Bank of America Corporation

Arun Pinto

Debashis Ghosh

Kurt Newman

Sudeshna Banerjee

William Anthony Nobili

David Joa

Naveen Gururaja Yeri

Agus Sudjianto

Thayer S Allison

David Neil Joffe

Yanghong Shao

Timothy John Breault

Aijun Zhang

Benhong Zhang

Zhe Zhang

Mark V Krein

Jie Chen

Harsh Singhal

Sandi Setiawan

Preston Wesley Ports, Iii

Marc Douglas Halsted

Kaloyan Mihaylov

Daniel Hudson

Jocelyn Sikora

Kiran Vuppu

Hungien Wang

Michael Chorba

Meghan Alita Steach

Elaine C Marino

Robert Caruso

Vipin Ramani

Ulrich A Bruns

John Delmonico

Shelly X Ennis

Ruilong He

Glenn B Jones

WeiCheng Liu

Shuchun Wang

Hungjen Wang

Kris Gagnon

Bridget Garavalia

Hetty E Harlan

Michael McKay

Jackie Noble

Apparatus and methods for processing a loan application. The apparatus and methods may involve accessing a financial institution customer account that includes a plurality of transactions; identifying those transactions that belong to a predetermined transaction category; and summarizing the transactions. Summary information may be presented as part of an income and expenses flow report that at least partially characterizes the account or the applicant. A financial institution representative may query a database for the summary information and, optionally, initiate an underwriting process based on the loan application and the summary information.

Apparatus and methods for verifying a credit applicant's income that enhance a credit applicant's experience

Systems, methods, and computer program products are provided for optimizing amounts collected in an offset action where a creditor attaches funds from a debtor's deposits account to satisfy overdue debt payments. In operation, embodiments of the present invention leverage a deposits account's transaction history to detect a deposit pattern for the account and, based on the detected pattern, predict the date of the next large deposit to the attachable account. An offset associate, using the present invention, can then schedule the offset action to occur on the expected date of the next large deposit.

Offset optimization system

A data driven and forward looking risk and reward appetite methodology for consumer and small business is described. The methodology includes account level historical data collection for customers associated with accounts as part of a portfolio. The account level historical data is segmented into groups of customers with similar revenues and loss characteristics. Segmented data is decomposed into seasoning, vintage, and cycle effects. Statistical clusters are formed based upon the data and effects. A simulation is applied to the statistical clusters and prediction data is generated. 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.

Risk and reward assessment mechanism

Aspects of the invention provide for the use of transactional data in determining credit and product offerings. Further aspects of the invention provide for generating financial statements and indices using transactional data for use by users and/or financial institutions. The transactional based financial statements and indices may be used for making underwriting and financial planning decisions.

Calculating credit worthiness using transactional data

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.

A method to trigger credit actions may include determining a quantity of triggers flagged for a selected creditor. The method may also include establishing an action plan in response to the quantity of flagged triggers being greater than the predetermined number. In accordance with another embodiment of the present invention, a system to trigger credit actions may include a processor and at least one trigger. The system may also include a credit action program operable on the processor to generate a sires of inquiries and to determine a quantity of the at least one trigger being flagged based on the responses to the series of inquiries for a selected creditor.

Method and system to manage a credit portfolio and to trigger credit actions

Systems, methods, and computer program products are provided for optimizing amounts collected in an offset action where a creditor garnishes funds from a debtor's deposits account to satisfy delinquent debt payments. In operation, embodiments of the present invention leverage a deposits account's transaction history to detect a deposit pattern for the account and, based on the detected pattern, predict the date of the next large deposit to the garnishable account. An offset associate, using the present invention, can then schedule the offset action to occur on the expected date of the next large deposit.

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New York, NY, United States of America

Arun Pinto