Patents by Inventor Elaine C. Marino

Elaine C. Marino has filed for patents to protect the following inventions. This listing includes patent applications that are pending as well as patents that have already been granted by the United States Patent and Trademark Office (USPTO).

  • Patent number: 8290951
    Abstract: Techniques for bridging data from business support units, e.g., call centers and marketing operations, with a data warehouse to augment and enrich pre-existing customer information. Unstructured data is received with incomplete integration information. A data key is created from the unstructured data, and the unstructured data is integrated with the structured data in a data warehouse based on the data key. Unstructured data can assume different forms of data, including recorded audio data, facial image data, and iris image data. At least one customer identifier is extracted from the unstructured data by data mining. A data key is subsequently created from the at least one customer identifier. Incomplete integration may include partial integration information or may not include any integration information.
    Type: Grant
    Filed: July 10, 2008
    Date of Patent: October 16, 2012
    Assignee: Bank of America Corporation
    Inventors: David Joa, Debashish Ghosh, Kurt Newman, Thayer S. Allison, Jr., Elaine C. Marino, Joy M. Tarquin, Maryann Mangini, Yanghong Shao, Mark V. Krein
  • Patent number: 7765139
    Abstract: A data driven and forward looking risk and reward appetite methodology for consumer and small business is described. The methodology includes customer segmentation to create pools of homogeneous assets in terms of revenue and loss characteristics, forward looking simulation to forecast expected values and volatilities of revenue and loss, and risk and reward optimization of the portfolio. One methodology used for modeling revenue and loss is a generalized additive effect decomposition model to fit historical data. Based on the model, a segmentation procedure is performed, which allows for creation of groups of customers with similar revenue and loss characteristics. An estimation procedure for the model is developed and a simulation strategy to forecast and simulate revenue and loss volatility is developed. Efficient frontier curves of risk (e.g., return volatility) and reward (e.g., expected return) are created for the current portfolio under various economic scenarios.
    Type: Grant
    Filed: August 30, 2007
    Date of Patent: July 27, 2010
    Assignee: Bank of America Corporation
    Inventors: Timothy J. Breault, Ulrich A. Bruns, John Delmonico, Shelly X. Ennis, Ruilong He, Glenn B. Jones, WeiCheng Liu, Elaine C. Marino, Arun R. Pinto, Meghan A. Steach, Agus Sudjianto, Naveen G. Yeri, Benhong Zhang, Zhe Zhang, Tony Nobili, Shuchun Wang, Hungjen Wang, Aijun Zhang
  • Publication number: 20090063361
    Abstract: A data driven and forward looking risk and reward appetite methodology for consumer and small business is described. The methodology includes customer segmentation to create pools of homogeneous assets in terms of revenue and loss characteristics, forward looking simulation to forecast expected values and volatilities of revenue and loss, and risk and reward optimization of the portfolio. One methodology used for modeling revenue and loss is a generalized additive effect decomposition model to fit historical data. Based on the model, a segmentation procedure is performed, which allows for creation of groups of customers with similar revenue and loss characteristics. An estimation procedure for the model is developed and a simulation strategy to forecast and simulate revenue and loss volatility is developed. Efficient frontier curves of risk (e.g., return volatility) and reward (e.g., expected return) are created for the current portfolio under various economic scenarios.
    Type: Application
    Filed: August 30, 2007
    Publication date: March 5, 2009
    Applicant: BANK OF AMERICA CORPORATION
    Inventors: Timothy J. Breault, Ulrich A. Bruns, John Delmonico, Shelly X. Ennis, Ruilong He, Glenn B. Jones, WeiCheng Liu, Elaine C. Marino, Arun R. Pinto, Meghan A. Steach, Agus Sudjianto, Naveen G. Yeri, Benhong Zhang, Zhe Zhang, Tony Nobili, Shuchun Wang, Hungjen Wang, Aijun Zhang