American Express Travel Related Services Company, Inc.

Wolters Kluwer Elm Solutions, Inc.

Sandeep Sacheti

Deep Thomas

Michael Shamai Oralevich

Manisha Jain

Donald Robert McGimpsey

Narasimha Murthy

Mickey S Oralevich

Sanjay S Agrawal

Karl Von Wolff

Sastry Vsm Durvasula

Vernon Marshall

Sastry V S M Durvasula

Mary Weissman

Chin H Khor

Jeetu Gupta

Janice Law

Jan L Biffle

Catherine B Black

Abhishek Mittal

Florence Merceron

Diane Farrell

Tracy J Steiner

Dennis Lacivita

Michael Mansell

Anand K Ramteke

Sharon Horozaniecki

Michael Mulder

Brent Vallat

A system that enables development and execution of predictive models comprises a centralized data management system, a data extraction tool a model validation tool and a model execution tool. In embodiments, a data management system includes a data management server that can be accessed via a web browser that stores data in the form of a flat file. An extraction tool extracts data. A model validation tool validates a model by scoring an analytical environment data set and a production environment data set. A model execution tool allows a user to select when and how often a model is scored.

Customer behavior predictive modeling

A description of a machine learning (ML) model is received, with the ML model including multiple features such as an unlikely combination feature, which corresponds to a first attribute to be located in an invoice and a second attribute to be located the invoice concurrently with the first attribute. Training data is received, including (i) invoice data with multiple invoices, each including the first attribute and the second attribute, and respective values of the first attribute and the second attribute, and (ii) validity data including indications of which of the invoices are valid and which of the invoices are invalid. The ML model is trained using the training data using the ML model. The training includes applying the values of the attributes to the unlikely combination feature. The ML model is applied to an invoice to be validated to determine a probability that the invoice is invalid.

Accuracy and speed of automatically processing records in an automated environment

Predictive modeling

Infrastructure and architecture for development and execution of predictive models

A system that enables development and execution of predictive models comprises a centralized data management system, a data extraction tool a model validation tool and a model execution tool. In embodiments, a data management system includes a data management server that can be accessed via a web browser that stores data. An extraction tool includes a data filter adapted to filter data based on, for example, a population criteria, a sample size, and a date range criteria. A model validation tool validates the model. A model execution tool allows a user to score the model.

A system and method for viewing models and model variables within a sophisticated modeling environment is disclosed. The system provides varying levels of insight into a modeling infrastructure to help the user understand model and model variable dependencies, usage, distribution, and/or the like. The method includes storing model and model variable data within a relational database system, receiving a request from a user interfacing with the system via a web interface, extracting search criteria and presentation preferences from the request, formulating and executing one or more queries on the database to retrieve the required data, formatting the data in accordance with the request, and returning the data to the requesting user in the form of a web page.

System and method for evaluation decision sciences of simulation models

Systems and methods that identify and manage partner relationships are disclosed. A third-party trustee collects and processes confidential customer information from more than one interested parties. The third-party trustee acts as a neutral intermediary between the parties. The third-party trustee processes and analyzes the information received from the various parties to identify mutual and/or prospective customers between the interested parties. The processing results may then be used for further analysis to help at least one of the interested parties to improve their marketing efforts, risk management, and servicing of their customers.

Identifying and managing strategic partner relationships

A system and method for viewing models and model variables within a sophisticated modeling environment is disclosed. The system provides varying levels of insight into a modeling infrastructure to help the user understand model and model variable dependencies, usage, distribution, and/or the like. (original) The method includes storing model and model variable data within a relational database system, receiving a request from a user interfacing with the system via a web interface, extracting search criteria and presentation preferences from the request, formulating and executing one or more queries on the database to retrieve the required data, formatting the data in accordance with the request, and retuning the data to the requesting user in the form of a web page.

A system and method for viewing models and model variables within a sophisticated modeling environment is disclosed. The system provides varying levels of insight into a modeling infrastructure to help the user understand model and model variable dependencies, usage, distribution, and/or the like. The method includes storing model and model variable data within a relational database system, receiving a request from a user interfacing with the system via a web interface, extracting search criteria and presentation preferences from the request, formulating and executing one or more queries on the database to retrieve the required data, formatting the data in accordance with the request, and retuning the data to the requesting user in the form of a web page.

System and method for determining resource allocation among simulation models

System and method for analysis and maintenance of simulation models

System and method for evaluating simulation model penetration

Growing community of inventors

Edison, NJ, United States of America

Sandeep Sacheti