Work

Credit Risk Prediction of Consumer Finance in Digital Economy Based on DeepFM Algorithm Under the Background of Green Economy

Year: 2026

Type: article

Abstract: As the green economy continuously integrates into the digital financial system, the structure of credit risk in consumer finance has changed accordingly. Traditional models gradually exhibit limitations in characterizing complex feature interactions and nonlinear relationships. To tackle this problem, this study establishes an attention-enhanced multi-head self-attention deep factorization machine. The attention mechanism is introduced into low-order feature interactions, and the multi-head self-attention mechanism is fused with deep neural networks in high-order interaction parts to achieve multi-level joint feature modeling. Experiments are carried out using the Lending Club dataset. This study verifies that the proposed method has strong adaptability and stability in consumer finance credit risk identification under the background of digital economy.

Source: International Journal of Information Technologies and Systems Approach

DOI: 10.4018/ijitsa.418775

Authors: Meiyan Sui, Zining Wang, Tarekol Islam Maruf

Institutions: Yantai Nanshan University, Northeastern University, Alfa University College

Language: Ndonga

Topic: Financial Distress and Bankruptcy Prediction

Subfield: Accounting

Field: Business, Management and Accounting

Domain: Social Sciences

Open Access status: hybrid

OpenAlex ID: W7202392079

FWCI:

Cites: 23

Cited by:

Related to: 10