Analyze this, that and the other

Commercial quote analytics, for the most part, is an unexploited opportunity to leverage the operational and tactical intelligence hidden in quote data – data that is already being collected by brokers and insurers. It provides insurers and brokers with the opportunity to anticipate and influence the future behaviour, growth and profitability of their commercial business.

To explore the opportunity within quote analytics, it is necessary to understand how commercial quoting technology is being leveraged by both insurers and brokers today.

Many insurers and brokers are exploiting new technology to expedite workflows, drive efficiency and improve customer service.

Progressive brokers, through the adoption of Commercial Management Systems (CMSs) such as Policy Works and Keal comXP, capture customer and risk information and use that data to prepare quote submissions for insurers and quote proposals for their clients.

In doing so, a wealth of client and risk information is being captured on the broker’s CMS, but this data is not currently being leveraged for analytics. Insurers have created “self serve” web-based rating portals for simple commercial package business and more complex internal rating systems for larger commercial accounts.

This enables management to track the influx of submissions, monitor service levels and deliver structure around pricing and appetite to the front-line underwriting staff.

Insurers continue to promote broker use of proprietary portals, which work for brokers where it fits with their workflows, although it does require the manual rekeying of the same data into multiple portals to generate multiple quotes. By capturing prospective and current client risk details in their CMSs, brokers can upload the data directly to insurer portals and rating engines, using XML data standards produced by the Centre for Study of Insurance Operations (CSIO). The quote is then completed by an underwriter or by the broker on the insurer portal.

The latest data integration advances by insurers, such as Travelers Insurance Company of Canada and Coachman Insurance Company, have seen real-time data integration with CMS, returning a live quote transaction and the corresponding CSIO XML in real time, to update the broker’s CMS.

What very few brokers and insurers are leveraging, however, are quote analytics based on quote data being captured by their CMSs and rating portals. Too many insurers are only focusing on the results themselves (bound premium and earned loss ratio) and only addressing quality and mix of business issues after they begin to impact the bottom line.

The drivers and lead indicators that are producing those results can be found in the historical quote data, well in advance of the financial performance itself. If the lead indicators and pricing relative to appetite are correct, the desired performance will follow.

FOR BROKERS…

By capturing all of the submission and quote data for clients through their CMSs, brokers can better manage the performance of their customer service representatives (CSRs), marketers and producers, as well as hold their insurers accountable from a competitive and service perspective.

Quote data can be used to track quote/bind activity at a producer level, to ensure that the quote and new business activity is being directed to markets that have growth plans and agreed targets in place with the brokerage. The data allows brokerage principals to track the relative new business and renewal performance of producers/CSRs, in addition to performance by insurer, and to then break down that performance as a function of premium size, class of business and geography.

This allows management to identify areas of unexploited opportunity and areas requiring improvement.

The data further allows brokers to monitor the relative new business performance and competitiveness of their insurers, tracking their conversion rates by class, protection and construction.

This detail can help identify individual insurer’s “sweet spots” in terms of appetite and relative competitiveness, enabling brokerage staff to market prospective new business to insurers where they know they will have the highest probability of success. This ultimately contributes to a brokerage’s growth, efficiency and conversion rates.

By tracking the rating detail – building, stock, equipment and liability rates on new business quotes and renewals by insurer – brokerages can use these specifics to negotiate more competitive terms for their clients, based on past rating history by type of risk and insurer. They can also track the historical pricing trend on renewal business, monitoring the fluctuations in rates, not just premium, which is impacted by the sums insured and revenues.

FOR INSURERS…

For small/simple commercial business, quote analytics from insurer portals can focus underwriters on creating the opportunities to quote rather than on the new business targets themselves. By working backwards from their new business written premium targets, insurers can use historical seasonality of the business, average new business premiums and conversion rates to establish quote activity targets for their regional offices.

Performance to quote activity targets can then be tracked daily to monitor how a region is performing against the monthly plan and corrective action can be taken early on should things start to veer off target.

In situations where quote targets are being met, but not the corresponding new business premium, underwriters can investigate, identify and action the drivers that are falling short of plan, be it mix of business, average premium or conversion rates.

Monitoring in real time

By tracking the quote performance of individual producers and CSRs, insurers can monitor quote activity and new business commitments in real time, not just at month end when production reports are issued. As a result, corrective action can be taken early and far more effectively.

Insurers can track the mix and quality of business they are being offered, relative to their underwriting appetite. By tracking the quote performance of individual brokerage staff, unexploited opportunities can be identified with specific producers and CSRs who may not be familiar with specific insurer’s portals and products.

Insurers can identify and correct situations where they may have become the market of choice for less desirable classes of business. They can also track discretionary pricing deviation at a user level to ensure that deviations are being applied to the appropriate risks, and that pricing integrity is maintained.

Insurers can share territorial conversion rates by product, industry code, protection and construction, identifying for brokers where they will have the greatest opportunities for success, leveraging historical conversion data. If insurers track the incumbent market on new business quotes, they can actually identify the classes by insurer where the broker will have the highest probability for success.

Insurers are always providing brokers with the same lists of targeted classes of business, but the quote conversion numbers reflect their actual appetite.

Pricing for commercial package business is actuarially driven, but the amount of available premium and loss data for rate making is not as credible as that for personal lines business.

Timely response to conversion rates

Quote analytics can be used to monitor conversion rates geographically by product and by rating variable.

Ideally, conversion rates for package business are targeted to be in the range of 30% to 50%. At less than a 30% conversion rate, brokers become frustrated with their lack of success and move on to competitors’ portals.

Where conversion rates are too low on targeted classes, underwriters can work with actuarial staff to identify opportunities to reduce pricing where warranted. They can then communicate the mo re competitive pricing to brokers and monitor the impact of the reduced pricing on quote activity and conversion rates.

On less desirable classes of businesses, insurers can monitor conversion rates and ensure that they are maintained within targeted parameters by adjusting their pricing model.

At a conversion rate of greater than 50%, the insurer is likely “leaving money on the table” and has an opportunity to increase its pricing in a class, and then monitor the impact of the action. If there is no significant change in the conversion rate, the pricing model can be further tweaked until an optimal pricing level is attained, even if the pricing exceeds actuarial recommendations.

Outliers as quality control

Conversion outliers, where conversion rates by producer or brokerage vary significantly from regional and national averages, warrant investigation and can serve as a quality control mechanism.

If regional conversion rates on a particular class of business are consistently in the range of 35%, but one office or producer manages to bind quotes for that class at a rate in excess of 50%, it warrants further investigation. Occupancy, building construction, fire protection or insured values could be being compromised, to secure the business.

Conversion outliers can also identify errors in insurer rating algorithms. Insurers could be seeing higher than anticipated conversion rates in undesirable industry codes, fire protections or construction classes. Are their conversion rates on frame unprotected buildings better than that on non-combustible hydrant protected buildings? Are the insurers’ rating algorithms unknowingly making them the market of choice for less desirable business?

Conversion rates driven by quote analytics enable insurers to more objectively review conflicting anecdotal pricing feedback for specific classes of business.

For larger commercial accounts, which are individually underwritten, insurers can leverage quote analytics to track underwriter productivity in terms of submissions, declinations, quotes produced, business bound and the level of pricing deviation from “book” rates. They can use analytics to compare underwriter performance to their peers, within an office or across the country.

Insurers can also use the same quote analytics to track broker performance relative to mix of business, quality and conversion rates. They can identify opportunities to grow successful relationships and also rehabilitate less successful ones. In addition, insurers can more meaningfully share their appetite with brokers, by showing them where they have historically had the greatest opportunities for success, so that they can grow those relationships.

Commercial quote analytics will provide a significant competitive advantage to brokers and insurers who have the foresight to leverage the historical quote data they already possess. It gives them an opportunity to shape their future growth and profitability, proactively and in real time, by impacting the behaviours that drive those results.