Commercial Insurance Rating in a Rapidly Changing Market

During this volatile time in commercial insurance, it can be difficult to know what steps to take to remain competitive. Protecting profitability, while attracting and retaining the right customers, is key.
Download this white paper to discover four critical steps that will help you leverage more effective risk scoring that give you the ability to:
  • Price with precision and avoid adverse selection
  • Increase conversion and retention rates for ideal customers
  • Increase straight-through processing
  • Improve the customer experience

Before you develop and implement your own predictive models, take this 4-question assessment to test your readiness:

Download the paper now to learn how leveraging the power of better predictive models can improve your underwriting process and improve profitability.

Unlock the full white paper

Diversity, change and the digitization of insurance

At the core, small businesses have always been a diverse population that span across a variety of industries and geographies. But today, the definition of small business continues to be redefined, driven by an evolving market. Examples of market changes include the rise in the gig economy, where nearly one-third of workers in the United States are now in that resource pool.1 This alone has mobilized business models that were unfavorable in a traditional market. And we would be remiss to not mention the effect of millennials. Forbes reports a rise in millennial entrepreneurship, with two-thirds of millennials saying they want to be in business for themselves.2
Further, for the commercial insurance market, servicing these diverse businesses is adding yet another layer of complexity.
All these factors point to new commercial insurance challenges that create new opportunities. To access those opportunities, commercial carriers will need effective methods for selecting and pricing those diverse risks. Crucially, carriers can no longer apply old tactics to this new era of small commercial.
of millennial small business owners would prefer to purchase commercial insurance online3
of all small business owners start their shopping journey using direct channels4
actually purchase their policy direct4

Carriers agree that predictive modeling is very important

Hover over images to see stats
Tap on the images to see stats
are using it to some degree but only one-third use it consistently across their business
of carriers are using predictive modeling to score loss propensity

Automated processes and real-time information are critical

Whether pursuing direct channels or keeping up with customer demands, carriers are increasingly compelled to digitize their workflows to become more efficient in this new small commercial era.

The power of predictive modeling and automation

Our latest survey
 of more than 400 small commercial insurance professionals revealed that carriers believe automating is important to their success, but they haven’t made much progress in fully integrating automation into their workflows.5 The following findings from the report regarding predictive modeling are especially compelling.

But, carriers should be asking themselves...

Are we using predictive modeling consistently and to our best advantage?
Are our predictive models enabling us to accurately price risk?
Do we have the right organizational culture to use predictive models effectively?

Follow the money to assess risk in a rapidly changing environment

Business financing is also a moving target.

Financial performance has proven to be key to predicting insurance loss. However, the same market changes that create diversity among business types also affect how small business owners fund their businesses. 
The most common financial products small businesses use to fund their enterprises are:6
lines of credit
credit cards
personal credit

Alternative sources of funding, such as crowdsourcing and venture capital, make the picture even more complex.

Carriers who can draw from a variety of financial data sources and apply that data to an automated risk scoring process can position themselves to capture and rate new business in these evolving market conditions.

Multi-sourcing is the backbone of effective risk scoring

While automated workflows and predictive modeling are essential to effective risk scoring, you can dramatically improve your risk assessment efforts by incorporating a multi-sourced strategy. If you are using only one financial performance source, you could be leaving yourself vulnerable to critical information gaps. 
LexisNexis internal analysis found that when using a single source for financial data, hit rates can vary from 30% to 65%. By leveraging two or three sources, we noted an incremental lift of 16% and 6% respectively. Overall, tapping into three sources results in an average scorable rate of 74%, compared to just 52% with one source. The ability to leverage business owner information further extends this coverage.

Increase hit rates by using multiple financial data sources


Single Sources


2 Sources

additional lift

3 Sources

additional lift
Your ability to more accurately rate risk increases significantly when you add additional financial data sources.

Multiple financial data sources reveal valuable information

As noted earlier, the diverse nature of small business customers and their funding sources can make it difficult to get the information you need for accurate rating. However, multiple sourcing can reveal valuable information that you would have otherwise missed.
Hover over images to see results
Tap on the images to see results

See the micro business with Robert,
the rideshare driver

Using 1 Source
No business history
Multi-Sourced Platform
Personal information available

See the small business at Chris’
Christmas tree farm

Using 1 Source
Not found on the only business source used
Multi-Sourced Platform
Found on 3rd available business source
Personal information available

See the “Smedium” business at
Brian’s brewing company

Using 1 Source
Found on the only business source used
Multi-Sourced Platform
Found on 1st available business source
Personal information available
Using multiple sources provides important information that would have been missed through single sourcing.
In the absence of the insights that multi-sourcing can deliver, many carriers neutral-rate policies. However, this can create long-term consequences for your book of business. Neutral rating results in higher premium quotes for low-risk customers, which can lead to lower conversion and retention rates. Similarly, neutral rating can generate lower premium quotes for high-risk customers—which can mean lost premiums, inflated claims losses and, in the long-term, adverse selection. 

Turn neutral ratings to accurate ratings to improve your book of business


Using one source may provide only 52% hits.


That’s 48% of policies that are neutral rated.

Multi-sourced scoring models allow you to reduce the number of policies you rate neutral by default. Instead, you can assign accurate predictive scores that can help you better manage your book for greater profitability.

Automated risk scoring, using the right data at the right time, can better equip carriers to achieve the business volume they need to be profitable in small commercial lines. However, there is no single data source that can adequately deliver all the information you need to properly assess risk. Thus, leveraging multiple sources can be more effective. 

Four steps to assessing risk in the changing commercial lines environment

Given the challenges of assessing risk in small commercial lines, how can you leverage multi-sourced data to help create more effective risk rating models? This four-step process can help.
Click on the steps to see more information
Understand your target market
Select the right data sources
Design & define your programs
Execute for maximum effectiveness

Step 1: Understand your target market

Financial information has proven to be predictive of insurance loss. However, it’s essential to select the financial data sources that reflect your target businesses and business owners’ funding practices. 
In choosing that data, consider the following:
  • What portion of your book consists of sole proprietors or business owners who are funding their business with personal finances? 
  • What financial products do your current and target customers use (traditional business loans, lines of credit, credit cards, etc.)?
  • Are you entertaining changes in your target market(s)? Are those markets financed differently from your current market?

Banks have similar struggles for evaluating small business risk.

With the growth of small businesses and the rise of the gig economy, new volumes of entities such as LLCs and sole proprietors are being created daily. When these new business owners need a loan for their business, banks may also evaluate the business owner’s personal credit history in determining whether to offer a business line of credit. To effectively use customer financial data, banks are leveraging both business and business owner personal financial performance to evaluate the risk. Insurers for small business coverages should consider a similar approach.
Understand your target market
Select the right data sources
Design & define your programs
Execute for maximum effectiveness

Step 2: Select the right data sources

Once you understand your target market, selecting the appropriate data sources for your book of business is critical. For the business, consider credit bureaus and non-traditional business financial information. For data about sole proprietors, consider personal credit and other public records to bridge the gap. Remember, not all credit and financial sources are created equally. Each source compiles different data elements and provides varying coverage.
Consider the type of data you need and how your data sources measure up against those needs. Evaluate how well each data source aligns with your book or target market. Lastly, you should evaluate and compare data providers to identify those with the best performance track record, then choose the data provider you think will work best for your business.
Understand your target market
Select the right data sources
Design & define your programs
Execute for maximum effectiveness

Step 3: Design and define your rating or underwriting programs

At this point, you’re ready to incorporate the source data into your rating and underwriting. Your key consideration here is whether to develop your own predictive models or to work with a solution provider.
It’s not enough to have access to good-quality financial data about the business. You must also have enough credible performance data to create predictive models with enough lift and segmentation. To do this, having access to models developed from large, pooled datasets can help smaller carriers that are challenged by a lack of credible data. They can also help larger carriers that may want to expand into industry segments or geographies where they currently have little exposure.

Your rating and underwriting program should be designed to get the greatest value from your data and models. Consider your risk appetite and current book as you determine the best mix of business credit, business owner credit or public record information. It’s important to have a good understanding of how the mix can help you address any profitability concerns.

Common sources of financial information, and special considerations

  • Non-FCRA sources, like business credit bureaus. These traditional lending sources may have limited coverage, and no single bureau provides a comprehensive view of the entire small commercial business market.
  • Financial exchanges. These data sources can offer an additional glimpse into important information about small business risk, such as payment performance.
  • Business owner public records. This non-FCRA data provides insight into the business owner’s personal financial performance such as bankruptcies, liens and judgements.   
  • Business owner consumer credit. While effective, this can add an extra hurdle for carriers who are not accustomed to using FCRA sources for rating.
Understand your target market
Select the right data sources
Design & define your programs
Execute for maximum effectiveness

Step 4: Execute for maximum effectiveness

Turnaround time is a key element in the customer experience, especially in commercial insurance. Our research about commercial insurance trends shows that 90% of carriers consider increasing turnaround time as their top priority for improving the customer experience.7 Businesses may use a variety of financial products in different ways, which means there are likely to be several sources to pull from. Having real-time access to data and the resources that provide that data can help improve your ability to derive accurate ratings and process quotes faster. This must be an integral part of your process and workflow.

How automated, cohesive, multi-sourced scoring benefits your business

The ability to execute an automated scoring plan based on real-time data, seamlessly leveraged from multiple sources, can help you:
Click on the tiles to see more information

Drive more precise pricing »

Rate-based pricing means you can more accurately price a business with a greater loss propensity, while ensuring you don’t overcharge a business with a lower loss propensity―and lose that account to a competitor. Also, you can better rate policies you may currently be rating neutral.

Avoid high risks from adverse selection​ »

Robust scoring helps mitigate the risk of adverse selection in two ways. First, it helps to provide a more complete picture of risk by incorporating more robust information into the scoring process. Second, by increasing the volume of risks that you score, you can minimize the risk of underrating a high risk and being subject to adverse selection.

Attract good risks and improve retention rates​​ »

With better coverage, you are able to identify good risks and approriately rate them. This can increase your conversion rate and reduce the risk of the business shopping at the time of renewal and potentially losing a customer to a competitor for these highly desired risks.

Reduce underwriting expense​ »

Risk scores enable STP by helping to identify those queries that don’t require human intervention. Efforts that increase STP can help you avoid the added expense of having underwriters review policies.

Improve the customer experience​​ »

Customers expect quick turnaround times. With more accurate pricing and increased STP, insurance carriers can offer their agents and their small business owners a better customer experience, while increasing their potential to service a direct presence.

Embrace change to improve your book

The current challenges that make predicting risk in small commercial lines more complex―diversity in business types, disparate funding sources, and getting the right and enough data―can be addressed by developing comprehensive multi-sourced scoring models that help you capitalize on the opportunity to: 

Achieve long-term profitability

Achieve long-term profitability, especially as the market shifts to accommodate more diverse business models and younger business owners

Improve retention​

Improve retention and conversion rates among low-risk businesses

Protect against adverse selection

Protect against adverse selection for high risk businesses
It’s an exciting time for commercial insurance―a time in which challenges can be turned into opportunities. Making multi-sourced risk scoring an integral part of your underwriting process is an important step in seizing these opportunities.

Find your opportunity. 
Make it happen. 
Move forward.

How LexisNexis Risk Solutions can help

Having a partner such as LexisNexis, who is focused on supporting your financial data insights and predictive modeling needs as they relate to small businesses, allows you to:
  • More seamlessly move from one data source to the next in a near real-time fashion
  • Better adapt to the fragmented market while supporting new business owners
  • Leverage up-to-date predictive models that help you keep up with the marketplace
  • Better target and capture new profit pools in the small business market

We are a trusted steward of the insurance industry

We are an experienced partner in predictive analytics―not just a data provider

We have a dedicated team to help file your predictive models, where mandated