Implementation of Credit Risk Decision Tree Using AWS Step Functions Technology
Name
Egert Ott Metsandi
Abstract
It is of great importance for companies that use automated solutions, that they have complete overview of all the processes and that these processes are as fast as possible to save up on the most important resource-time. Most of these processes are related to different IT solutions. For example, one of these is the use of decision trees in many information system processes in the firms. The main goal of this research paper is to reduce time in fintech start-up by implementing a decision tree. Decision tree gives an overview on every customer and on what step in the process the customer currently is on obtaining the credit. Furthermore the decision tree also helps save on time on not performing unnecessary requests and finally outputs a result, with which the credit risk examiner can make an offer for the client with minimal time loss. Decision tree will be implemented by using AWS (Amazon Web Services) Step Functions technology. Decision tree will be validated by using manual testing and after that will be debugged in live environment.
Graduation Thesis language
Estonian
Graduation Thesis type
Bachelor - Computer Science
Supervisor(s)
Pelle Jakovits
Defence year
2021