1. A computer implemented method of generating a scoring model, comprising: accessing, using one or more data processors, a plurality of transactional data records organized into a plurality of fine bins, wherein the data records include an attribute and an indicator variable, and wherein the data records are organized into the plurality of fine bins according to the attribute, associating, using the one or more data processors, a weight of evidence with the plurality of fine bins, wherein the weight of evidence is based upon the indicator variable of the data records, and wherein the weight of evidence indicates a level of risk corresponding to the data records; minimizing, using an objective function and the one or more data processors, a difference between the weight of evidence associated with the plurality of fine bins and a surrogate weight of evidence associated with a plurality of coarse bins; generating, using the one or more data processors, an optimization model using the objective function, one or more constraints, and a surrogate weight of evidence, wherein the one or more constraints include linear constraints derived from business requirements, and wherein the one or more constraints include one or more of a minimum or maximum number of total bins, minimum or maximum bin widths, a maximum number of fine bins per coarse bin, a minimum or maximum number of good or bad points in each bin, a minimum or maximum number of total points in each bin, and a minimum difference in weight of evidence between two consecutive bins; generating, using the one or more data processors, a plurality of coarse bins by applying a mixed integer problem solver to the optimization model; associating, using the one or more data processors, the surrogate weight of evidence with the plurality of coarse bins, wherein the surrogate weight of evidence is based upon the indicator variable of the data records, and wherein the surrogate weight of evidence indicates a level of risk corresponding to the data records; and generating, using the one or more data processors, a scoring model using the coarse set of bins, wherein the scoring model predicts a level of financial risk for a financial transaction.