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公开(公告)号：US08396789B1
公开(公告)日：2013-03-12
申请号：US12651666
申请日：2010-01-04
IPC分类号： G06Q40/00
CPC分类号： G06Q40/025
摘要： Embodiments of the present invention evaluate consumer spending and borrowing patterns and, based thereon, forecast changes in consumer failure to repay rates. Embodiments of the present invention then develop macroeconomic variables that reflect the forecasted changes in consumer failure to repay rates and implement those macroeconomic variables into credit-approval decision models. The implemented macroeconomic variables adjust the decision models' credit-approval thresholds to account for the forecasted changes in consumer failure to repay rates. For example, if forecasts indicate decreasing credit failure to repay rates, then macroeconomic variables are developed and implemented in decision models to reduce credit-approval thresholds, thereby reducing qualifying creditworthiness scores and making it easier to get credit. On the other hand, for example, if forecasts indicate increasing credit failure to repay rates, then macroeconomic variables are developed and implemented in decision models to increase credit-approval thresholds, thereby restricting access to credit and reducing future losses from consumer failures to repay.
摘要翻译： 本发明的实施例评估消费者支出和借款模式，并据此预测消费者未能偿还差价的变化。 然后，本发明的实施例开发出反映消费者未能偿还利率的预测变化的宏观经济变量，并将这些宏观经济变量实施为信用审批决策模型。 实施的宏观经济变量调整决策模型的信用审批阈值，以解决消费者未能偿还利率的预测变化。 例如，如果预测表明信贷未能偿还利率下降，则在决策模型中制定和实施宏观经济变量，以减少信贷审批门槛，从而降低合格信用评分，并使其更容易获得信贷。 另一方面，例如，如果预测表明贷款利率不断下降，那么在决策模型中制定和实施宏观经济变量，以增加信贷审批阈值，从而限制信贷获取和减少未来消费者未偿还的损失。
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公开(公告)号：US08533082B1
公开(公告)日：2013-09-10
申请号：US12541728
申请日：2009-08-14
申请人： Agus Sudjianto , Jie Chen , Meghan Alita Steach
发明人： Agus Sudjianto , Jie Chen , Meghan Alita Steach
IPC分类号： G06Q40/00
CPC分类号： G06Q40/00 , G06Q40/025
摘要： Embodiments of the present invention relate to systems, methods and computer program products that model consumer leverage and provide a leading indicator that predicts increases or decreases in consumer net non-collectibles. To do so, for example, the present invention determines the growth of consumers' spending and borrowing, and tracks a relationship between the value of a ratio that compares consumers' spending and borrowing and the value of the equilibrium of the ratio that compares consumers' spending and borrowing. This relationship is then applied to predict changes in consumers' ability to repay borrowed funds and consumer net non-collectibles.
摘要翻译： 本发明的实施例涉及模拟消费者杠杆的系统，方法和计算机程序产品，并提供预测消费者非收集品的增加或减少的主要指标。 例如，本发明确定了消费者支出和借款的增长，并追踪了比较消费者支出与借款的比率价值与比较消费者比例平衡的价值之间的关系。 消费和借款。 然后将这种关系用于预测消费者偿还借款资金和消费者非收藏品的能力变化。
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公开(公告)号：US20130073481A1
公开(公告)日：2013-03-21
申请号：US13618121
申请日：2012-09-14
申请人： Agus Sudjianto , Michael Chorba , Daniel Hudson , Sandi Setiawa , Jocelyn Sikora , Harsh Singhal , Kiran Vuppo , Kaloyan Mihaylov , Jie Chen , Timothy J. Breault , Arun R. Pinto , Naveen G. Yeri , Benhong Zhang , Zhe Zhang , Tony Nobili , Hungien Wang , Aijun Zhang
发明人： Agus Sudjianto , Michael Chorba , Daniel Hudson , Sandi Setiawa , Jocelyn Sikora , Harsh Singhal , Kiran Vuppo , Kaloyan Mihaylov , Jie Chen , Timothy J. Breault , Arun R. Pinto , Naveen G. Yeri , Benhong Zhang , Zhe Zhang , Tony Nobili , Hungien Wang , Aijun Zhang
IPC分类号： G06Q40/06
摘要： 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.
摘要翻译： 描述了消费者和小企业的数据驱动和前瞻性风险和奖励食欲方法。 该方法包括与帐户相关联的客户的帐户级历史数据收集作为投资组合的一部分。 账户级别的历史数据被分为具有相似收入和损失特征的客户群体。 分段数据分解为调味料，复古和循环效应。 基于数据和效果形成统计群集。 将仿真应用于统计集群，生成预测数据。 开发了一种预测和模拟收入和损失波动率的模拟策略。 在各种经济情景下为当前投资组合创建有效的边际风险曲线（例如回报波动性）和报酬（例如预期收益）。
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4.发明申请DECISION SUPPORT SYSTEMS USING MULTI-SCALE CUSTOMER AND TRANSACTION CLUSTERING AND VISUALIZATION 审中-公开使用多尺度客户和交易分类和可视化的决策支持系统公开(公告)号：US20090327036A1
公开(公告)日：2009-12-31
申请号：US12206103
申请日：2008-09-08
申请人： Preston W. Ports, III , Debashis Ghosh , Weicheng Liu , Agus Sudjianto , Jie Chen , Thayer Allison , David Joffe , Mack Amin , Samir Pawar , Matt Quinn
发明人： Preston W. Ports, III , Debashis Ghosh , Weicheng Liu , Agus Sudjianto , Jie Chen , Thayer Allison , David Joffe , Mack Amin , Samir Pawar , Matt Quinn
IPC分类号： G06Q10/00
摘要： Systems, methods and consumer-readable media for using multi-scale customer and transaction clustering and visualization according to the invention have been provided. Systems and methods according to the invention may use program code to obtain customer transaction data and categorize obtained customer transaction data. The systems and methods may also analyze the categorized customer transaction data in order to identify patterns among the data. The systems and methods may also use the identified patterns to isolate a selected number of behavioral factors and group customers into population segments based on the behavioral factors.
摘要翻译： 已经提供了根据本发明的用于使用多尺度客户和事务集群和可视化的系统，方法和消费者可读介质。 根据本发明的系统和方法可以使用程序代码来获得客户交易数据并对获得的客户交易数据进行分类。 系统和方法还可以分析分类的客户交易数据，以便识别数据中的模式。 系统和方法还可以使用所识别的模式来基于行为因素来隔离选定数量的行为因素并将客户群组合成群体段。
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公开(公告)号：US08577776B2
公开(公告)日：2013-11-05
申请号：US13618121
申请日：2012-09-14
申请人： Agus Sudjianto , Michael Chorba , Daniel Hudson , Sandi Setiawan , Jocelyn Sikora , Harsh Singhal , Kiran Vuppu , Kaloyan Mihaylov , Jie Chen , Timothy J. Breault , Arun R. Pinto , Naveen G. Yeri , Benhong Zhang , Zhe Zhang , Tony Nobili , Hungien Wang , Aijun Zhang
发明人： Agus Sudjianto , Michael Chorba , Daniel Hudson , Sandi Setiawan , Jocelyn Sikora , Harsh Singhal , Kiran Vuppu , Kaloyan Mihaylov , Jie Chen , Timothy J. Breault , Arun R. Pinto , Naveen G. Yeri , Benhong Zhang , Zhe Zhang , Tony Nobili , Hungien Wang , Aijun Zhang
IPC分类号： G06Q40/00
摘要： 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.
摘要翻译： 描述了消费者和小企业的数据驱动和前瞻性风险和奖励食欲方法。 该方法包括与帐户相关联的客户的帐户级历史数据收集作为投资组合的一部分。 账户级别的历史数据被分为具有相似收入和损失特征的客户群体。 分段数据分解为调味料，复古和循环效应。 基于数据和效果形成统计群集。 将仿真应用于统计集群，生成预测数据。 开发了一种预测和模拟收入和损失波动率的模拟策略。 在各种经济情景下为当前投资组合创建有效的边际风险曲线（例如回报波动性）和报酬（例如预期收益）。
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公开(公告)号：US08423454B2
公开(公告)日：2013-04-16
申请号：US13344709
申请日：2012-01-06
申请人： Jie Chen , Timothy John Breault , Fernando Cela Diaz , William Anthony Nobili , Sandi Setiawan , Harsh Singhal , Agus Sudjianto , Andrea Renee Turner , Bradford Timothy Winkelman
发明人： Jie Chen , Timothy John Breault , Fernando Cela Diaz , William Anthony Nobili , Sandi Setiawan , Harsh Singhal , Agus Sudjianto , Andrea Renee Turner , Bradford Timothy Winkelman
IPC分类号： G06Q40/00
CPC分类号： G06Q10/067 , G06Q40/00
摘要： Embodiments of the present invention relate to methods and apparatuses for determining leading indicators and/or for modeling one or more time series. For example, in some embodiments, a method is provided that includes: (a) receiving first data indicating the value of a total income amount for a plurality of consumers over a period of time; (b) receiving second data indicating the value of a total debt amount for a plurality of consumers over a period of time; (c) selecting a consumer leverage time series that compares the total income amount to the total debt amount over a period of time; (d) modeling the consumer leverage time series based at least partially on the first and second data; (e) determining, using a processor, the value of the cycle component for a particular time; and (f) outputting an indication of the value of the cycle component for the particular time.
摘要翻译： 本发明的实施例涉及用于确定前导指示符和/或建模一个或多个时间序列的方法和装置。 例如，在一些实施例中，提供了一种方法，其包括：（a）在一段时间内接收指示多个消费者的总收入金额的值的第一数据; （b）在一段时间内接收表示多个消费者的总债务金额的第二数据; （c）选择消费者杠杆时间序列，将总收入与一段时间内的债务总额进行比较; （d）至少部分地基于第一和第二数据对消费者杠杆时间序列进行建模; （e）使用处理器确定特定时间的周期分量的值; 和（f）输出特定时间的循环分量的值的指示。
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公开(公告)号：US08326723B2
公开(公告)日：2012-12-04
申请号：US12546807
申请日：2009-08-25
申请人： Agus Sudjianto , Michael Chorba , Daniel Hudson , Sandi Setiawan , Jocelyn Sikora , Harsh Singhal , Kiran Vuppu , Kaloyan Mihaylov , Jie Chen , Timothy J. Breault , Arun R. Pinto , Naveen G. Yeri , Benhong Zhang , Zhe Zhang , Tony Nobili , Hungien Wang , Aijun Zhang
发明人： Agus Sudjianto , Michael Chorba , Daniel Hudson , Sandi Setiawan , Jocelyn Sikora , Harsh Singhal , Kiran Vuppu , Kaloyan Mihaylov , Jie Chen , Timothy J. Breault , Arun R. Pinto , Naveen G. Yeri , Benhong Zhang , Zhe Zhang , Tony Nobili , Hungien Wang , Aijun Zhang
IPC分类号： G06Q40/00
摘要： 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.
摘要翻译： 描述了消费者和小企业的数据驱动和前瞻性风险和奖励食欲方法。 该方法包括客户细分，以便在收入和损失特征方面创建同质资产池，前瞻性模拟以预测收益和损失的预期值和波动率，以及投资组合的风险和报酬优化。 用于建模收入和损失的一种方法是广义加和效应分解模型，以适应历史数据。 基于该模型，执行分割程序，其允许创建具有类似收入和损失特征的客户群体。 开发了模型的估计程序，并开发了一种预测和模拟收入和损失波动性的模拟策略。 在各种经济情景下为当前投资组合创建有效的边际风险曲线（例如回报波动性）和报酬（例如预期收益）。
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公开(公告)号：US20120173399A1
公开(公告)日：2012-07-05
申请号：US13344709
申请日：2012-01-06
申请人： Jie Chen , Timothy John Breault , Fernando Cela Diaz , William Anthony Nobili , Sandi Setiawan , Harsh Singhal , Agus Sudjianto , Andrea Renee Turner , Bradford Timothy Winkelman
发明人： Jie Chen , Timothy John Breault , Fernando Cela Diaz , William Anthony Nobili , Sandi Setiawan , Harsh Singhal , Agus Sudjianto , Andrea Renee Turner , Bradford Timothy Winkelman
CPC分类号： G06Q10/067 , G06Q40/00
摘要： Embodiments of the present invention relate to methods and apparatuses for determining leading indicators and/or for modeling one or more time series. For example, in some embodiments, a method is provided that includes: (a) receiving first data indicating the value of a total income amount for a plurality of consumers over a period of time; (b) receiving second data indicating the value of a total debt amount for a plurality of consumers over a period of time; (c) selecting a consumer leverage time series that compares the total income amount to the total debt amount over a period of time; (d) modeling the consumer leverage time series based at least partially on the first and second data; (e) determining, using a processor, the value of the cycle component for a particular time; and (f) outputting an indication of the value of the cycle component for the particular time.
摘要翻译： 本发明的实施例涉及用于确定前导指示符和/或建模一个或多个时间序列的方法和装置。 例如，在一些实施例中，提供了一种方法，其包括：（a）在一段时间内接收指示多个消费者的总收入金额的值的第一数据; （b）在一段时间内接收表示多个消费者的总债务金额的第二数据; （c）选择消费者杠杆时间序列，将总收入与一段时间内的债务总额进行比较; （d）至少部分地基于第一和第二数据对消费者杠杆时间序列进行建模; （e）使用处理器确定特定时间的周期分量的值; 和（f）输出特定时间的循环分量的值的指示。
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公开(公告)号：US20100293107A1
公开(公告)日：2010-11-18
申请号：US12546807
申请日：2009-08-25
申请人： Agus Sudjianto , Michael Chorba , Daniel Hudson , Sandi Setiawan , Jocelyn Sikora , Harsh Singhal , Kiran Vuppu , Kaloyan Mihaylov , Jie Chen , Timothy J. Breault , Arun R. Pinto , Naveen G. Yeri , Benhong Zhang , Zhe Zhang , Tony Nobili , Hungien Wang , Aijun Zhang
发明人： Agus Sudjianto , Michael Chorba , Daniel Hudson , Sandi Setiawan , Jocelyn Sikora , Harsh Singhal , Kiran Vuppu , Kaloyan Mihaylov , Jie Chen , Timothy J. Breault , Arun R. Pinto , Naveen G. Yeri , Benhong Zhang , Zhe Zhang , Tony Nobili , Hungien Wang , Aijun Zhang
IPC分类号： G06Q40/00
摘要： 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.
摘要翻译： 描述了消费者和小企业的数据驱动和前瞻性风险和奖励食欲方法。 该方法包括客户细分，以便在收入和损失特征方面创建同质资产池，前瞻性模拟以预测收益和损失的预期值和波动率，以及投资组合的风险和报酬优化。 用于建模收入和损失的一种方法是广义加和效应分解模型，以适应历史数据。 基于该模型，执行分割程序，其允许创建具有类似收入和损失特征的客户群体。 开发了模型的估计程序，并开发了一种预测和模拟收入和损失波动性的模拟策略。 在各种经济情景下为当前投资组合创建有效的边际风险曲线（例如回报波动性）和报酬（例如预期收益）。
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公开(公告)号：USD1020384S1
公开(公告)日：2024-04-02
申请号：US29893657
申请日：2023-06-01
申请人： Jie Chen
设计人： Jie Chen
摘要： FIG. 1 is a top perspective view of a cup, showing my new design;
FIG. 2 is a bottom perspective view thereof;
FIG. 3 is a front view thereof;
FIG. 4 is a rear view thereof;
FIG. 5 is a left side view thereof;
FIG. 6 is a right side view thereof;
FIG. 7 is a top view thereof; and,
FIG. 8 is a bottom view thereof.
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