Abstract: A computer implemented method of generating a custom signal from a data library containing multiple datasets of variable values correlated with time and geography includes receiving a user defined target variable, a time parameter, and a geography parameter, determining the applicable datasets from the data library overlapping the user-defined time parameter or geography parameter, testing the control variables of the applicable datasets for statistical significance to the target variable, aggregating a custom signal of at least three control variables having the greatest statistical significance to the target variable. The method includes generating a forecasting model by determining an internal feature analysis, determining an optimal external feature analysis, and selecting an optimal feature set based on a statistical strength of the internal feature analysis and the optimal external feature analysis.

Abstract: A method and system are disclosed that provides efficient interventions based on unique collection strategies and the priorities of such interventions. The system also provides the expected time for payment. The interventions are generated on an individual debtor basis to improve the efficiency and success of collecting delinquent debts. A profile is determined for each debtor based on historical data that provides the most efficient collection strategy and the optimal priorities of interventions and the likelihood of the delinquent debtors paying by paying by a predicted time The debt collection strategy is based on data analytics of data from different sources including information about the debtor assets, the debtor's financial profile and the debtor's communication habits. This data is fed into a predictive model that is scalable and is used to generate a web-based report on each individual debtor to provide an improved and more efficient collection strategy for collecting delinquent debts.