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: 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.

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 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: 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.

Abstract: 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.

Abstract: Aspects of this disclosure relate to a computer assisted method for managing credit risk which includes electronically receiving data regarding one or more credit quality standards, electronically receiving data regarding one or more policy limits or exception rate limits and electronically receiving data regarding one or more concentration limits. The method may further include using a computer to establish one or more predetermined delinquency guardrails which relate to a maximum desired potential Net Credit Losses (NCL) or a minimum desired potential return (e.g., Risk Adjusted Margin (RAM)) for particular aspects of an organization.

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: 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.

Abstract: 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.

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: 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.