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How to Lose $7 Billion a Year

It is estimated that commercial property writers lose out on more than $7 billion annually in business interruption insurance, a line that could deliver increased and sustainable earnings upside annually but has often struggled to do so. This loss represents not only undervalued policies, but also income lost because of premium calculations that are not commensurate with risk.

As with other property business, the No. 1 culprit is the decades-old difficulty that insurance companies’ face establishing adequate coverage limits for property lines — and business interruption insurance (BII) often has worse results than insurance on buildings and contents.

For the past 10 years especially, the property insurance industry worldwide has been buzzing with concerns about coverage adequacy for BII. The problem affects both business owners policies (BOPs) and the larger package policies (CPP/SMPs).

Caroline Woolley, senior vice president at Marsh’s Business Interruption Center, wrote a comprehensive report in 2015 summarizing the challenges the industry faces making BII coverage profitable. Woolley lays out five major obstacles that agents, companies and brokers face when underwriting this coverage line. Woolley says the No. 1 problem is simply “getting the values right” when policies are first written and again at time of renewal.

The valuation concern stems from the fact that there has been no standardized, simple-to- learn-and-use insurance-to-value (ITV) system for BII coverages similar to what is done today for buildings and contents.

No. 1: Getting the values right

According to a survey conducted by the Chartered Institute of Loss Adjusters in 2012 ((and quoting from PMWBG)), 40% of declarations were deemed too low by about 45%. More recently, PMWBG research shows as much as 58% of BII coverages are undervalued by 48%, suggesting the problem is getting worse at a time when demand for property insurance is in decline and competition is fierce.

Inadequate coverage disenfranchises consumers, and improper valuation undermines providers. In a very competitive marketplace, where too much supply is chasing dwindling demand, carriers losing on the valuation front lose reputation, financial advantage and long-term revenue.

From the inception of BII coverage in the 1930s, calculating risk-specific BII limits has not been easy. The BII coverage addresses shortfalls in the margins corporations face when loss occurs, so underwriters, brokers and agents should understand key variables in the insured’s financials. Unfortunately, not enough industry professionals are proficient in this area, leading to costly exposure errors, pricing mistakes and the age-old dilemma of undervaluation.

As important is the fact that, unlike with other lines, there has been very little third-party data to aid insurers with BII calculations. 

When losses occur, it’s too late in the game to correct undervaluation problems. The impact, especially in today’s economy, where wildfires, storms and other disasters routinely happen, has caused companies like Marsh to look again at the coverage line, suggesting the need for industry-standard ITV calculation tools.


Now, modern web-enabled technology offers both substantive raw data on businesses that actuaries will want to work with to improve pricing models, at the same time carriers will use the program’s web-based ITV system to calculate detailed BII coverage reports for the majority of businesses found anywhere in the U.S. Virtually any enterprise can be valued, with complex insurance specific data sets searched automatically on behalf of the user to both pre-fill input and create BII reports.

First Step to Success

Vast amounts of insight about corporations and their supply chains can be aggregated on to estimate BII limits in seconds, accessible anywhere from the Internet.

In the case of the BOP sector, actuaries and pricing managers have instant access to large amounts of aggregated data for the various sizes and types of business insured, to develop more representative and localized pricing models. Users can also adjust models automatically for the business opportunity rather than offer one-size-fits-all pricing. Additionally, because core data changes annually, savvy users can also upgrade model variables.

The 2 New Realities Because of Big Data

I have some bad news. There are no longer any easy or obvious niches of sustained, guaranteed profits in insurance. In today’s environment of big data and analytics, all the easy wins are too quickly identified, targeted and brought back to par. If you’ve found a profitable niche, be aware that the rest of the industry is looking and will eventually find it, too.

Why? The industry has simply gotten very good at knowing what it insures and being able to effectively price to risk.

Once upon a time, it was sufficient to rely on basic historical data to identify profitable segments. Loss ratio is lower for small risks in Wisconsin? Let’s target those. Today, however, all of these “obvious” wins stand out like beacons in the darkness.

To win in a game where the players have access to big data and advanced analytics, carriers should consider two new realities:

  • You can’t count on finding easy opportunities down intuitive paths. If it’s easy and intuitive, you can bet that everyone else will eventually find it, too.
  • Sustainable opportunities lie in embracing the non-obvious and the counter-intuitive: finding multivariate relationships between variables, using data from novel sources and incorporating information from other coverages.

Just knowing what you insure is only the start. The big trick is putting new information to good use. How can carriers translate information on these new opportunities into action? In particular, how can carriers better price to risk?

We see two general strategies that carriers are using in pricing to risk:

  • Put risks into categories based on predicted profitability level
  • Put risks into categories based on predicted loss

The difference appears subtle at first glance. Which approach a given carrier will take is driven by its ability to employ flexible pricing. As we will now explore, it’s possible for carriers to implement risk-based pricing in both price-constrained and flexible-rate environments.

Predicting Profitability: Triage Model

In the first strategy, carriers evaluate their ability to profitably write a risk using their current pricing structure. This strategy often prevails where there are constraints on pricing flexibility, such as regulatory constraints, and it allows a carrier to price to risk, even when the market-facing price on any given risk is fixed.

The most common application here is a true triage model: Use the predicted profitability on a single risk to determine appetite. Often, the carrier will translate a model score to a “red/yellow/green” score that the underwriter (or automated system) uses to guide her evaluation of whether the risk fits the appetite. The triage model is used to shut off the flow of unprofitable business by simply refusing to offer coverage at prices below the level of profitability.

A triage model can also be implemented as an agency-facing tool. When agents get an indication (red/yellow/green again), they start to learn what the carrier’s appetite will be and are more likely to send only business that fits the appetite. This approach has the added benefit of reducing underwriting time and expense for the carrier; the decline rate drops, and the bind/quote rate rises when the agents have more visibility into carrier appetite.

A final application carriers are using is in overall account evaluation. It may be that a carrier has little or no flexibility on workers’ compensation prices, but significant pricing flexibility on pricing for the business owners policy (BOP) cover. By knowing exactly how profitable (or unprofitable) the WC policy will be at current rates, the carrier can adjust price on the BOP side to bring the entire account to target profitability.

Predicting Loss: Pricing Model

If a carrier has pricing flexibility, pricing to risk is more straightforward: Simply adjust price on a per-risk basis. That said, there are still several viable approaches to individual risk pricing. Regardless of approach, one of the key problems these carriers must address is the disruption that inevitably follows any new approach to pricing, particularly on renewal business.

The first, and least disruptive, approach is to use a pricing model exclusively on new business opportunities. This allows the carrier to effectively act as a sniper and take over-priced business from competitors. This is the strategy employed by several of the big personal auto carriers in their “switch to us and save 12%” campaigns. Here we see “know what you insure” being played out in living color; carriers are betting that their models are better able to identify good risks, and offer better prices, than the pricing models employed by the rest of the market.

Second, carriers can price to risk by employing a more granular rate structure. This is sometimes referred to as “tiering” – the model helps define different levels of loss potential, and those varying levels are reflected in a multi-tiered rate plan. One key advantage here is that this might open some new markets and opportunities not in better risks, but in higher-risk categories. By offering coverage for these higher-cost risks, at higher rates, the carrier can still maintain profitability.

Finally, there is the most dramatic and potentially most disruptive strategy: pricing every piece of new and renewal business to risk. This is sometimes called re-underwriting the book. Here, the carrier is putting a lot of faith in the new model to correctly identify risk and identify the correct price for all risks. It’s very common in this scenario for the carrier to place caps on a single-year price change. For example, there may be renewals that are indicated at +35% rate, but annual change will be limited to +10%. Alternatively, carriers may not take price at all on renewal accounts, unless there are exposure changes or losses on the expiring policy.

Know What You Insure

Ultimately, the winners in the insurance space are the carriers that best know what they insure. Fortunately, in an environment where big data is becoming more available, and more advanced analytics are being employed, it’s now possible for most carriers to acquire this knowledge. Whether they’re using this knowledge in building strategy, smarter underwriting or pricing to risk, the results are the same: consistent profitability.

Sometimes there are pricing constraints that would, at first glance, make effectively pricing to risk challenging. As we have discussed, there are still some viable approaches for carriers facing price inflexibility. Even for carriers with unlimited price flexibility, pricing to risk isn’t as easy as simply applying a model rate to each account; insurers must take care to avoid unnecessary price disruption. We’ve discussed several approaches here, as well.

Effectively pricing to risk gives carriers the opportunity to win without relying on protecting a secret, profitable niche. In the end, this will give them the ability to profit in multiple markets and multiple niches across the entire spectrum of risk quality.

What Will Be the Uber of Insurance?

Insurance is ripe for disruption, and, given the conservative nature of the reigning carriers and large brokers, it is a fair guess that a lot of innovation will come from outside the industry. A few weeks ago, this article touched on how innovation is affecting the financial services industry, but the focus was very much on banking and investing. Today, we aim to expand on this author’s work by focusing on new entrants that are working on disrupting the insurance industry.


It is far too early to call who the big winner(s) will be, so we are not yet ready to crown an Uber of insurance, but here are a few of the candidates that we think might be in the winner’s circle when the dust settles:

1. Zenefits: Founded in 2013, this cloud-based HR management company shouldn’t be on a list of companies changing the insurance industry, but it is, because of its innovative approach to selling benefits. According to Forbes, Zenefits was one of the hottest startups in 2014 and look poised for success in 2015. Its focus is on the more than 5 million employers with fewer than 1,000 employees. Zenefits gives the HR software away and makes money on broker commissions for health insurance sold through the software.

The benefits industry was blindsided by this model, and Zenefits is facing lawsuits in multiple states but assuming it survives them, it will be in position to upend the traditional way benefits are marketed. The software looks great, and the company claims 10,000 companies with 100,000 employees are already using it. Whether or not Zenefits survives the legal and regulatory onslaught, we love its innovative free-software approach. It’s also interesting that the company started in the Y Combinator startup accelerator. We expect more and more insurance and risk management start-ups to come from start-up accelerators in the next few years as the tech crowd is waking up to the opportunities to disrupt our industry.


2. BizInsure: Founded and owned by San Francisco-based broker Woodruff-Sawyer, BizInsure brought in software from Australia to essentially automate the sales and service process for small commercial insurance. The company started with professional liability and has since expanded to also offer business owner policies (BOPs). The whole business model is based on being able to quote online, buy in seconds and have a declarations page in your inbox in minutes, all while retaining the ability to chat with a licensed agent by phone at any time for either sales or service.

The company has been growing slowly by choice, only signing up the carriers that have made their systems completely compatible so there are no manual or overnight batch processes. The company has a decent stable of carriers available, including CNA, Hiscox, Liberty International, Philadelphia and USLI. It looks like BizInsure will now push growth harder, and the question is whether it will be able to hit an exponential growth curve allowing it to disrupt how small business insurance gets sold.


3. MetroMile: The first and thus far only company offering by-the-mile auto insurance in the U.S. Metromile takes a similar approach to Zenefits in that the service is free to everybody, and then the company tries to convert you into a paying customer by offering by-the-mile insurance. Thus far, it’s only available in a few states: California, Illinois, Washington and Oregon. But the company is starting to advertise heavily that it can save you money if you drive less than 10,000 miles per year.

The free service gives you a free Bluetooth device to install in your car and an app that gives you diagnostics of your vehicle’s performance. For those not ready to fully utilize telematics, this innovative company will still allow you to stay informed about your driving behavior with Metromile Tag., which can track mileage for expenses and driving trends and provide parking location and commute optimization.

Another reason the company is a potential disruptor to the industry is because, since January 2015, it has partnered with Uber to offer insurance to drivers, essentially guaranteeing that Uber drivers don’t have a gap in coverage when the Uber policy isn’t covering them. If you think about it, consumers are very used to the pay-for-usage model in other areas, like electricity, water and gas, and MetroMile’s marketing makes the connection explicit. Technically, the company is an agency, not a carrier, and the product is underwritten by National General Insurance Group.


4. Evosure: Currently on invitation-only beta, Evosure’s goal is to reduce the 60% of unwanted quote requests that commercial carriers receive. Evosure simplifes the communication of constantly changing underwriter appetites; a web platform allows brokers to describe the type of risk they have and finds a matching underwriter. The management team has some insurance chops (unlike a lot of other insurance start-ups, which are heavy on tech people): Matt Foran, former director of strategy for Zurich Specialty Products; Brian Wood, former SVP for Marsh & McLennan; and Brett McKenzie, former director of marketing at Fireman’s Fund. We also really love their “Commercial Insurance Is Sexy” T-shirts; we completely agree!


5. Friendsurance (Germany): Combining social networking with personal lines insurance in a very interesting way creating a peer-to-peer (P2P) insurance solution. You create a group of friends needing the same type of insurance and pool your money and insure the pool’s risks with a carrier. If money is left over at the end of the policy period because of good claims experience, you get a refund, or your next term’s premium is cheaper. You never have to pay more than your premium, even if losses are bad because of a stop-loss. Friendsurance works because insuring with friends reduces fraud and results in better risk selection. Small claims are paid from the pool without the expensive process at the carrier, and the pool grows virally without the need to pay a sales force. We really hope that this works and that somebody tries it in the U.S. soon. After all, if you think about it, this would be a natural 21st century extension to the age-old idea of mutual insurance.


6. SocialIntel.com: Getting credit history, driving history and other background information to underwrite personal lines accounts is expensive. What if we could underwrite equally effectively by analyzing a person’s social media posts? It’s kind of a crazy idea, but that’s what SocialIntel.com is selling. If it works, it could be a game changer. The company aims to help carrier underwriters without using expensive data from the usual databases. Our guess is that it wouldn’t work too well for the over-40 crowd, but it probably works great on my generation because we have a tendency of posting everything on social media. The coolest part of it is that the company continually re-evaluates the risk, not just at underwriting, claim and renewal time.


7. Policy Genius: Started by two former McKinsey consultants who were astonished at the backwardness of the insurance industry. They are focused on life and disability insurance and trying to disprove the idea that insurance is “sold and not bought.” They believe that if you educate consumers with the right system, they will buy the right product without a hard sell. Aimed squarely at the Millennial buyer, the friendly insurance checkup takes five minutes and walks you through the different risks in your life. Then it shows you what “People Like You” usually need coverage for and explains why. At the end, you get an insurance to-do list, which recommends the insurance you need in simple language. Interestingly, it points out even home and auto insurance, which, currently, the company doesn’t sell. We really like that the company also tell you what kinds of insurance you don’t need, which builds trust.

The company recommended that, at 32 years old, I don’t need to buy long-term care yet. If they expand to do all insurance products and do it well, they could become the new way to buy personal lines insurance. One minor thing that’s a turnoff: The company doesn’t currently have an app, so you have to do everything at the website.


We are excited to watch these seven companies develop. The insurance industry is ripe for disruption, and innovative ideas that approach opportunities from a different perspective and complement policyholder demographics are bound to put new life in an old business. Comment below: What other companies or products do you have your eye on?

This article originally appeared on InsNerds.com.

Survey: Predictive Modeling Lifts Profits

The breadth and depth of predictive modeling applications have grown, but, of equal importance, the percentage of participants reporting a positive impact on profitability has dramatically increased, Towers Watson’s most recent predictive modeling survey finds.

Our 2014 Predictive Modeling Benchmarking Survey indicates the use of predictive modeling in risk selection and rating has increased significantly for all lines of business over the last year, continuing a long-term trend. For instance, in the personal auto business, 97% of participants said that in 2014 they used predictive modeling in underwriting/risk selection or rating/pricing, compared with 80% in 2013, a 17-percentage-point increase. For standard commercial property/commercial multiperil (CMP)/business-owner peril (BOP), the number jumped 19 percentage points, to 51%, during the same time period (Figure 1). In fact, the percentage of participants that currently use predictive modeling increased for every line of business covered in the survey.

Figure 1. The use of predictive modeling in risk selection/rating has increased significantly for all lines of business over the last year

Does your company group currently use or plan to use predictive modeling in underwriting/risk selection or rating/pricing for the following lines of business?

Sophisticated risk selection and rating techniques are particularly important in personal lines, where models have now penetrated most of the market. An overwhelming 92% of survey participants cited these techniques as essential drivers of performance or success. To a significant degree, this was also true for small to mid-sized commercial carriers, with 44% citing sophisticated risk selection and rating techniques as essential and another 42% identifying them as very important.

Even as the use of predictive modeling extends to more lines of business, there is an increasing depth in its use. Predictive modeling applications are increasingly being deployed by insurance companies more broadly across their organizations as their confidence in modeling increases. For example, 57% of survey participants currently use predictive modeling techniques for underwriting and risk selection, and another 33% have plans to use them over the next two years. Although a more modest 28% currently use predictive modeling to evaluate fraud potential, a sizable additional 36% anticipate using it for this purpose over the next two years. Survey participants report plans to deploy predictive modeling applications in areas including claim triage, evaluation of litigation potential, target marketing and agency management. These applications will favorably affect loss costs, expenses and premium growth.


Eighty-seven percent of our survey participants report that predictive modeling improved profitability last year, an increase of eight percentage points over 2013 (Figure 2). The increase continues a pattern of growth over several years.

Figure 2. Companies implementing predictive models have increasingly seen favorable profitability impacts over time

What impact has predictive modeling had in the following areas?

Slide 9 of Executive Summary

A positive impact on rate accuracy helps explain the improvement. In fact, the percentage of carriers citing a positive impact on rate accuracy has increased every year since 2010, when 70% cited a positive impact. In three of the past four years, the percentage-point increase in carriers citing a positive impact has hovered around 10%. In this year’s survey, nearly all (98%) of the respondents reported that predictive modeling has improved their rate accuracy. Improved rate accuracy has both top- and bottom-line benefits: It boosts revenue because it enables insurers to price more effectively in very competitive markets, retaining existing customers and attracting potential customers with rates that accurately reflect their level of risk. At the same time, rate accuracy drives profit because it also helps carriers identify and write more profitable business,and not focus solely on market share and price.

More accurate rates also improve loss ratios, which have improved in parallel, according to our survey participants. In 2014, 91% of survey participants cited the favorable impact of predictive modeling on loss ratios, an increase of 14 percentage points over 2013. When premiums more accurately reflect risk, losses are more likely to be properly funded.


The bottom-line fundamentals — profitability, rate accuracy and loss ratio improvement — identified in our survey are complemented by top-line benefits. Positive impacts were registered on renewal retention (55%), underwriting appetite (46%) and market share (41%).


Sophisticated risk selection and rating are cited as essential by many of our participants, but our survey indicates that, despite favorable trends, insurers are still far from leveraging sophisticated modeling techniques to their fullest, even in pricing. Two-thirds of participants aren’t currently using price integration (the overlay of customer behavior and loss cost models to create metrics that measure different rate scenarios) for any products. A few are past price integration and are currently implementing price optimization (harnessing a mathematical search algorithm to a price integration framework to maximize profit, volume and other business metrics) for some products.

The disparity between what is viewed as the optimal use of modeling techniques and the current level of implementation needs to be bridged if insurers want to leverage predictive modeling as a competitive advantage to identify and capture profitable business. Increasingly, insurers are making greater use of analytics including by peril rating (which replaces rating at the broad, line-of-business level with specific rating by coverage), proprietary symbol (customizing vehicle classifications for personal automobile policies) and territorial and credit analysis.

Those insurance companies that can’t employ sophisticated risk identification and management tools face the possibility of losing profitable business and adverse selection.


Profitability is hard-earned in the current competitive property/casualty market, and predictive modeling is recognized by a steadily growing number of companies as an invaluable tool to improve both top- and bottom-line performance that ultimately reflects in earnings growth. Our survey suggests that insurers are increasingly comfortable with predictive modeling and are using it in a growing number of capacities. However, participant responses also indicate that there are still many benefits offered by predictive modeling and other more sophisticated analytical tools that have not been achieved, such as treating data as an asset and more effectively using predictive modeling applications to improve claim and other functional results. Improving performance on these issues alone could make a significant difference in the profitability of insurance companies and offers all the more reason to explore new ways to benefit from data-driven analytics and predictive modeling.


Towers Watson conducted a web-based survey of U.S. and Canadian property/casualty insurance executives from Sept. 3 through Oct. 22, 2014. The results discussed in this article represent the views of 52 U.S. insurance executives. Responding companies represent a significant share of the U.S. property/casualty insurance market for both personal lines carriers (17%) and commercial lines carriers (22%).

Leap Year: Season 2, Episode 3 – Of All The Gin Joints

Leap Year Season 2: Episode 3 by Mashable

Just when you thought things couldn’t get any worse for C3D, they really did. Even without any equipment or prototypes, a trashed office, an accelerated launch schedule (thanks Jack!) and no insurance money to rebuild (thanks Glenn Cheeky!), it still felt like the team could pull it off. But, having the company bank account drained is just the perfect sour cherry on top of their sad sundae of a business. It’s no wonder Olivia wanted to quit. I’m sure she’s not the only one.

The bank account hack really threw C3D for a loop. Unfortunately, this type of thing happens more often than you’d think and it’s often an inside job. But, just like their coverage for the damaged equipment from last week’s break-in (if they could report it), there’s a way to protect a company from employee theft. If C3D added a commercial crime package to their business owner’s policy, they’d be reimbursed for fraudulent transfers, employee theft, forged checks and other dishonest acts that might happen.

So, about that rival company, Livefy. It’s hard to believe that the office being destroyed and the bank account hack aren’t tied together. Jack’s romantic wanderings have once again caused trouble for the team. It seems like June Pepper was very busy while she had Jack detained on her couch at the beginning of the season. What about Sam the Livefy CEO that Jack and Aaron invited over to threaten and dress down? That didn’t exactly work out as planned. Jack is going to have to pull of a miracle to make this work and regain the support of his team.

But, why was Sam so harsh to Jack and Aaron and so sweet with Olivia? I’ve got a hunch her feelings might change once she realizes she’s sleeping with the enemy.

If their rival Livefy really did all of these things why wouldn’t C3D want revenge? The only problem is, the notion of getting revenge is always better than actually doing it. They say revenge is a dish best served cold, but C3D needs to do something now before they transform from a hot startup into Silicon Valley’s latest cold leftovers.