lower fraud rates through improved identification, prediction, and prevention. Improved claims data models allow for much more precise actuarial modeling, opportunistic pricing and product profitability. Advanced claims data analytics enable improved administrative capabilities like better litigation handling, subrogation, and appeals processing. Going further, these enhanced capabilities drive specialist satisfaction, removing unnecessary manual interventions, and resulting in lower overall claim handler attrition figures. Complementary data capabilities and analytics efforts improve productivity further via enhanced training capabilities, faster dissemination of leading practices, and improved access to on-demand coaching/continuous improvement resources.

For many insurance companies, the hurdles to capturing these myriad advantages are several folds:

  1. The time, effort, and investment necessary to develop enhanced claims data infrastructure
  2. Organizational silos that serve as roadblocks to Enterprise-level advancements
  3. Mindset to accept status-quo on the current processes and methods that create an “innovation death valley”

Time, effort, and investment in enhanced claims data infrastructure

While sufficient to satisfy a previously adequate range of descriptive tasks, simple queries, and reporting functions, the majority of carriers we speak with recognize the need for data modernization. The missing link in many cases, however, is the recognition of the need for detailed granularity in the data. For example, a traditional approach is to accept actuarial aggregation of claims data right along with the often incomplete implications these methods often suggest. Carriers that invest in better claims data models quickly become aware of the advantages of more detailed claim-level attribution, as a variety of claims segment models begin to reveal valuable and formally hidden nuances. We have our own experience of developing Claims Insights Hub, the data lake architecture created to support granular claims data to be ingested quickly and support actionable insights delivery. The impacts of these implementations are both dramatic and instructional. We learned very quickly across implementations that there are very different methods and outcomes for carriers that had adopted these solutions when compared to the broader industry. Simply put, those that take advantage of detailed granular claims data have a distinct advantage over those that do not.

Organizational silos preventing Enterprise-level advancements

To illustrate the issue here, consider the following scenario: Claims leaders understand the value of improved comprehensive claims data models, but these data assets are controlled/owned by another domain leader in Finance and/or Actuarial. Further, the business case supporting one strain of a cost-benefit analysis is realized via improved U/W margin (owned by yet another domain leader) when claims experience data is factored into pricing, which in turn improves profitability for the organization at large.

How far does this opportunity get in an organization with low cross-functional coordination? Not very far at all. Herein lies the core disadvantage, and simultaneously the challenge to executive leaders. To realize these sometimes complex, yet lucrative and strategically important opportunities, the organization must allow for cross-functional cooperation and benefits tracking that is strongly supported by an executive mandate driving the transformation from the top-down. Organizational fiefdoms that cannot or will not recognize cross-functional benefit scenarios limit innovation.

Mindset to accept status-quo on the current processes and methods that create an “innovation death valley”

Insurers, like people, are all too often stuck in their ways. A quaint attachment to “the way things are done” can unfortunately lead to functional leaders overlooking or worse yet, purposefully ignoring potential value centers due to the effort or organizational impact these opportunities represent. This effect manifests itself in technical debt caused by “Band-Aid” workarounds, and approaches that stifle the advancement of necessary capability builds. This is what we refer to as the “innovation death valley” – a difficult but not insurmountable hurdle that serves to obscure the ultimate benefit claims data and analytics transformation offers. To overcome these challenges, organizations must shift their thinking away from traditional normative methods, and take a first principles approach that allows functional and executive leaders to reimagine how they might envision their respective organizations without these legacy constraints. Embracing process improvement, automation, operating model enhancement, and advanced capabilities development (e.g., AI, Machine Learning) is a critical step towards advancing transformation goals.

As transformations go, momentum is key…

An effective means to overcoming these aforementioned hurdles is a strategy curatively called the “Flywheel Effect”. The principles of the strategy are simple: small wins generate initial ROI, which then can (and should) be reinvested into larger efforts with larger ROI. The critical element here, then, becomes timing, communication, and importantly the leveraging of organizational momentum.

Investment in cross-functional efforts should include clear effort contributions, impact considerations, and benefit paths from the outset – with all stakeholders understanding and committing to their respective roles. Lastly, ensuring proper resource competency and availability is allocated avoids inevitable “resource-crunches” where competency/skillset bottlenecks can derail steady progress.

In conclusion…

We have observed that the carriers that engage in efforts and successfully build capabilities/competencies in connecting the dots between granular claims, exposure and policy characteristics have been able to enjoy better combined ratios, more competitive pricing, lower policyholder attrition, and overall better-than-industry-average profitability as a result.

It is not technologically hard to connect the dots in the data to drive actionable insights. What is harder to drive is the more specific application of these efforts given the circumstances, yesteryear processes, and organizational structures unique to each insurer. That said, bold leadership encouraging truly transformative capability development in the claims data and analytics space has now established itself as a winning strategy to drive value in today’s modern carrier.

 

Written by

Dr. Upendra Belhe
Belhe analytics advisory
(www.belheanalytics.com)

Karl Canty
EXL Analytics, Vice-President, Life and Annuity Analytics
(www.exlservice.com/insurance-analytics)

 
 

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