Prediction of late credit card payments to aid Hyundai Card withprior to a missed payment, market repayment plans to high risk customers who may be struggling to make monthly paymentscapturing borrower changes in financial circumstances over timerepayment forecasting
Develop I-tag that indicates borrow risk of a future missed credit card payment
aDevelop prototype while awaiting permission to access Hyundai Card database
Find similar tags to those in the prototype to implement a real prediction model
Database-Prototype: Local Postgres ContainerDatabase-Production: Hyundai Card Hive DBPickle Pandas data frame and transfer its path to next task
Receive path from x-com and un-pickle data frameExecute Scikit-Learn transformation pipelinePickle transformed training and test data frames
un-pickle training data frameimplement training function to produce modelpickle model
un-pickle training modelspredict test data labelsevaluate performanceselect and pickle best model for production
Develop data transformation functions to be implemented by AirflowImplement tranformation functions in a transformation pipeline to be executable on both training and test data separately important for proper isolation during future training data refreshes (avoid training data getting into test data)
Explore multiple algorithms and optimize with cross validation of model performance and grid/random search for optimal hyper parameters