公开(公告)号：CA2713597A1

公开(公告)日：2011-02-25

申请号：CA2713597

申请日：2010-08-20

Applicant: BANK OF AMERICA

Inventor： SUDJIANTO AGUS ,  CHORBA MICHAEL ,  HUDSON DANIEL ,  SETIAWAN SANDI ,  SIKORA JOCELYN ,  SINGHAL HARSH ,  VUPPU KIRAN ,  MIHAYLOV KALOYAN ,  CHEN JIE ,  BREAULT TIMOTHY J ,  PINTO ARUN R ,  YERI NAVEEN G ,  ZHANG BENHONG ,  ZHANG ZHE ,  NOBILI TONY ,  WANG HUNGIEN ,  ZHANG AIJUN

IPC: G06Q10/00 ,  G06Q40/00

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.

公开(公告)号：GB2471317A

公开(公告)日：2010-12-29

申请号：GB0911028

申请日：2009-06-25

Applicant: BANK OF AMERICA

Inventor： PORTS PRESTON W ,  GHOSH DEBASHIS ,  LIU WELCHENG ,  SUDJIANTO AGUS ,  CHEN JIE ,  ALLISON THAYER ,  JOFFE DAVID ,  AMIN MACK ,  PAWAR SAMIR ,  QUINN MATT

IPC: G06Q40/00

Abstract: A method for providing decision support systems using customer clustering comprises obtaining customer transaction data (e.g. internal-external customer transaction data, credit card information, customer funds ( income)), and categorising it. The categorised customer transaction data is analysed to identify patterns among the data. The identified patterns are used to isolate a selected number of behavioural factors. The customers are grouped into population segments based on the behavioural factors. Any non-linear transaction data may be analysed using a Hidden Markov method. The behavioural segments may be visually presented in a graph (Fig. 3). The decision support system may be used to provide more directed and accurate offers to customers thus improving the customer experience.