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Support vector machines for default prediction of SMEs based on technology credit

Kim, Hong Sik; Sohn, So Young - In: European journal of operational research : EJOR 201 (2010) 3, pp. 838-846

Persistent link: https://www.econbiz.de/10003959870

Random effects model for credit rating transitions

Kim, Yoonseong; Sohn, So Young - In: European journal of operational research : EJOR 184 (2008) 2, pp. 561-573

Persistent link: https://www.econbiz.de/10003768289

Technology credit scoring model considering both SME characterisics and economic conditions : the Korean case

Moon, T. H.; Sohn, So Young - In: Journal of the Operational Research Society : OR 61 (2010) 4, pp. 666-675

Persistent link: https://www.econbiz.de/10003970088

Pattern recognition for evaluator errors in a credit scoring model for technology-based SMEs

Sohn, So Young; Doo, M. K.; Ju, Y. H. - In: Journal of the Operational Research Society : OR 63 (2012) 8, pp. 1051-1064

Persistent link: https://www.econbiz.de/10009576955

Updating a credit-scoring model based on new attributes without realization of actual data

Ju, Yong Han; Sohn, So Young - In: European journal of operational research : EJOR 234 (2014) 1, pp. 119-126

Persistent link: https://www.econbiz.de/10010247350

Behavioral credit scoring model for technology-based firms that considers uncertain financial ratios obtained from relationship banking

Sohn, So Young; Kim, Yoonseong - In: Small business economics : an entrepreneurship journal 41 (2013) 4, pp. 931-943

Persistent link: https://www.econbiz.de/10010254465

Behavioral technology credit scoring model with time-dependent covariates for stress test

Ju, Yonghan; Jeon, Song Yi; Sohn, So Young - In: European journal of operational research : EJOR 242 (2015) 3, pp. 910-919

Persistent link: https://www.econbiz.de/10010492360

A credit scoring model based on the Myers-Briggs type indicator in online peer-to-peer lending

Woo, Hyunwoo; Sohn, So Young - In: Financial innovation : FIN 8 (2022), pp. 1-19

Although psychometric features have been considered for alternative credit scoring, they have not yet been applied to peer-to-peer (P2P) lending because such information is not available on platforms. This study proposed an alternative credit scoring model for P2P lending by extracting typical...

Persistent link: https://www.econbiz.de/10013272683