The Top Analytics to Focus On for Improving Underwriting Operations Performance

By Etienne Castonguay, InEdge Partner and Co-founder

Montreal, QC (Aug. 27, 2015) – The stakes are high for underwriting staff and their managers. Occupying a front-line position, underwriters represent an insurance company directly in their daily interactions with current and potential clients. Despite the pressure to achieve sales objectives and ultimately generate profit for the insurer, underwriters must strictly adhere to organizational and underwriting rules before taking on new risk. Underwriting managers, in turn, are tasked with overseeing these dedicated teams whose work can span multiple product lines, while nevertheless being grouped around specialties.

Perhaps because of their crucial, front-line position, measuring the performance of front-office underwriting remains a matter of intense interest. What are the goals and are they being met? What are the most relevant performance metrics, and which can take back seat? Are team overstaffed, understaffed, or is staffing always keeping up with demand peaks?

With these questions in mind, underwriting managers are always seeking to confirm the performance of the teams in their charge. But how do we approach the problem? We can start by breaking down analytics requirements into four distinct area of concern, underwriting managers can gain insight into performance, observe trends as they develop, meet staffing needs, and even provide a starting point for one-on-one annual performance reviews with individual underwriters.

Sales analytics put the focus on all aspect of an underwriting team’s performance and key factors that impact profitability. They help to set and follow growth objectives for teams, brokers, agents and product lines. The metrics that sales analytics should measure include DWP, loss ratios, claim frequency and severity. Sales analytics provide foundational answers such as the sum of direct written premiums during specific periods of time, the number of policies with an in-force status at the end of a given period, and so on.

Quality of Service is an often underdeveloped category of underwriting analytics that nevertheless plays a crucial part in contributing to profitability. For example, QoS measures up-to-date time-to-completion metrics against objectives set by management. But a well-constructed QoS analytics system doesn’t simply measure processing times, client on-hold times, and provide views on target time hits or misses. It ensures efficiency by enforcing quality standards throughout the entire underwriting process. In doing so, it measures and upholds the quality of services offered to brokers, agents and clients.

Productivity analytics are the third area of interest to underwriting managers that see the value in this approach to improving underwriting performance. Productivity analytics handle the short-term decision cycles and assist in adjusting weekly or monthly workloads and staffing needs, for example. Productivity analytics brings both call center an underwriting transactional information together for the purpose of analyzing and adjusting ongoing processes (such as hiring and overtime needs) on an as-needed basis.

For example, Productivity analytics presents information such as the number of pending/finished transactions per day, the percentage of employee time available for calls during specific periods of the day, and so on. While the focus is largely on workflow planning, this information is also useful to assess a team’s performance relative to its peers.

The final analytical category for improving the performance of underwriters is Employee Performance. As implied by the name, these analytics measure the operational efficiency of individual underwriters. In this context, it yields employee-specific information, identifying trends, performance patterns, opportunities for improvement and a good deal more.

For example, how much flex does a particular employee use, overall? What is the hit ratio of a particular employee? Generally speaking Employee analytics let you compare the performance of an employee relative to the rest of the team, based on Sales, QoS and Productivity metrics. They make an excellent starting point for one-on-one discussions between an employee and supervisor.

With underwriting operations widely recognized as occupying a critical position in the insurance value chain, it makes sense to introduce performance analytics into the equation. By focusing on four distinct aspects of underwriting — Sales, Quality of Service, Productivity and — underwriting managers will have a clearer picture of how client calls and transactions are being processed by their underwriting teams.

For more on Underwriting Analytics, download your copy of the white paper Unlocking Underwriting Performance with Analytics.

About the Author

Etienne Castonguay is Partner and Co-founder at InEdge, an insurance Analytics solution provider, where he is responsible for business development and making sure strategies are aligned with the Insurance Industry needs for pre-built Analytics. He has over 25 years of sales and management experience in the distribution of information technology solutions. He previously held various positions with Sybase, Sun Microsystems and Hewlett Packard.

About InEdge

InEdge is a leader in Insurance Analytics solutions. Experienced at quickly leveraging data, InEdge seamlessly and powerfully creates business advantage for its clients. Since its creation in 1994, InEdge has designed and implemented some of the most sophisticated analytical applications available today. Our clients add up to an impressive roster of Property & Casualty and Life Insurance companies. Our Analytics solutions improve and make easier decision-making at all levels for our clients. Visit

Source: InEdge