Work

Big-data-driven Model Construction and Empirical Analysis of SMEs Credit Assessment in China

Year: 2019

Type: conference-paper

Abstract: Most of SMEs(Small and Medium-size Enterprises) in China are facing severe financing constraints, while credit reporting could be effective to help overcome it. However, traditional credit reporting mainly based on financial data, can hardly give a well-rounded evaluation on SMEs limited on financial data while flourished in non-financial data. In this work, we propose a big-data-driven credit assessment framework for SMEs, highlighting the combination of financial and non-financial data including big data from business, government, social media & networks. An application to 123 SMEs in China inllustates that our methodology outperforms the traditional one, especially for those SMEs of worse financial conditions.

Source: Procedia Computer Science

DOI: 10.1016/j.procs.2019.01.205

Authors: LIU Yadi, SONG Yuning, YU Jiayue, XIE Yingfa, WANG Yiyuan, ZENG Xiaoping

Institutions: North China University of Water Resources and Electric Power, Shandong University, University of Pennsylvania, George Washington University, Australian National University, Beijing Normal University

Language: English

Topic: Financial Distress and Bankruptcy Prediction

Subfield: Accounting

Field: Business, Management and Accounting

Domain: Social Sciences

Open Access status: diamond

OpenAlex ID: W2911316743

FWCI: 8.752

Cites: 8

Cited by: 19

Related to: 10