Evaluation of farm credit express delinquencies

dc.contributor.authorMcAllister, Kristina
dc.date.accessioned2018-08-10T13:53:23Z
dc.date.available2018-08-10T13:53:23Z
dc.date.graduationmonthAugusten_US
dc.date.issued2018-08-01en_US
dc.date.published2018en_US
dc.description.abstractCredit scoring is a tool used to make lending decisions. AgChoice Farm Credit has a dealer financing program called Farm Credit Express that makes lending decisions based on a scoring model. Farm Credit Express is a dealer financing option for farm equipment purchases. AgChoice has generated significant loan volume with this program but has also experienced challenges with loan delinquencies as field staff must service loans that they did not originate. This thesis evaluates loan delinquencies within AgChoice Farm Credit’s Farm Credit Express (“FCE”) program. The thesis develops a regression model that includes delinquencies as the dependent variable and Total AgChoice Borrowing, Original Loan Amount, Farming Segment, CBI Score, AgScore, and FCE Only as the independent variables. The model provides an examination of AgChoice’s Farm Credit Express delinquencies and evaluates the variables mentioned above and their ability to predict delinquencies. The results showed that Total AgChoice Borrowing, Original Loan Amount, CBI Score and FCE only were statistically significant independent variables. Based on results of the model, recommendations were made to potentially reduce future delinquencies in the Farm Credit Express loan portfolio.en_US
dc.description.advisorChristine Wilsonen_US
dc.description.degreeMaster of Agribusinessen_US
dc.description.departmentDepartment of Agricultural Economicsen_US
dc.description.levelMastersen_US
dc.identifier.urihttp://hdl.handle.net/2097/39125
dc.subjectCredit Scoringen_US
dc.subjectDelinquencyen_US
dc.subjectFarm Crediten_US
dc.subjectDealer Financingen_US
dc.subjectLogistic Modelen_US
dc.subjectProbability of Defaulten_US
dc.titleEvaluation of farm credit express delinquenciesen_US
dc.typeThesisen_US

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