With more than 33 million small businesses in the U.S., their insurance needs become more complex and competitive each year. Small-business owners require various insurance policies – from commercial auto and property to employee liability.
While the personal-lines insurance market started digital transformation years ago, commercial insurance was much slower to automate due to the complexity of the transactions and the reliance on independent-agent distribution models.
Overreliance on more manual processes can result in a poor customer experience, inefficient operations and a lack of usable data for underwriting and pricing. Moreover, TransUnion research shows that 82% of business insurance customers are open to obtaining a policy quote through online channels without agent assistance.
Cutting-edge technology and advanced data capabilities offer commercial insurers an unprecedented opportunity to boost profitability, elevate product sophistication, enhance customer experience and reduce costs.
Insurers that don't embrace digital transformation may risk losing market share to competitors using automation to gain an advantage in the small-business market and add to their bottom lines significantly. To realize higher profits and performance, small-business insurers must prioritize the many digital technology options available and have a clear strategy for automation.
Algorithm-Based Underwriting
When shopping for insurance policies, small businesses oftentimes seek providers offering them the most affordable policy quickly and efficiently. Any delay in receiving the quote will likely result in the customer going to a competitor instead.
Automated underwriting relies on robotic process automation (RPA), artificial intelligence (AI) and machine learning to find new information sources, glean new insights from existing data, establish consistency in evaluating risks and achieve greater efficiency.
Using externally available data to prefill necessary information at quote facilitates algorithm-based underwriting processes, enabling customers to see a price quote within minutes instead of days. Additionally, data is captured and validated in online forms, significantly reducing the probability of human error and policy mispricing.
Historically, commercial insurance underwriters have reviewed and evaluated most risks because legacy data systems could not process complex small-business transactions and data sources were fragmented, causing significant delays in the quoting process. Additionally, due to the high policy volume, underwriting departments were large, which can drive up costs.
On the other hand, with the proliferation of available data and improved data accuracy, algorithms analyze risks quickly and effectively, enabling insurers to optimize underwriter workloads to focus on more complicated policies and use their time more efficiently. Also, automation can lead to greater worker satisfaction by enabling underwriters to focus on more challenging work.
See also: How to Use Social Media Data in Underwriting
Range of Discretionary Pricing Is Shrinking
Because algorithms and data were not as readily available and accurate as today, underwriters have historically had more latitude to change prices. For example, they could lower the price from what the algorithm produced by 20-40 points in percentage terms or even raise it by a similar amount, if necessary.
As the result of improvements in commercially available and scalable third-party data, small business insurance rate plans are increasingly capable of pricing the risk more accurately, and the need for discretionary adjustments to price is shrinking.
For example, previously, a rating algorithm might price a premium at $1,000, but an underwriter could raise or lower it by $500. However, with more precise data, algorithms are more capable of pricing risks, and there's more confidence in the ability to set the price. As a result, the underwriter might still need to change the price, but only plus or minus 10%, rather than 50%. In many cases, underwriter discretion may be eliminated entirely.
For certain less complex small-business risk segments, most insurance companies have a great deal of data. For example, residential plumbers present a common risk. In the past, underwriters may have reviewed these policies and made pricing adjustments, which is a disruptive and time-consuming process. But now, an algorithm can access the risk more precisely and in a much shorter time. As a result, what may have once taken several hours to evaluate can now be completed in a matter of minutes.
Online Transactions
With digital transformation, more small-business insurance policies are transacted online instead of through an agent, reducing costs and improving the cycle times considerably. For example, instead of waiting three days for a quote, customers can receive it in 10 minutes.
When small-business owners evaluate policies, they likely request quotes from several insurance providers. Assuming their policy needs are typical and not complex, the process takes less time because they enter the policy information online instead of visiting an agent's office, which generally takes a significant amount of time and can therefore lead to an unsatisfactory customer experience.
For example, a landscaper looking for insurance coverage has relatively standard risks. The customer is self-employed, so they may only need a policy for the vehicle and a general liability policy. Instead of spending all day in an agent's office, the landscaper can spend 20 minutes online and receive quotes from 10 different insurers of his or her choosing.
If the customer has a large, complex or medium-sized business, an automated process might not be appropriate; but, for small businesses with standard risks operating in higher-volume business segments, transacting online streamlines the underwriting process and maximizes efficiencies.
See also: 3 Must-Haves for a Self-Service Portal
Transformation Is the Key to Profitability
Small business insurance profitability has been a challenge for providers due to a multitude of reasons including operational inefficiencies, high expenses and inaccurate pricing.
However, with a substantial increase in data availability, small commercial insurers are realizing the benefits that automation brings to the underwriting and pricing processes, including algorithms, precision pricing and online transactions.
Today's customers expect to receive all types of information immediately and want insurance companies to follow suit. If small business insurers don't join the digital transformation across the industry, they risk being left behind or becoming obsolete.
