A Solution to Insurance Price Grading Challenges

With over 25 years of experience in price modeling, we’re deeply familiar with the in’s and out’s of the standard process of pricing insurance policy renewals. The issue is that very little has changed to streamline and optimize the process. Fulcrum Analytics now has a solution that will provide an intuitive, automated, collaborative environment to take out human error, increase transparency, and speed up the time involved with pricing insurance policy renewals.

A Solution to Insurance Price Grading Challenges

 March 21, 2019


With over 25 years of experience in price modeling, we’re deeply familiar with the in’s and out’s of the standard process of pricing insurance policy renewals. The issue is that very little has changed to streamline and optimize the process. Fulcrum Analytics now has a solution that will provide an intuitive, automated, collaborative environment to take out human error, increase transparency, and speed up the time involved with pricing insurance policy renewals.

Our newly created app ClearGrade combines the best of data visualization and price modeling in an easy to use web-based platform. Curious how we’re able to transform the tedious back-and-forth of price modeling into a smooth and easy task? Keep reading to find out more.

How do insurers typically go about pricing renewal policies?

The actual dynamics of pricing analytics within insurance is as such: an analytics team (or “Price Modelers”) collaborates with the Underwriters and Pricing Actuaries in providing risk-based price grades that baseline the quotes. The Pricing Actuary provides modeling guidance and domain/business experience to make modifications to the price grades. An Underwriter is responsible for providing the policy terms and pricing for a set of insured entities segmented by certain criteria such as region or industry. The Underwriter’s pricing decisions are at the forefront of the contracting process and are meant to ensure the Insurer is maintaining prescribed profitability at the client-level as well as for the overall book of business the Underwriter is overseeing. He or she will rely on the aforementioned Price Modelers and Pricing Actuaries (with respect to individual policies) for recommendations regarding pricing premiums.

The disconnects that leads to inefficiency

Fundamentally, the biggest cause of friction within the renewal policy process is caused by segmented personnel and outdated forms of data sharing.

Segmented PersonnelThe ultimate end user of this process, Underwriters, are often segmented by geography or industry. However, Price Modelers and Pricing Actuaries typically are aligned by Lines of Business (LOBs). The difference in alignment causes trouble when an Underwriter needs to work on renewal quotes for a client that holds multiple policies or coverages, needing to receive policy-level price suggestions from multiple Price Modelers and Pricing Actuaries from each LOB. The lack of standardization in reporting format can result in high human-error risk when manually pulling and copy/pasting data for a combined-policy renewal quote. A further complication is that varying KPIs across LOBs often make it more complex for an Underwriter to asses the P&L holistically across policies for a single client.

File sharing. The typical flow often involves the creation and sharing of individual files between the individual Pricing Actuaries and Pricing Modelers in several iterations before it is ultimately shared with an Underwriter. Initial modeling requires inputs from the Pricing Actuaries for better guidance. When the baseline risk is scored by Price Modelers, the output of the modeling results will often be shared with the Pricing Actuaries in a file such as Excel. Then, the Pricing Actuaries provide the business/domain-based modifications such as target rate changes to compute the ultimate pricing grade. The spreadsheet is then sent back to the Price Modelers to finalize and distribute the report to the Underwriter. Due to this tedious back and forth, it is common for lines of communication to get tangled and/or pricing errors to occur, due either to version control mistakes in the file sharing, or formula based errors in the spreadsheet files.

In summary, common challenges in the standard method of price grading include, but are not limited, to the following.

  • A significant portion of the copy and pasting (balancing, adjusting, etc) is done by Actuaries. Since the exchange of information happens over a “wide” Excel spreadsheet (with many columns) there is high version control risk.
  • Underwriters tend to approach the problem from an account perspective while the Price Modelers and Pricing Actuaries cover each Line of Business. Consequently, an Underwriter may need to interact with multiple Price Modelers and Actuaries per project.
  • Price Modelers and Actuaries are LOB-based, and because of this, reporting is not consistent across types of policies. As such, it is difficult to analyze account level performance at a glance because it requires a significant amount of time to manipulate, standardize, and analyze data.

Bringing benefits to Underwriters, Price Modelers and Actuaries

ClearGrade is a new app built by Fulcrum Analytics which provides a means for standardization across LOB price grades, an automated summary view at the client level across all policies, and a web-based user interface to control for the errors commonly associated with spreadsheet-based information exchange, among other benefits. In fact, ClearGrade provides Insurers with transparency surrounding all the factors responsible for the performance of an account in the following ways:

  • It allows Underwriters to drill down all the way from book to policy level, not only for price grading, but for the factors that make up the price grade as well
  • It provides Underwriters with scenario planning tools to explore how any adjustment on a policy’s terms or price would impact the accounts’ P&L
  • It allows benchmarking with similar policies to provide additional context in order to support the Underwriter’s decision to renew an account with a particular rate increase.

With ClearGrade, Price Modelers and Actuaries are able to improve operational efficiency and spend more time on analyzing and fine-tuning the baseline risk models:

  • Actuarial inputs are provided seamlessly through the user interface
  • The risk of human-caused error is minimized because the data preparation process is performed programmatically
  • The smooth data extract process reduces manual data inputs
  • Increased transparency of the risk scoring model and process makes it easier for the Underwriters to fully understand the suggested price grades.

If you are in the business of renewing insurance policies, contact us to schedule a ClearGrade demo.

If you are interested in finding ways to turn your data into predictive intelligence or to streamline manual processes, Contact us to find out the ways we can help streamline your business. As always, follow us on Linkedin to see what exciting news/activities we’ll be up to in 2019.

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