Abstract: A method of valuation of large groups of assets by a partial full underwriting, partial sample underwriting and inferred valuation of the remainder using an iterative and adaptive statistical evaluation of all assets and statistical inferences drawn from the evaluation and applied to generate inferred asset values. Individual asset values are developed and listed so that individual asset values can be rapidly taken and quickly grouped in any manner for bidding purposes. The assets are collected into a database, divided into categories, subdivided by ratings and then rated individually. Asset value is continuously recalculated based on progressively improving asset valuation data. The assets are then regrouped for bidding and a collective valuation is established by cumulating individual valuations.

Abstract: A method of valuation of large groups of assets by partial full underwriting, partial sample underwriting and inferred values of the remainder using an iterative and adaptive supervised and unsupervised statistical evaluation of all assets and statistical inferences drawn from the evaluation and applied to generate the inferred asset values. Individual asset values are developed and listed in relational tables so that individual asset values can be rapidly taken from the tables and quickly grouped in any desired or prescribed manner for bidding purposes. The assets are collected into a database, divided into categories by credit variable, subdivided by ratings as to those variables and then rated individually. The assets are then regrouped according to a bidding grouping and a collective valuations established by cumulating the individual valuations.

Abstract: A method of valuation of large groups of assets using an iterative and adaptive statistical evaluation to generate asset values is described. Individual asset values are developed and listed so that individual asset values can be rapidly taken and quickly grouped in any desired or prescribed manner for bidding purposes. One method of automated underwriting includes defining clusters of financial instruments by common attributes, receiving an expert opinion of value from selected samples of the clusters, checking values for combinations of attributes and reconciling the values. A collective valuation of the assets is established by cumulating the individual valuations.

Abstract: In a system and method for saving and retrieving process capability and guidance information related to supporting product design and manufacturing activities, specific capability and guidance information related to sets of standardized product attributes are collected and stored as a plurality of records in a database. A user may then access the database through a suitable computer program interface and design a product using any combination of standardized attributes. Upon each attribute selection, the system queries the database and retrieves the process capability and guidance information associated with the received set of attributes. This information is then displayed to the user to assist in product design and manufacturing activities. Users may also group information retrieved relating to various sets of attributes and generate composite checklists including ranked listings of relevant guidance information.

Abstract: A method for providing producibility information to a user during a design process includes providing process capability models with integrated coaching information and providing a producibility evaluation worksheet having at least one input and at least one output, the input being selectable to represent a specific design. The worksheet is initialized with a relevant process capability model that is used to determine a producibility measure indicating an effect of the input on the output. The producibility measure is then displayed to the user.

Abstract: A method of inferring valuation of large groups of assets by credit scores includes the steps of organizing valuation scores, adjusting valuation scores based on special factors and business decisions, reconciling multiple valuation scores which describe the same assets and making an overall adjustment to override the inferred valuation. Individual asset values are developed and listed in tables so that individual asset values can be rapidly taken from the tables and quickly grouped for bidding purposes. The valuations are collected into a database, divided into categories by credit variable, subdivided by ratings as to those variables and then rated individually.

Abstract: A method of valuation of large groups of assets by partial full underwriting, partial sample underwriting and inferred values of the remainder using an iterative and adaptive supervised and unsupervised statistical evaluation of all assets and statistical inferences drawn from the evaluation and applied to generate the inferred asset values. Individual asset values are developed and listed in relational tables so that individual asset values can be rapidly taken from the tables and quickly grouped in any desired or prescribed manner for bidding purposes. The assets are collected into a database, divided into categories by credit variable, subdivided by ratings as to those variables and then rated individually. The assets are then regrouped according to a bidding grouping and a collective valuations established by cumulating the individual valuations.

Abstract: An integrated system organizes a company's experiences, operating procedures, best practices, information sources, competitive information and analytical tools. The goal is increasing profitability within a due diligence process while facilitating ongoing operations. The system incorporates a method for collaborating on due diligence issues to affect knowledge building within due diligence teams. The method includes accessing stored, accumulated knowledge in a repository from prior due diligence exercises, applying to due diligence decisions criteria based on consolidated analytical building blocks of past due diligence exercises and storing newly accumulated knowledge from the current due diligence exercise into the repository of accumulated knowledge. Access to this information is available globally via the internet as well as locally.

Abstract: An integrated system organizes a company's experiences, operating procedures, best practices, information sources, competitive information and analytical tools. The goal is increasing profitability within a due diligence process while facilitating ongoing operations. The system incorporates a method for collaborating on due diligence issues to affect knowledge building within due diligence teams. The method includes accessing stored, accumulated knowledge in a repository from prior due diligence exercises, applying to due diligence decisions criteria based on consolidated analytical building blocks of past due diligence exercises and storing newly accumulated knowledge from the current due diligence exercise into the repository of accumulated knowledge.

Abstract: A method of valuation of large groups of assets using an iterative and adaptive statistical evaluation to generate asset values is described. Individual asset values are developed and listed so that individual asset values can be rapidly taken and quickly grouped in any desired or prescribed manner for bidding purposes. One method of automated underwriting includes defining clusters of financial instruments by common attributes, receiving an expert opinion of value from selected samples of the clusters, checking values for combinations of attributes and reconciling the values. A collective valuation of the assets is established by cumulating the individual valuations.

Abstract: The cross correlation tool is used to quickly understand and describe the composition of an asset portfolio and the response of a user selected variable versus other variables in the portfolio. The tool is also used to quickly identify unexpectedly high or low correlation between two attribute variables and the response variable. Identification of unexpected correlations improves understanding of the portfolio data and the decisions regarding a potential purchase of the portfolio. Attribute variables are of two types, continuous and categorical. The cross correlations are computed between all variables of interest and their bin or level and presented in a two dimensional matrix for easy identification of trends.

Abstract: A method of valuation of large groups of assets by partial full underwriting, partial sample underwriting and inferred values of the remainder using an iterative and adaptive supervised and unsupervised statistical evaluation of all assets and statistical inferences drawn from the evaluation and applied to generate the inferred asset values. Individual asset values are developed and listed in realtional tables so that individual asset values can be rapidly taken from the tables and quickly grouped in any desired or prescribed manner for bidding purposes.. The assets are collected into a database, divided into categories by credit variable, subdivided by ratings as to those variables and then rated individually. The assets are then regrouped according to a bidding grouping and a collective valuations established by cumulating the individual valuations.

Abstract: A method of valuation of large groups of assets by a partial full underwriting, partial sample underwriting and inferred valuation of the remainder using an iterative and adaptive statistical evaluation of all assets and statistical inferences drawn from the evaluation and applied to generate inferred asset values. Individual asset values are developed and listed so that individual asset values can be rapidly taken and quickly grouped in any manner for bidding purposes.. The assets are collected into a database, divided into categories, subdivided by ratings and then rated individually. Asset value is continuously recalculated based on progressively improving asset valuation data. The assets are then regrouped for bidding and a collective valuation is established by cumulating individual valuations.

Abstract: A method of valuation of groups of assets by partial full underwriting, partial sample underwriting and inferred values of the remainder using an iterative and adaptive statistical evaluation of all assets. Statistical inferences drawn from the evaluation are applied to generate the inferred values. The assets are collected into a database, catagorized, subdivided by ratings as to those variables and then rated individually. The assets are then regrouped according to a bidding grouping and a collective valuation is established. Simulated bid scenarios are examined for combinations of bid prices and a best bid price according to risk and return is determined.