Generalized Machine Learning Credit Scoring Algorithms for Crowdfundingof SMEs


Tezin Türü: Doktora

Tezin Yürütüldüğü Kurum: Marmara Üniversitesi, Mühendislik Fakültesi, Endüstri Mühendisliği Bölümü, Türkiye

Tezin Dili: İngilizce

Öğrenci: Doruk Şen

Danışman: Cem Çağrı Dönmez

Özet:

Lacking access to finance is a huge struggle for SMEs and financing them is the next big move. Therefore, the world needs to pay its utmost attention to Fintech for dealing with this gap. Since this subject is relatively new, researchers have not fully focused on this subject yet. However, it is expected to witness rising interest in it. In this study, a new approach in SME credit scoring will not only be presented for a reduction of the associated risk of failure to pay the debt but also for reduction of delinquency and credit refunds. Additionally, a crowdfunding base will be set to expand the applications of cryptocurrencies for money transferring. Hence, it will enhance the understanding of blockchain technologies. The main purpose of this research is to enhance the understanding of SME financing with the proposed approach which is to allow them to reach the finance from any investor without bureaucratic obstacles. After the completion of this thesis, the literature will be contributed twofold; it will present a new generalizable algorithm for SME credit scoring and set a base for crowdfunding mechanism for application of the credit scoring model.