Abstract: A computer for displaying an evaluation tool for evaluating a proposed fee on behalf of a professional, including a memory having at least one region for storing computer executable program code and a processor for executing the program code stored in the memory. The program code includes code for receiving a product type for a proposed client account, a proposed fee for the proposed client account, and at least one of the following numerical parameters: (i) an account asset amount for the proposed client account, (ii) a relationship asset amount for the proposed client account, and (iii) a breakdown of components in an asset mix for the proposed client account. A range of historical fees of the nearest neighbor historical accounts is shown on a graph from lowest to highest, and the proposed fee is shown on the graph relative to the nearest neighbor historical fees.

Abstract: A method of computer-assisted price modeling is provided, which uses a reference price to assist in evaluating discretionary pricing of transactional services provided (i) by a professional among his own transactions or (ii) by a target professional among others' transactions. A universe of pricing episode data is segmented into groupings based on price predictive parameters. These data are then arranged in each grouping according to price. A reference price is determined within each grouping based on a predetermined level, rank or percentile. This reference price can then be used to evaluate the pricing episode data and provide various calculations or comparisons, including the revenue opportunity that could have been obtained by pricing at the reference price.

Abstract: A method of computer-assisted price modeling is provided, which uses a reference price to assist in evaluating discretionary pricing of transactional services provided (i) by a professional among his own transactions or (ii) by a target professional among others' transactions. A universe of pricing episode data is segmented into groupings based on price predictive parameters. These data are then arranged in each grouping according to price. A reference price is determined within each grouping based on a predetermined level, rank or percentile. This reference price can then be used to evaluate the pricing episode data and provide various calculations or comparisons, including the revenue opportunity that could have been obtained by pricing at the reference price.

Abstract: A method of computer-assisted price modeling is provided, which uses a reference price to assist in evaluating discretionary pricing of transactional services provided (i) by a professional among his own transactions or (ii) by a target professional among others' transactions. A universe of pricing episode data is segmented into groupings based on price predictive parameters. These data are then arranged in each grouping according to price. A reference price is determined within each grouping based on a predetermined level, rank or percentile. This reference price can then be used to evaluate the pricing episode data and provide various calculations or comparisons, including the revenue opportunity that could have been obtained by pricing at the reference price.

Abstract: A method of computer-assisted price modeling is provided, which uses a reference price to assist in evaluating discretionary pricing of transactional services provided (i) by a professional among his own transactions or (ii) by a target professional among others' transactions. A universe of pricing episode data is segmented into groupings based on price predictive parameters. These data are then arranged in each grouping according to price. A reference price is determined within each grouping based on a predetermined level, rank or percentile. This reference price can then be used to evaluate the pricing episode data and provide various calculations or comparisons, including the revenue opportunity that could have been obtained by pricing at the reference price.

Abstract: A securities transaction performance framework for developing an evaluation system directed toward the securities industry. The framework comprises a compilation of Broker demographics, a compilation of Broker performance data, a compilation of Client Portfolio information, and a compilation of periodic Transaction data including volume of Transactions, commission charged, and associated Broker information. The data compilations interface with a Broker Master to correlate a Broker to a statistical database as requested by the user. The Broker Master correlates financial statistics from Transaction data to Broker demographics and performance data so as to provide a performance evaluation system. Transaction data is stored in a secure environment and is able to provide historical analysis upon request of the end user.