Daniel Lee Hudson

US Patent:

8577776, Nov 5, 2013

Filed:

Sep 14, 2012

Appl. No.:

13/618121

Inventors:

Agus Sudjianto - Matthews NC, US
Michael Chorba - Charlotte NC, US
Daniel Hudson - Charlotte NC, US
Sandi Setiawan - Charlotte NC, US
Jocelyn Sikora - Charlotte NC, US
Harsh Singhal - Charlotte NC, US
Kiran Vuppu - Charlotte NC, US
Kaloyan Mihaylov - New York NY, US
Jie Chen - Charlotte NC, US
Timothy J. Breault - Huntersville NC, US
Arun R. Pinto - Charlotte NC, US
Naveen G. Yeri - Charlotte NC, US
Benhong Zhang - Charlotte NC, US
Zhe Zhang - Charlotte NC, US
Tony Nobili - Charlotte NC, US
Aijun Zhang - Ann Arbor MI, US

Assignee:

Bank of America Corporation - Charlotte NC

International Classification:

G06Q 40/00

US Classification:

705 36R, 705 35

Abstract:

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.

US Patent:

20100293107, Nov 18, 2010

Filed:

Aug 25, 2009

Appl. No.:

12/546807

Inventors:

Agus Sudjianto - Matthews NC, US
Michael Chorba - Charlotte NC, US
Daniel Hudson - Charlotte NC, US
Sandi Setiawan - Charlotte NC, US
Jocelyn Sikora - Charlotte NC, US
Harsh Singhal - Charlotte NC, US
Kiran Vuppu - Charlotte NC, US
Kaloyan Mihaylov - New York NY, US
Jie Chen - Charlotte NC, US
Timothy J. Breault - Huntersville NC, US
Arun R. Pinto - Charlotte NC, US
Naveen G. Yeri - Charlotte NC, US
Benhong Zhang - Charlotte NC, US
Zhe Zhang - Charlotte NC, US
Tony Nobili - Charlotte NC, US
Aijun Zhang - Ann Arbor MI, US

Assignee:

Bank of America Corporation - Charlotte NC

International Classification:

G06Q 40/00

US Classification:

705 36 R

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.