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.

Abstract: A method for anti-money laundering surveillance may include analyzing transaction data based on a group that may include at least one of peer comparison, expected level of activity and debit/credit flow through. The method may also include generating an alert in response to one or more predetermined results from the analyzing.

Abstract: 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.

Abstract: 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.

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.

Abstract: 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.

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.

Abstract: 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.

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.

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.

Abstract: 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.

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.

Abstract: A system and method for interactive design of a product includes the steps of identifying an ideal design solution by identifying an unnecessary design parameter having a predetermined significant influence on a variable design response and fixing a predetermined nominal value of the identified unnecessary design parameter at which the variable design response is a minimum and the product design is an uncoupled design or a decoupled design. The method also includes the steps of selecting a most robust ideal design solution from the identified ideal design solution that is the most uncoupled design or the most decoupled design. The method further includes the steps of optimizing the most robust ideal design solution to obtain a pareto-optimal design solution for use in the design of the product that includes a design parameter having an independent design response.

Abstract: A system for interactive design a product having a design solution which includes a design parameter and a design response includes a user computer system and a remotely located computer system in communication with the user computer system. The system also includes a computer- generated geometric model of a product design stored in a data storage means. The system further includes a statistical analysis software program implemented by the remotely located computer system and a computer aided engineering software program implemented by the remotely located computer system.

Abstract: A system 10, which receives a computer, aided model or design 18 and which probabilistically analyzes the model 18 by use of a modified Latin Hypercube sampling technique and combined MARS and Kriging simulation methodologies, thereby allowing a simulation to be conducted at a most probable point of operation and allowing products having desired characteristics and attributes to be created.

Abstract: A system 10, which receives a computer, aided model or design 18 and which probabilistically analyzes the model 18 by use of a modified Latin Hypercube sampling technique and combined MARS and Kriging simulation methodologies, thereby allowing a simulation to be conducted at a most probable point of operation and allowing products having desired characteristics and attributes to be created.