Christopher Donald Johnson - Clifton Park NY, US Tim Kerry Keyes - West Redding CT, US Marc Thomas Edgar - Glenmont NY, US Chandrasekhar Pisupati - Niskayuna NY, US William Cree Steward - Norwalk CT, US
Assignee:
GE Capital Commercial Finance, Inc. - Stamford CT
International Classification:
G06F 17/60
US Classification:
705 36R, 705 38, 705 37
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.
Methods And Systems For Efficiently Sampling Portfolios For Optimal Underwriting
Tim Kerry Keyes - West Redding CT, US Christopher Donald Johnson - Clifton Park NY, US Richard Paul Messmer - Rexford NY, US Marc Thomas Edgar - Glenmont NY, US Navneet Kapoor - Tokyo, JP
Assignee:
GE Capital Commercial Finance, Inc. - Stamford CT
International Classification:
G06F 17/60
US Classification:
705 36, 705 37
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.
Multivariate Responses Using Classification And Regression Trees Systems And Methods
The present invention is a method of allowing inclusion of more than one variable in a Classification and Regression Tree (CART) analysis. The method includes predicting y using p exploratory variables, where y is a multivariate, continuous response vector, describing a probability density function at “parent” and “child” nodes using a multivariate normal distribution, which is a function of y, and defining a split function where “child” node distributions are individualized, compared to the parent node. In one embodiment a system is configured to implement the multivariate CART analysis for predicting behavior in a non-performing loan portfolio.
Methods And Systems For Finding Value And Reducing Risk
Richard Paul Messmer - Rexford NY, US Christopher Donald Johnson - Clifton Park NY, US Tim Kerry Keyes - West Redding CT, US William Cree Steward - Norwalk CT, US Marc Thomas Edgar - Glenmont NY, US
Assignee:
GE Capital Commercial Finance, Inc. - Stamford CT
International Classification:
G06F 17/60
US Classification:
705 35, 705 38
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.
Methods And Systems For Automated Inferred Valuation Of Credit Scoring
Christopher Donald Johnson - Clifton Park NY, US Marc Thomas Edgar - Glenmont NY, US Tim Kerry Keyes - West Redding CT, US
Assignee:
GE Capital Commerical Finance, Inc. - Stamford CT
International Classification:
G06F 17/60
US Classification:
705 36, 705 37
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.
Rapid Valuation Of Portfolios Of Assets Such As Financial Instruments
Christopher Donald Johnson - Clifton Park NY, US Tim Kerry Keyes - West Redding CT, US David Jonathan Spencer - Bangkok, TH Catharine Lynn Midkiff - Bangkok, TH Richard Paul Messmer - Rexford NY, US Chandrasekhar Pisupati - Niskayuna NY, US Yu-to Chen - San Ramon CA, US Marc Thomas Edgar - Glenmont NY, US James Louis Cifarelli - Schenectady NY, US Kunter Seref Akbay - Niskayuna NY, US Vrinda Rajiv - Guilderland NY, US David Richard Nelson - Alpharetta GA, US William Cree Steward - Norwalk CT, US
Assignee:
GE Capital Commercial Finance, Inc. - Stamford CT
International Classification:
G06F 17/60
US Classification:
705 36R, 705 35, 705 37, 706 8
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.
Methods And Systems For Optimizing Return And Present Value
Christopher Donald Johnson - Clifton Park NY, US Marc Thomas Edgar - Glenmont NY, US Tim Kerry Keyes - West Redding CT, US
Assignee:
GE Capital Commercial Finance, Inc. - Stamford CT
International Classification:
G06Q 40/00
US Classification:
705 37, 705 38
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 statistical evaluation of all assets and statistical inferences drawn from the evaluation and applied to generate inferred values. Individual asset values are developed and listed in tables so that individual asset values can be taken and quickly grouped in any desired or prescribed manner for bidding purposes. The assets are collected into a database, divided 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 valuation established by cumulating the individual valuations.
Methods And Systems For Modeling Using Classification And Regression Trees
A method of valuation of large groups of assets using classification and regression trees is described. The method includes defining relevant portfolio segmentations, assessing performance of the classification and regression tree based model against a simple model and ranking all portfolio segments based upon performance of the models. Iterative and adaptive statistical evaluation of all assets and statistical inferences are used to generate the segmentations. The assets are collected into a database, grouped by credit variable, subdivided by ratings as to those variables and then rated individually. The assets are then regrouped and a collective valuation is established by cumulating individual valuations.
The MEDC (Michigan Economic Development Corp.) and the airport came to ask if we would help incentivize the project, said Tim Keyes, economic development director for Romulus. They asked for an abatement. We offered a 10-year abatement and they came back and asked if wed be willing to up it to 1
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