By Dax Craig, CEO of Valen Analytics
Of the many reasons to incorporate analytics, we’ve long reported that the lack of investment income is a primary driver. The challenge first appeared in tandem with the economic crash in 2008, and has remained an issue through today, according to recent reports from A.M. Best. Using analytics to tighten underwriting continues to be one of the most critical ways for carriers to redress lost investment yields.
This isn’t exclusively a U.S. issue either; it extends across the globe. The Bank of England recently warned that Great Britain’s insurance market needed to decrease its reliance on cutting rates to secure business, otherwise, it won’t adequately price the risks the market is assuming. As work comp carriers begin to leverage analytics to align price to risk and compensate for investment income woes with better underwriting performance, knowing the best path forward can be daunting. There is no magic “start here” option for carriers looking to more effectively utilize analytics. Depending on the unique strategy of a carrier, there can be many different use cases for underwriting analytics that gauge specific situations more appropriately than others.
There is no one size fits all approach to incorporating analytics, but general guidelines and best practices that carriers can work through do exist. One of the most obvious, albeit regularly overlooked, aspects of achieving long-term sustainable success in analytics is to foster a collective organizational understanding of what the analytics project aims to achieve and how to monitor its progress. In short, identifying what a carrier wants to accomplish, and how it will be tracked/measured, is a critical component to ensuring success. It’s the difference between a carrier stuck in the pilot stages of analytics and one that has become data-driven.
While there are many different ways to measure an analytics program, there are some key metrics a carrier will likely want to use depending on their initial goal:
Loss ratio is a commonly used metric when monitoring the success of analytics initiatives in several scenarios. For example, a carrier is writing more high risk business than low risk, and not getting the appropriate price for the exposure. In another example, a carrier’s loss ratio begins to deteriorate quite rapidly, which is a clear sign of adverse selection. This carrier is now losing the more desirable risks and underpricing the riskier policies.
Analytics can help shed high risk accounts, identify where to raise rates, and retain the lowest risks through competitive pricing. Although effective, it’s harder to isolate this metric to any one initiative as it’s a core measurement for all insurers. We recommend looking at a combination of the discretionary pricing and risk selection decisions being made by underwriters and the predictive scores at a policy level.
The dreaded new business penalty is something any insurer focused on growth is worried about. You decide to grow into new classes or geographies, and loss ratio takes a hit. It can even go so far as to cause a downgrade in your financial strength rating. Perhaps you are in a state experiencing a surge in economic growth, with many new businesses that your work comp competitors are hesitant to cover. If a carrier can get the price right, it creates an extremely advantageous situation. Carriers must act quickly to offer the adequate rates for the risk and seize the best policies to grow their market share. For traditional underwriting, carriers struggle to properly vet policies where their underwriters don’t have much experience. There’s pressure to quote quickly, which opens vulnerability to taking on high risk new business at insufficient rates. For analytics initiatives built to find success in this scenario, a key metric to measure while using predictive analytics is responsible growth. Responsible growth is the ability to continue growing into previously unknown areas of business without performance deterioration.
Whether the goal is to grow or protect existing market share, a lack of consistency in decision-making becomes increasingly problematic as more insurers leverage analytics to find patterns in their data that predict performance. When individuals make decisions solely on their experience, it’s incredibly difficult to carry out a new strategy or test more sophisticated approaches to pricing and risk selection. At the same time, throwing out underwriter expertise is also a miss. In fact, we conducted a study that shows improved performance occurs when analytics and underwriter expertise are combined. The net impact is more than 3x what underwriters can achieve on their own in terms of aligning price to risk.
Risk quality is a key metric carriers use when they already have a sufficient loss ratio, but recognize that the landscape is changing and they must grow their business to stave off challenges from the competition. Risk quality is a beneficial metric for carriers new to analytics and those without a definitive loss ratio target in mind. The idea is to bring predictability to pricing and risk selection decisions, specifically designed to improve a portfolio’s overall quality. Even a small improvement in loss ratio can lead to substantial improvement to the bottom line.
These four metrics can be used alone or together to meet the individual specifications of carriers. The ability to understand which metrics benefit a carriers’ business goals and measure success will assist them in becoming an analytically driven company, maximize their investment, and keep all stakeholders on the same page.
About Dax Craig
Dax Craig is the co-founder, president, and chief executive officer of Valen Analytics. 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 Analytics
Valen Analytics is an advanced data and analytics provider for property and casualty insurance companies. We work with insurers who are actively looking to improve underwriting profits by driving growth and/or lowering their loss ratio. Our customers are focused on increasing competitive pressures, fighting adverse selection with innovative solutions, and raising awareness for the impending “experience gap” in underwriting with initiatives such as Tomorrow’s Talent Challenge. Our customers span many lines of business including Homeowners, Workers’ Compensation, Commercial Auto and Telematics, Commercial Package, Commercial Property, and BOP. Learn more about Valen at www.valen.com.