December 6, 2017

Dax Craig: Do you have the Commitment and Buy-in for Predictive Analytics?

By Dax Craig, CEO and President, Valen Technologies

Dax CraigLast week, we reviewed the most important considerations to discuss internally before taking on predictive analytics: senior level commitment, organizational buy-in, data assets, and IT resources. If you’ve decided this is the right time for your organization to use analytics in underwriting, there are manageable steps you can take to move the effort forward. Whether you are the CEO, a senior manager, or have to sell your plan to management, you need to secure the commitment and organizational buy-in to succeed with a predictive analytics program.

Dedicated commitment from the senior management team is paramount and, like any group of executives, they need certain proof points, goals and plans. Answering the following three questions can better ensure that commitment.

  • How will you know if the predictive model works?
  • Are the predictive analytics driving meaningful and demonstrable benefits that are key metrics for your organization: for example growing surplus or profits, loss ratio improvements, pricing accuracy, improved efficiency, etc.?
  • What are the implications to the organization? What do you know about the IT impact, changes to the underwriting workflow, how underwriters will be trained, and how this will affect agency relationships?

In our business, we regularly address the following common concerns at the C-level. First, you need to prove that predictive analytics works. You can create a model or pilot project to showcase how a predictive model will impact your book of business and uncover previously unseen trends in your data. Make sure you have a common definition to measure success that includes concrete goals to determine where the effectiveness for your organization lies. Whether the success metrics for your organization are target loss ratio improvements, more competitive pricing or premium growth, be sure to set executive management expectations prior to embarking on any predictive analytics project.

According to an article by Chairman and CEO of Gen Re, Tad Montross, entitled “Model Mania,” he notes that predictive modeling is changing the game for the insurance industry and requires execution excellence. A few questions that he suggests answering will help internally build the confidence that your organization can monitor and validate the model’s results.

  • What is the appropriate risk appetite?
  • Do we understand the sensitivity to the assumptions being made in the model?
  • What are the model’s limitations? How do those limitations impact projected results?

Finally, CEOs and senior managers want to know how the implementation will be successful. We’ve seen several effective strategies to get the organization on board and facilitate the change management process. There are top-down and bottom-up strategies, and communication plans for each. Your challenge is to figure out what strategy is right for your organization and culture.

To give you some real examples, one of our customers made a declaration to implement a predictive model in a top-down approach that was prescribed and followed at every level of the organization. Their models have been in production for four years and have produced tremendous improvements. Another carrier took a bottom-up approach and included underwriters during each step of the process from pilot to implementation, with a great deal of transparency and the ability to ask questions. There were several workshop sessions to talk through counterintuitive examples so that underwriters had time to understand the value of counterintuitive scores well ahead of implementation. This carrier too is seeing significant results. Lastly, one of the most successful implementations we’ve seen comes from a carrier that developed a comprehensive marketing and education program for their independent agents. It was designed specifically for agents to explain what the predictive model included, how it worked and what the pricing impact would be. They did not experience a high level of friction with agents that we’ve heard about from other carriers.

One thing to remember in this whole process is do not be afraid to start small. Whether you have predictive analytics in place or you’re thinking about expanding, you can build on early wins to show measurable results and secure organizational buy-in. You don’t have to go all in and then cross your fingers hoping things work — you can start small to get up-and-running and build from there. Carriers that focus the use of predictive analytics on one area of operations, like underwriting or claims, and then broaden their implementation across the entire organization over time, will see greater results.

Using a thoughtful approach and methodology will go a long way to getting senior level commitment and organizational buy-in when implementing predictive analytics. To help you learn more about preparing your organization to use analytics effectively, download Valen’s webinar “Ready to Take on Predictive Analytics?”.

About Dax Craig
Dax Craig is the co-founder, president, and chief executive officer of Valen Technologies. Based in Denver, Colorado Valen is an advanced data and analytics provider for the property and casualty insurance industry. The company leverages its large consortium data assets to help carriers price insurance policies more accurately and achieve lower loss ratios.

Prior to founding Valen in 2004, Dax was founder and CEO of Xertex Technologies, which was acquired by global leader in the wireless antenna industry, Centurion Wireless. Dax proceeded to serve as vice president of global business development at Centurion, where he was directly responsible for global business development including sales, market definition, market segmentation, market research, strategic planning, and market development.

Dax graduated from the University of Tulsa with a bachelor’s degree in business administration and marketing. He earned his MBA in finance from the University of Colorado at Boulder.

About Valen Technologies, Inc.
Valen Technologies, Inc. provides turnkey predictive analytics to the property and casualty insurance industry. Valen’s proprietary consortium database, called Valen Network Data, is used to deliver predictive modeling products that improve risk selection, pricing, underwriting, audit, and inspection processes. Valen Network Data is comprised of nationwide data that includes policy-level information for Workers Compensation, Homeowners, Premium Audits, Commercial Auto and BOP, combined with disparate, non-industry data sources carefully mined to maximize usefulness. Our suite of products that includes PropertyRightTM, InsureRight®, UnderRight®, RateRight®, and AuditRight® are delivered in a fully hosted environment. Learn more about Valen at www.valen.com and http://propertyright.valen.com.

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