# Pricing ### Sample portfolio "what-if" Sticking with watches for now, using generated watch valuations and observed sale data we've been able to analyze the prediction against the achieved sale price (SP) and this can show us the “what-if” insurance book and Gross Loss Ratios (GLR) that our watch valuation services product would have achieved in prior years (albeit with a much smaller portfolio than that proposed).

Figure 1: Simulated insurance book, based on 4,700 transactions 2018 forward

### Assumptions To generate this book several assumptions are needed. Three of these assumptions are: * The valuation price * The ceiling for a single watch * Saleability An average valuation cost 2.5% shows a favorable GLR while providing an attractive valuation services product, and lies in the middle of our assumed achievable rate. Our current model and pricing are designed to provide valuation services backed by warranties for watches from $1k-$200k, however, we are raising the price ceiling as we collect additional data and gain confidence in pricing the higher value end of the market. Our saleability assumption is that all valuation services contracts that offer a valuation of at least 80% of the low estimate would be accepted by the consignor. ### Robust Backtesting We used over \~4,700 records to evaluate our backtest. These \~4,700 records cover models from the top five watch brands: Rolex, Patek Philippe, Cartier, Omega, Audemars Piguet. Giving us a strong representation of the watch models that we expect to be most frequently transacted over. The claims, and therefore GLRs given above are driven by three main observations. Namely: * Claim size * The average size of non-zero claims in relation to the total value protected * Sales frequency * The proportion of the portfolio executing a sale, whether resulting in a claim or not * Claim frequency given sale * The frequency of executed sales that result in a claim

Figure 2: Yearly deviation from the mean in key metrics

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