Personal auto liability is U.S. property/casualty insurers’ largest line of business, and personal auto insurers face a long and daunting list of challenges. But many of those challenges will merely alter competitive dynamics within auto insurance markets, enabling the best insurers to gain market share at the expense of weaker competitors (e.g., those insurers that master telematics and the associated big data issues can look forward to stealing share from those that don’t.)
Unlike the majority of other challenges, the advent of autonomous vehicles threatens all personal auto insurers, because liability will shift from vehicle owners to auto manufacturers or those who provide the systems and software that enable autonomous driving. Simply put, the market for personal auto liability insurance is likely to shrink dramatically at some point, with a number of auto manufacturers already committing to accept liability when their autonomous vehicles are at fault in accidents.
None of this would be of any consequence if the cost of autonomous vehicles placed them out of reach of the typical consumer. But technology costs for autonomous vehicles are plunging. According to a recent article in the Washington Post, the cost of LIDAR (the “eyes” for autonomous vehicles) is poised to drop from $75,000 to a mere $500 or less. (See here)
Yes, it will be years before autonomous vehicles constitute the lion’s share of the vehicles on the road, and today’s personal auto liability insurers have some good years ahead of them. But change is coming, and, as Sun Tsu said, all battles are won or lost before they are ever fought. Is it really too soon for personal auto liability insurers to begin positioning for the world just now coming in to focus on long-range scanners?
The Latin America insurance outlook for 2015 is generally favorable, with high-single-digit premium growth across the region presenting complex risks and opportunities. Although real economic growth has slowed recently in the largest markets of Brazil and Mexico, stronger economic growth and inflation in some areas continue to drive premiums. Long-term trends (reduced poverty, shrinking unemployment and a population increasing above the pace of most mature markets) are bolstering consumer demand for insurance products.
In general insurance, catastrophic risks from floods, hurricanes and earthquakes are driving premium growth in a number of Latin American countries. Premiums peak following major losses as demand increases and supply becomes more costly. In contrast, the underwriting cycle slowly reduces premium rates after benign catastrophe-loss periods, such as those experienced in the last few years. The development of efficient distribution systems to increase insurance market penetration and encourage product acceptance remains a critical challenge.
As economic, political and regulatory environments evolve inconsistently across the region, inflation risk continues to persist at varying levels. While Chile’s, Peru’s and Colombia’s annual inflation rates averaged 2% to 3% from 2009 through 2013, Argentina’s and Venezuela’s percentages were the highest in the region. Argentina’s battles with its creditors, and its governmental hand in business, have destabilized its currency. In contrast, Mexico’s government remains stable and is progressing with reforms to modernize insurance and other business sectors.
From a tax perspective:
Brazil imposes the highest income tax in the region, with insurer profits taxed at 40%. Popular products include health insurance and term life insurance, as well as auto and property covers, which are sold by independent brokers. Tax incentives for retirement accumulation plans are growing in popularity.
Mexico’s tax incentives, promoting retirement savings and a reasonable income tax structure, are contributing to growth. In a country where third-party auto liability coverage is mandatory in several cities, auto insurance generates the highest premiums.
The scenario is similar in Chile, where auto insurance is also compulsory and characterized by intense price competition. Provisional life and retirement products are part of the national social security system. Approximately half of all insurers are subsidiaries of international firms. Although an open market has led to stability and a competitive balance, insurers continue to adapt in the wake of earthquakes and other natural disasters.
In Argentina, independent agents and brokerage firms account for an estimated 75% of total premiums. The nationalization of private pension funds in 2008 changed the insurance industry structure, sharply reducing the size of the life and annuity market and the number of insurers in the country. Argentina imposes a high income tax burden, with profits taxed at 35% and a 10% dividend withholding tax.
Colombia, the fifth largest Latin American insurance market,
is partially focused on investing in infrastructure to encourage demand for guaranty bonds. Automobile insurance, compulsory personal auto accident protection and reinsurance and earthquake insurance are the most important product lines. The industry aims to develop catastrophe insurance markets and enhance risk models, hoping that a stable commercial market will help deter government response to gaps in market coverage.
Peru has upgraded its economy in recent years to manage its rapid growth. Significant changes are being made in consumer protection, tax legislation and new regulation. Peru’s growth forecast is 6% this year, compared with predicted growth of 1.5% for Brazil and 1.1% for Mexico. Many foreign companies are considering Peru as a safe and desirable country for investment.
The Latin America insurance environment is becoming more similar to mature markets. Strong economic growth rates and regulatory reforms in the past decade(s) have attracted a number of global insurers, reinsurers and insurance brokers to the region. Mergers and acquisitions continue to help these global players build their positions. And cross-regional expansion efforts by Latin American-based insurers have increased their size and market reach, as well. These deals are enhancing insurers’ capabilities in product development and risk management. The implementation of new Solvency II insurance capital management regulations in 2015 is expected to result in a shift toward greater insurance industry consolidation and increased sophistication in risk management.
Low penetration rates in Latin America are caused by a number of factors and afford significant room for growth if economic expansion continues. Factors include:
Insufficient tax incentives for retirement products
Lack of knowledge among the general population about the value of insurance
Also contributing to potential opportunity is the changing perception of insurance as a necessity or investment, rather than a cost. This comes about with a change to the region’s income disparity, which in most countries is shrinking. Brazil is expecting double-digit declines in premiums across many low-hazard markets. In this heightened competitive environment, many insurers believe they can accelerate premium growth by targeting rapidly growing market clusters.
In comparison, Argentina is experiencing high inflation, tight regulation and a fluctuating economic market; nevertheless, insurance is a fast-growing industry that continues to show resilience in premiums and tolerance for expansion in a challenging environment. Argentina and Venezuela also have strict foreign-exchange control regimes. These generally do not allow residents to pay dividends or inter-company services/royalties outside of the country — in some cases, also limiting the deductibility of certain payments.
In general, it is worth discussing the value added tax (VAT) system in these countries,which is a key concern for insurers.TheVATpaid on the local purchase or importation of goods or services constitutes “input VAT” that typically should be credited against the “output VAT” generated on the taxable sale of goods or services. VAT should not be a cost of doing business. However, VAT is often an unexpected cost when entering a market. In the case of Latin American insurers with VAT taxable and non-taxable activities, the VAT calculation methodology is complex and usually generates some level of irrecoverable VAT.
Some products sold by insurance companies are exempt from VAT, meaning that any VAT incurred on the local purchase of goods or services becomes an irrecoverable cost for the insurance company (although deductible for local corporate income tax purposes). For example, the following are exempt:
Argentina’s life insurance and workers’ compensation policies
Mexico’s life and pension insurance
Certain insurance contracts in Chile, including those related to international trade, insurance of assets located outside of Chile and earthquake-related coverage
Brazil deserves a separate analysis because Brazilian insurance companies are subject to Social Integration Program (PIS) and Contribution for the Financing of Social Security (COFINS) taxes on gross revenues, at a combined rate of 4.65%. PIS/COFINS are not a VAT type of tax but, rather, they are paid on a cumulative basis: any PIS/COFINS paid by the local insurance company is not a recoverable cost. Brazil has a state VAT (ICMS) and a federal VAT (IPI), but these taxes do not apply to the sale of insurance products.
Property/casualty, auto insurance, professional liability, environmental and finance solutions are generally subject to VAT in Latin America, so any VAT paid should be fully recoverable for the local insurance company.
In addition to the VAT, some Latin American countries impose additional layers of indirect taxes that should be carefully reviewed by local insurers (e.g., gross revenue taxes, taxes on financial transactions, net worth taxes and stamp taxes, among others).
Data-driven analysis is a critical decision-making tool for Construction Financial Managers and other industry leaders.
Decision-making is arguably the most important responsibility of company leadership.
Companies that make better decisions make fewer mistakes, and achieve a distinct competitive advantage in the marketplace.
The underlying purpose of benchmarking is to continually improve the quality of organizational decision-making.
As construction risk management consultants, we help contractors prevent accidents, mitigate claims, and reduce the total cost of risk through a continuous improvement process.
We believe companies must instill management accountability for continuous improvement by linking performance measurement to both prevention activities (leading indicators) and operational results (lagging indicators). As the adage goes:
“What gets measured is what gets done.”
In our consulting roles, we frequently help companies establish realistic performance measures by conducting various types of claim and loss analysis.
This type of data analysis is usually the starting point in a performance improvement process — and a common practice among insurance agencies, brokerages, carriers, and risk management consulting firms.
In addition, we are often asked to conduct a benchmarking analysis that compares one company's claim and loss data against peer companies or to the construction industry as a whole.
The term “benchmarking” refers to the comparison of a company's performance results against those of similar peer companies. Benchmarking evolved out of the quality improvement movement in the late 1980s and early 1990s.
Its initial intent was to identify leading companies regardless of industry sector, and apply their best practices to improve one's own company. Over time, benchmarking has become synonymous with process improvement.
The traditional view of benchmarking required two separate disciplines focused on performance improvement: measures and methods. Identifying and capturing performance indicators (the measures) is only the first step; developing and implementing performance improvement (the methods) is the second and most important step for the benchmarking process to be truly effective.
The Health Club Analogy
There is limited value in benchmarking without applying new methods to address continuous performance improvement. Performance improvement requires more than the measurement of performance indicators; it requires the implementation of changes in management disciplines to attain improved operational results.
Using only performance indicators without implementing new methods to improve operations is akin to joining a health club and expecting the benefits without actually using the equipment or committing to an exercise program.
Merely jumping on the scale and gauging your weight relative to others doesn't help you achieve your own weight loss goals anymore than comparing your pulse and respiration rate to others helps you attain your aerobic or cardiovascular fitness goals. What matters most is that a person embarking on a weight loss or fitness program stays committed to the process and monitors his or her own progress.
Similarly, we believe the ongoing monitoring of claim and loss data specific to an individual company is even more important than the initial measurement of insurance claim and loss data relative to other companies.
Baselining As Benchmarking
The term “baselining” refers to the internal benchmarking process that occurs when a company compares its performance against its own results year after year. Ongoing, internal monitoring allows a contractor to determine if the company's claim and loss trends are improving or deteriorating, and to make the critical performance improvement decisions necessary to facilitate a change in results.
Referring back to the health club analogy, baselining does not compare an individual's weight and aerobic fitness to that of the other health club members. Instead, individual fitness goals and measures are established, monitored, and tracked to verify continuous personal improvement.
Similarly, a construction company can develop a baseline analysis of its loss cost performance by reviewing loss and claim data for a minimum of 3-5 years. Company results are compared from year to year, and ideally are broken down by operating entity, division, project, manager, or even crew levels.
Exhibit 1 provides a sample of a baseline analysis that compares one company's relative claim and loss performance within all of its operating divisions.
This analysis reviews the historical loss cost data for the entire company and breaks it down into meaningful data relative to each operating division. The total workers' comp, Comprehensive General Liability, and auto liability incurred claim costs (sum of paid and reserves) for each company division over a five-year period were compared to the total man-hours for each division, producing a cost per man-hour figure.
The results illustrate dramatic differences in total claim costs per man-hour for each division. This baseline analysis was the first step in raising awareness of the predominant loss leaders within the company. This increased awareness led to a detailed analysis that established plans of action and realistic cost targets by company division for the upcoming year.
We acknowledge that there are numerous benefits to measuring the frequency, type, and cost of insurance claims compared to peer groups and/or the entire construction industry. Such analyses provide the ability to:
Identify leading types and sources of claims
Establish strategic objectives to prevent the occurrence of common industry claims
Create awareness among managers and employees about the costs of claims and the impact on profitability
Post positive results on company websites and for use in other marketing materials
The Bureau of Labor Statistics provides safety-related data so that companies can externally benchmark injury and illness data against specific industry groups. (Check out the Web Resources section at the end of this article for more information.)
In addition, Bureau of Labor Statistics data is used to calculate and compare OSHA Recordable Incident Rates and Lost Workday Incident Rates, both of which are common construction industry benchmarks. This data is useful when making high-level comparisons within construction industry segments relative to injury and illness rates.
We also use external benchmarking analyses to establish risk reduction, loss prevention, or cost containment goals. In “Risk Performance Metrics” by Calvin E. Beyer in the September/October 2007 issue of Building Profits, a sample benchmarking comparison shows a representative contractor's duration of lost workdays workers' comp cases in median number of days compared against the median duration for the industry. Results such as these can highlight the importance of an increased focus on injury management and return-to-work programs.
The benchmarking analysis in Exhibits 2A and 2B compares a contractor's workers' comp claim and loss performance to an established group of peer contractors in the same specialty trade. (These companies engaged in similar work, and performed in states with similar insurance laws and legal climates.)
The analysis was based on total incurred workers' comp costs and total number of workers' comp claims as compared to payroll for each entity. Overall, Company D had worse results than the other three companies.
This prompted an in-depth review of Company D's workers' comp losses by division and occupation. As shown in Exhibit 3, the company experienced significant claim frequency and severity issues within the first six months of employment.
These findings triggered the development and implementation of specific activities designed for Company D's new employees.
Below are some of the activities that were incorporated into the formal improvement plan:
new hire skills assessments
daily planning meetings
Other Sources Of Benchmarking Data
Professional associations and industry trade/peer groups also provide comparative data for benchmarking purposes.
The Construction Financial Management Association's Construction Industry Annual Financial Survey is an excellent source for understanding the key drivers of contractor profitability. We use the survey data to determine comparative profit margins for different types and classes of contractors when we calculate a revenue replacement analysis to show the additional sales volume needed to offset the cost of insurance claims. (This technique was highlighted in the “Risk Performance Metrics” article previously mentioned.)
Similarly, the Risk and Insurance Management Society (RIMS) conducts an annual benchmarking survey that reviews insurance rates, program coverages, and measures of total cost of risk.
An example of a peer group data source for benchmarking is the Construction Industry Institute (CII). The Construction Industry Institute is a voluntary “consortium of more than 100 leading owner, engineering-contractor, and supplier firms from both the public and private arenas” (www.construction-institute.org). It develops industry best practices and maintains a benchmarking and metrics database for its participating members.
Another peer group example involves members of captive insurance companies sharing and comparing claim and loss data for the group as a whole. There is a major advantage when a true peer group shares benchmarking data: Such data sharing often leads to peer pressure in the form of increased ownership and accountability for improvement by the companies shown to be the poorest performing members.
We continue to search for more new sources of industry best practices and comparator data. A possible emerging source for the construction industry is the National Business Group on Health. This organization has developed standardized metrics known as Employer Measures of Productivity, Absence and Quality™ (EMPAQ®).
EMPAQ® helps member companies gauge the effectiveness of their injury and absence management and return-to-work programs. The founder and principal of HDM Solutions, Maria Henderson, served as a project sponsor for EMPAQ® from 2003-2007, and co-presented with Calvin E. Beyer on “Return to Work as a Workforce Development Strategy” at CFMA's 2008 Annual Conference & Exhibition in Orlando, Florida.
Limitations Of External Benchmarking
We fear that the increasing popularity of external benchmarking analyses may indicate that it has become a “quick fix” solution or a management fad. When asked to conduct an external benchmarking analysis, we always ask the following questions:
What is your purpose in seeking these comparisons with other companies?
Who are you trying to convince and what are you trying to convince them to do?
What specific peer companies should be used for comparative purposes?
Are these companies (and their operations and exposures) truly similar enough for a fair comparison?
Beware Of Pitfalls
There are many hurdles to surmount in locating suitable companies for external benchmarking comparisons. Generally, when benchmarking comparisons can be made, more often than not the greatest value lies in the workers' comp line of insurance coverage.
Here are some key factors to consider when choosing contractors for external benchmarking comparisons:
Percent of self-performed work vs. subcontracted work
Payroll class codes and hazard groupings of selfperformed work
Differential geographic labor wage rates
Payroll rate variances between union and merit shop operations
Size of insurance deductibles
Claim reporting practices
For example, claim reporting practices must be similar in order to minimize distorting the frequency or average cost of a claim. If one or more comparison companies self-administers minor claims or does not report all claims to their carrier, using carrier loss reports for the comparison is an invalid method.
We also find that comparing the frequency of claims and total loss dollars divided by thousands or millions of dollars of payroll (exposure basis) is a helpful workers' comp benchmark between companies of similar operations in similar states.
Likewise, a suitable benchmark for auto liability performance compares the frequency of claims and total loss dollars per one hundred vehicles.
When benchmarking fleet-related claims, ensure that the number and size of fleet vehicles — as well as the type of driving (urban vs. rural) and the total number of miles driven annually — are similar among the contractors whose claims are being compared.
Benchmarking comparisons of Comprehensive General Liability insurance results are especially challenging due to delays in reporting third-party bodily injury and property damage claims, in addition to the expected long tail of loss development for these claims.
All of these factors are compounded by vastly different litigation trends and liability settlements in various states and regions of the country.
Common Limitations Of Data Sources
Whether or not you intend to develop a baseline of your company's claim data or to benchmark your company's performance against a peer company, there are several issues that must be successfully resolved regarding the data's quality and integrity.
Based on our experience, we classify the key challenges associated with exposure and claim/loss data into the categories shown in Exhibit 4: availability, accuracy, accessibility, standardization, reliability, comparability, and date-related problems.
Value Of Multiple Measures
Evaluating data from various sources and different angles is also valuable. Why? Because it's possible to gain a better understanding of the whole by dissecting the parts. This practice illustrates the principle of multiple measures.
This approach is substantiated by 2006 research, which concluded that the “simultaneous consideration” of frequency and severity provides a more comprehensive result than performing analysis based solely on one factor.1
This is similar to our approach when we conduct a “Claim to Exposure Analysis” and review historical frequency and severity vs. the relative bases of exposure for each line of casualty insurance coverage.
Returning to the health club analogy, when starting a formal exercise program, you often begin with such general baseline measurements as height and weight; this is usually followed by additional measurements, such as BMI, body fat content, and the girth of arms, legs, and chest (the baseline).
As we all know, weight alone is not always the best indicator of success in fitness efforts. In fact, since muscle weighs more than fat, an increase in total body weight may actually occur after beginning and maintaining a fitness program.
Although you might not experience a dramatic weight drop, you could see a reduction in waist size and BMI — positive changes that would not be evident unless multiple measures were being used and reviewed.
Benchmarking insurance claim and loss data performance is like comparing one person's height and weight against the ideal height and weight charts based on the entire population.
Wouldn't it be more effective to establish your baseline weight and other multiple measures initially so you can see the progress you are making?
This is similar to the baseline measurements that a company should take (as well as the multiple measures) that are necessary to meet your company's performance improvement goals for financial success, operational excellence, or risk reduction.
Cal Beyer collaborated with Greg Stefan in writing this article. Greg is Assistant Vice President, Construction Risk Control Solutions, at Arch Insurance Group. As a member of the Southeast Regional team in Atlanta, GA, Greg supports underwriting and claims in risk selection, claim mitigation, and risk improvement activities. He is also responsible for high-risk liability risk reduction initiatives including contractual risk transfer, construction defect prevention, and work zone liability management.
1 Baradan, Selim, and Usmen, Mumtaz A., “Comparative Injury and Fatality Risk Analysis of Building Trades,” Journal of Construction Engineering and Management, May 2006, pp. 533-539.