Research on FinTech Reshaping Enterprise Investment and Financing Modes from the Corporate Finance Perspective (Highlights in Business Economics and Management)
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- Traditional financial mechanisms rely heavily on fixed assets and collateral, creating information asymmetry and financing difficulties for small and micro enterprises.p.1
- Fintech integrates big data and artificial intelligence to expand enterprise credit dimensions through supply chain finance and online credit granting.p.2
- Digital dynamic credit models replace rigid physical collateral requirements by utilizing non-financial data such as tax records and business flow details.p.3
- Intelligent investment research tools improve capital allocation efficiency by reducing manual subjective biases in project value determination.p.3
- Uneven digital transformation across enterprise scales leaves many SMEs lacking basic digital management infrastructure.p.4
- Data silos across regulatory and judicial departments impede financial institutions from establishing complete risk pricing models.p.4
Key insights
- Data aggregation and intelligent algorithm modeling narrow the information gap between banks and real enterprises.p.2
- Online credit products like tax loans enable small enterprises to obtain disbursement based on compliant tax payment records without physical asset pledges.p.3
- Quantitative data modeling helps reduce wasteful capital phenomena like blind expansion and repeated industrial investment.p.3
- Management teams lacking digital financial literacy face increased liquidity risks due to multiple borrowings and high implicit financing costs.p.4
- Algorithmic risk control models based on historical data struggle to accurately price risks for light-asset startup enterprises.p.4
- Enterprises can compensate for algorithm technical shortcomings by combining intelligent data analysis with manual professional review.p.5
- Establishing cross-departmental government data sharing platforms helps break data silos and support precise risk management.p.6
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