Automatic model refreshment based on degree of model degradation

A computer system for managing data, the computer system comprising:

• one or more processors, one or more computer-readable memories, one or more computer-readable tangible storage medium, and program instructions stored on at least one of the one or more tangible storage medium for execution by at least one of the one or more processors via at least one of the one or more memories, wherein the computer system is capable of performing a method comprising:
• program instructions to accumulate a plurality of predicted outputs according to a data accumulation rule, wherein the plurality of predicted outputs is generated by a predictive model executed by a first system, and wherein the predictive model is loaded, from a predictive model store, on to the first system, and wherein the data accumulation rule comprises program instructions to accumulate the plurality of predicted outputs according to a predefined period of time;
• program instructions to evaluate, by a second system, an accuracy of the predictive model, wherein evaluating the accuracy of the predictive model comprises determining a degree of difference between the plurality of predicted outputs and information generated during a development stage of the predictive model;
• in response to the determined degree of difference, program instructions to determine whether the accuracy of the predictive model has declined by an amount which exceeds a pre-determined threshold value;
• and
• based on determining that the accuracy of the predictive model has declined by an amount which exceeds a pre-determined threshold value, program instructions to update the predictive model.

A computer program product for managing data, the computer program product comprising:

• one or more computer-readable tangible storage medium and program instructions stored on at least one of the one or more tangible storage medium, the program instructions executable by a processor to cause the processor to perform a method comprising:
• program instructions to accumulate a plurality of predicted outputs according to a data accumulation rule, wherein the plurality of predicted outputs is generated by a predictive model executed by a first system, and wherein the predictive model is loaded, from a predictive model store, on to the first system, and wherein the data accumulation rule comprises program instructions to accumulate the plurality of predicted outputs according to a predefined period of time;
• program instructions to evaluate, by a second system, an accuracy of the predictive model, wherein evaluating the accuracy of the predictive model comprises determining a degree of difference between the plurality of predicted outputs and information generated during a development stage of the predictive model;
• in response to the determined degree of difference, program instructions to determine whether the accuracy of the predictive model has declined by an amount which exceeds a pre-determined threshold value;
• and
• based on determining that the accuracy of the predictive model has declined by an amount which exceeds a pre-determined threshold value, program instructions to update the predictive model.