Session

LAW

Description

This paper explores the advantages of machine learning over traditional statistical methods in the context of real estate mortgage scoring. While traditional methods require extensive data preprocessing, machine learning offers a more streamlined and efficient approach. The financial industry is recognizing these benefits, with machine learning enabling faster mortgage application processing and reduced modeling biases. The findings underscore the potential of machine learning to revolutionize the financial sector.

Keywords:

Machine Learning, Real Estate Mortgage, Financial Industry, Data Preprocessing, Traditional Statistical Methods.

Proceedings Editor

Edmond Hajrizi

ISBN

978-9951-550-95-6

Location

UBT Lipjan, Kosovo

Start Date

28-10-2023 8:00 AM

End Date

29-10-2023 6:00 PM

DOI

10.33107/ubt-ic.2023.128

Included in

Law Commons

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Oct 28th, 8:00 AM Oct 29th, 6:00 PM

Revolutionizing Real Estate Mortgage Scoring: The Superiority of Machine Learning Over Traditional Statistical Methods

UBT Lipjan, Kosovo

This paper explores the advantages of machine learning over traditional statistical methods in the context of real estate mortgage scoring. While traditional methods require extensive data preprocessing, machine learning offers a more streamlined and efficient approach. The financial industry is recognizing these benefits, with machine learning enabling faster mortgage application processing and reduced modeling biases. The findings underscore the potential of machine learning to revolutionize the financial sector.