Frank Zizzamia is director, actuarial, risk & analytics at Deloitte Consulting LLP. Jim Kinzie is senior manager, actuarial, risk & analytics, Deloitte Consulting LLP. Caroline Buckley is senior manager, actuarial, risk & analytics, Deloitte Consulting LLP. Andreea Brezeanu, Consultant, actuarial, risk & analytics, Deloitte Consulting LLP. For more information, visit www.deloitte.com.

Chances are, by now you have heard a lot of discussions happening around the implementation of claim predictive models and the potential cost savings that can be achieved. However, have you considered the impact on claims handlers as a result of implementing a claims predictive model? In this article, we will focus on the human capital impact of leveraging advanced analytics in the claims life cycle.

A Balanced Approach To Implementation
By taking the plunge and implementing claim predictive models (CPMs), claims organizations have started the journey towards identifying and solving organizational problems that exist today, next month and years down the road. If implemented and used correctly, models can provide immediate insights and tangible cost savings for the organization. Leveraged effectively at first notice of injury or loss (FNOI/L) and throughout the lifetime of the claim, advanced analytics can have an impact on various aspects of the claims lifecycle: claims assignment, special investigative unit (SIU) referral, medical case management, litigation, subrogation, escalation and, ultimately, claims settlement and outcome.

Much of the discussion around implementing CPMs to date has been on the technical model building side of the equation, and rightly so. There is still quite a bit of 'noise' across the CPM landscape, however. There are great differences in capability in this market space from very basic data mining and analytics to far more complex and statistically advanced predictive models; with hundreds of potential claims data variables, groupings or correlations in play. In fact, the observations described later in this article are based on actual insights and experience from our having implemented this more sophisticated type of CPM solution.

Beyond Potential Cost Savings
Claims organizations tend to focus heavily on how implementing claims predictive models will favorably impact the bottom line. However, one of the major benefits of rolling out a CPM comes from creating workflow efficiencies through providing timelier loss insights to claims handlers. By accelerating critical adjusting decisions and refocusing the composition of their pending workload in a way that better uses their experience and skills, claim handlers can better focus on the right claims at the right time. This ability to better segment claims by severity and align adjuster skill set can help to increase morale, reduce case workload and can improve the overall speed and quality of claims file handling. The industry's acceptance and adoption of CPMs has moved well beyond conceptual debate to a more focused implementation and benefit realization discussion, and this is anticipated to continue to gain momentum. Has your organization considered both the cost and human capital implications of implementing a CPM?

Facilitate Higher Acceptance of Model Insights
The effectiveness of a CPM—or any large technology change program for that matter—is contingent upon claims handlers adopting the tool and embracing change. As Spencer Johnson said in the book Who Moved my Cheese?, "If you do not change, you can become extinct!" Ultimately tools don't adjust claims, people do. Whether your claims organization is thinking about adopting a CPM or you are in the midst of implementing your own models, there are some key success factors to consider. First, the organization needs to communicate the upcoming changes to the claims professionals. Communication is important, not only to adjusters and claims department, but to the entire organization. Transparency regarding any changes can reassure the claims handlers of the changes ahead. It is critical to communicate that a CPM is another adjusting tool to help enable them do a better job—for example, considering fifty or more predictive factors that no human being could process alone.

The adjusting process, however, is still very much a combination of art and science, where the insights of claims handlers will always be needed. Employee engagement in large transformational programs can directly affect morale and retention. If claims handlers understand how CPMs can help them enhance job performance, then they are more likely to feel at ease and understand that they are part of the post-implementation plan and solution. Their value is not being questioned. Rather, their insights are being acknowledged and institutionalized while being better equipped to do their job. When all is said and done, CPMs are merely another tool for the adjusting toolbox, albeit an effective one.

The second key factor is engaging and motivating a strong team of claims system users representing many offices, regions and levels, from the onset of the project. While there can be a strong tendency for parties to be skeptical and uncomfortable with transformational change, selecting the appropriate group of CPM "champions" to carry the message forward can help assist the claims organization with the adoption of the new tool and technology. This can be done by facilitating focus groups, surveys, roundtable discussions, or simply water cooler conversations with the organization's champions.

Oddly enough, it is very important to engage the users that are the most vocal opponents of model adoption early in the process. Why? Because when these earlier doubters "buy-in" to the benefits of leveraging claims predictive models, they often times become the strongest supporters of change. From models we have implemented to date, these "converts" have become an ardent force in rallying their colleagues.

A third factor is the development of education and training materials to help end-users with the adoption and acceptance of the output and insights provided by a CPM. When it comes to education and training, it is more than teaching claims handlers how to work with the model's output. It entails translating model benefits into a language to which claims handlers can relate: positive impact on case load closure and quality.

Questions to ponder include:

How will the model's output positively affect the day-to-day activities of the claims handler?
What information and insight is new, or what information is being looked at differently now?
Will the claims handler have less or more capacity based on his or her skills?
What is the best way for the claims handler to use the time earned from the efficiencies afforded by the model?
What additional activities will he or she need to undertake to support or complement the model's outputs?

With these three key factors "top of mind" and addressed, the claims organization can be much better positioned to realize the full financial value and positive claims handling workflow benefits expected from the implementation and roll-out of a CPM.

How Models Help Change Perspective
What does a claims handler need most? Odds are, most professionals would answer "more time in a day." The use of models can help by freeing up time for a claims professional to focus more on examining the right files at the right time. While the impacts to a claims handler's productivity and workload efficiency will vary by individual, tenure, and level or position within the claims organization, so will his or her readiness and willingness to accept, adopt, and change.

The following two examples demonstrate how the change readiness and apprehension of a team and an individual were addressed in the course of implementation of a CPM. The needs of teams and individuals are quite different. Ultimately, both were enlightened about the value of a CPM and have since bolstered adoption and excitement for CPMs in their respective claims organizations.

In the early communication phase of a business implementation of a large CPM, it became clear that some of the more senior workers' compensation examiners were skeptical about the value of implementing a CPM. Gaining buy-in and acceptance from a group of such seasoned claims adjuster can be challenging. In this particular situation, the examiners claimed they "knew a bad claim when they saw one and could easily identify the highest severity claims." It was fairly obvious, at least to them, that they "did not need a CPM telling them how to adjust a claim."

When faced with this type of situation, a good approach to consider is performing a closed file review (CFR) compared against the prospective claim scores generated from a claims predictive model, using information typically available at FNOL. When claims organizations encounter this type of challenge, some have employed a CFR in part as a means of "promoting" a CPM's potential better segmentation of claims at FNOL. By doing so, they found a more objective way the challenge conventional or tribal wisdom while engaging a group of highly experienced resources. Typically, a team of senior claims professionals are instructed to review several hundred closed, very high-severity claim files in order to determine if they can correctly identify the high severity claims based only on the information typically available at FNOL.

What is most interesting about this challenge is that by the end of the closed file review, the examiners who claimed they could "spot a bad claim when they see one" correctly identified just one-third of the high-severity claims based on the FNOL information. Based on our collective experience implementing CPMs and this added 'real world' closed file perspective, there exists a significant business opportunity to more consistently identify potentially high-severity claims at FNOL.

To be clear, these exercises were not conducted to discredit these very capable claims examiners, but to instead illustrate how a mathematical combination of 50 internal, external and synthetic variables could fundamentally change how claims handlers might approach a new file. The revelation experienced by the examiners was to understand that a CPM can bring them insight much sooner in the claims handling process, and in some cases, it could also deliver valuable new insights. These claims handlers quickly realized and appreciated how a CPM could be used to support their claims investigation, evaluation, and settlement. There remained a real need for their talent and skills, but their time would be better spent on the most severe claims by leveraging a well-educated head start at FNOL.

In other situations, change readiness and management may need to be considered all the way down to the individual claims handler level. In one such auto bodily injury (BI) CPM implementation, a particular claims handler was hesitant to accept the CPM outputs. This individual felt it was targeted at "automatically closing claim files and minimizing the need for (his) skills." When faced with this type of situation, an effective approach for management to take could be leading the claims handler through the CPM design and building process.

More specifically, the claims manager could walk the adjuster through what pieces of information led to the creation of the scoring algorithm and what variables carry more weight in terms of potentially predicting claims outcomes.

Talking in a business language that claims handlers can relate to is absolutely key here. It is not necessarily imperative that claims handlers know the mechanics of how a CPM is technically constructed. It is, however, quite helpful for them to understand how some of their day-to-day investigation and evaluation activities have been incorporated, along with what new insights have been brought to light. Thus, educating claims handlers about how model output provides earlier and better insights is essential.

This information may have been difficult and time-consuming to gather or interpret before, or it may have not have even been considered at all. The information can allow the claims handler to tailor the investigation, evaluation, and negotiation by being armed with more knowledge to arrive at a quality settlement and/or closure in a timelier manner.

The claims handler who was "afraid [his] job was on the line" embraced the insights being provided by a CPM. Only then did he realize that the model being introduced would help move the claim towards closure, rather than eliminate necessary justing steps or to diminish precious handling skills. This particular claims handler also became a vocal proponent of the CPM, and helped the organization accelerate the adoption of the CPM output.

Impact on Claims Handlers
Again, the key takeaway is this: models don't adjust claims, people do. The better claims handlers understand the true motivation and business objectives of implementing a CPM, the better the outcomes can be for all of those involved. Many of the business objectives and desired outcomes of implementing a CPM are squarely focused on common human capital challenges. For example, one of the pleasant byproducts of implementing a CPM is obtaining knowledge of where skill/resource gaps or excess capacity exist.

Having this insight can help allocate talent to where it may be better served. In turn, this can help the claims organization and the individual claims handlers. Morale is normally higher when a claims handler feels well-matched for his or her role and is actively contributing, not caught up in repetitive, administrative, or lower-value tasks. The insights gleaned from a CPM can offer claims professionals additional time to focus their energy on the claims that matter most. With more time to focus on claims files that truly affect outcomes (delivering value to insureds/claimants as well as facilitating more favorable financial outcomes), claims handlers can better manage caseload and do more with less.

This acknowledgement of value in the collective claims handler's knowledge base and experience, coupled with its scarce availability, is central to the design and rationale for building and implementing CPMs. Having a more thorough understanding of a CPM's design and business intent is helpful. However, consistently and effectively utilizing the insight generated from a CPM and doing so in a balanced manner is often critical to long term success. While the financial benefits derived from a CPM can be significant, those who also appreciate the impacts on human capital and the claims organization can realize the true value of a claims predictive model.

This publication contains general information only and is based on the experiences and research of Deloitte practitioners. Deloitte is not, by means of this publication, rendering business, financial, investment, or other professional advice or services. This publication is not a substitute for such professional advice or services, nor should it be used as a basis for any decision or action that may affect your business. Before making any decision or taking any action that may affect your business, you should consult a qualified professional advisor. Deloitte, its affiliates, and related entities shall not be responsible for any loss sustained by any person who relies on this publication.

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The Human Capital Impact of Using Claim Predictive Models

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