Revenue Modeling Exercise: Overview Of Sales Process Matrix

Revenue Modeling Exerciseoverview Of Sales Processmatrixs Distributio

Revenue modeling exercise overview of sales process matrix’s distribution model is built upon developing relationships with agencies and brokers located across the US and Canada regions (B2B). The sales organization segments brokers by revenue bands—small, medium, and large—and onboard them onto the sales platform to generate quote submissions. These brokers collaborate with internal teams in security, risk engineering, and customer success to convert quote submissions into policyholders or binds. The conversion rate from quotes to binds is known as the Quote-to-Bind (QtB) ratio. The number of policyholders (bonds) and the average premium per policy determine the total Gross Written Premium (GWP).

Exercise: Using Excel or Google Sheets, forecast a 12-month new business GWP based on key drivers such as brokers, submission volume, QtB ratio, and average premium. The forecast should be segmented into three revenue bands: small, medium, and large. Assume the broker base starts with 1,000 brokers in month 1, with an increase of 100 brokers each month, and incorporate a 0.5% monthly attrition rate. Model the expected renewal GWP based on policies from the previous year, assuming 85% renewal rate and a rate increase that maintains unchanged GWP year-over-year. Next, extend the model into a 24-month P&L, projecting new business and renewals, along with expenses including broker commissions, claims, sales and marketing, research and development, and G&A expenses. The expense assumptions can be based on reasonable estimates, as no specific rates are provided.

Paper For Above instruction

Revenue modeling plays a critical role in strategic planning and financial forecasting for insurance intermediaries such as Managing General Agents (MGAs). This exercise aims to develop a comprehensive 24-month financial forecast by analyzing sales processes, broker engagement, quote-to-bind ratios, renewal rates, and expense allocations. The process involves creating detailed projections for new business, renewals, and associated expenses to inform operational and financial decision-making.

Introduction

The sales process within an MGA relies heavily on establishing strong relationships with agents and brokers across North America, who serve as the primary distribution channel for insurance products. These brokers, segmented by revenue bands—small, medium, and large—are instrumental in generating quote submissions, which are then processed through internal teams to convert into policyholders. Quantifying and modeling this process involves understanding driver metrics such as broker count, quote volume, conversion ratios, and premium rates. Accurate forecasting helps MGAs allocate resources effectively and set strategic goals for growth and profitability.

Modeling the 12-Month New Business GWP Forecast

The first step involves estimating the volume of new business over a 12-month horizon. Starting with 1,000 brokers in month 1, an incremental addition of 100 brokers monthly is assumed, alongside a 0.5% attrition rate to account for broker disengagement or loss. These brokers are evenly distributed across revenue bands, simplifying the assumption that each segment’s base is initially the same. The submission volume per broker, combined with the quote-to-bind ratio—how many quotes convert into policies—and the average premium for each policy, together determine the monthly GWP for each segment.

For the assumptions, suppose each broker submits an average of 10 quotes per month, with a QtB ratio of 20%. The average premium varies by revenue band, with small policies averaging $1,000, medium policies $5,000, and large policies $20,000. By applying these parameters, the forecast estimates the number of policies bound each month across the three segments, summing the resulting premiums for total GWP. The progression over twelve months captures growth and attrition effects, providing a realistic estimate of new business GWP.

Renewal GWP Modeling

Policies typically renew annually, necessitating the modeling of renewal GWP from policies written in the prior year. Assuming an 85% renewal rate, a significant majority of policies are retained monthly. To sustain GWP levels, premiums on renewals are increased at a rate that offsets the natural attrition, keeping GWP stable year-over-year. This approach simplifies revenue estimates by assuming renewal premiums are adjusted proportionally to original premiums, maintaining constant GWP despite policy turnover.

Applying these assumptions involves calculating the renewal base for each month, multiplying the number of policies by the renewal rate, and adjusting premiums accordingly. This process iterates across all months, implementing renewal growth or shrinkage in line with retention rates. This model provides insight into recurring revenue streams and highlights the importance of retention strategies.

Projection of 24-Month P&L

With the detailed forecast of new and renewal GWP, a 24-month income statement can be constructed. The forecast incorporates expenses associated with the sales process and policy issuance, including broker commissions—typically a percentage of GWP; claims costs—also a percentage; and operational expenses such as sales and marketing, research and development, and G&A expenses.

Assuming, for example, broker commissions are 15% of GWP, claims cost 65%, sales and marketing 10%, R&D 5%, and G&A 10%, the model computes these costs monthly based on GWP projections. These expenses are deducted from gross revenue to estimate monthly profit margins. The model should highlight critical drivers of profitability, sensitivities to assumptions, and potential growth bottlenecks.

Extending the model over 24 months allows for analysis of cash flow, profit margins, and return on investment. It also provides a framework for scenario analysis, whereby parameters such as QtB ratio, renewal rate, or expense percentages can be adjusted to assess their impact and guide strategic decision-making.

Conclusion

This comprehensive revenue modeling exercise demonstrates the interconnectedness of sales processes, broker engagement, policy lifecycle, and expense management within an MGA context. Building accurate forecasts equips leadership with vital insights for scaling operations, optimizing resource allocation, and enhancing profitability. The model’s flexibility enables testing different assumptions and preparing for various market conditions, which is essential for sustaining competitive advantage in a dynamic insurance environment.

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