Exploration of Financial Market Credit Scoring and Risk Management and Prediction Using Deep Learning and Bionic Algorithm

Peng Du · Hong Shu

63 citations0/0 files storedJournal of Global Information Management

No readable copy stored yet — this record is metadata only.

No open-access location is known for this record yet.

Literature note Cite in a project Citation map

Financial Distress and Bankruptcy Prediction Customer churn and segmentation Evaluation and Optimization Models

Abstract

The purpose is to effectively manage the financial market, comprehensive assess personal credit, reduce the risk of financial enterprises. Given the systemic risk problem caused by the lack of credit scoring in the existing financial market, a credit scoring model is put forward based on the deep learning network. The proposed model uses RNN (Recurrent Neural Network) and BRNN (Bidirectional Recurrent Neural Network) to avoid the limitations of shallow models. Afterward, to optimize path analysis, bionic optimization algorithms are introduced, and an integrated deep learning model is proposed. Finally, a financial credit risk management system using the integrated deep learning model is proposed. The probability of default or overdue customers is predicted through verification on three real credit data sets, thus realizing the credit risk management for credit customers.

Paper brief

Loading…

Cite this work

Citation unavailable for this work.

BibTeX RIS CSL-JSON

No public copy is stored for this record, so only the metadata is cited.

Citations in this library

Citation map →

Stored only when both papers are in the corpus — 63 citations exist upstream.

References

2020Strategic management during the financial crisis: How firms adjust their strategic investments in response to credit market disruptions 2020Environmental cost control system of manufacturing enterprises using artificial intelligence based on value chain of circular economy 2019Big data analytics for financial Market volatility forecast based on support vector machine

Cited by

2022Emerging Trends in Deep Learning for Credit Scoring: A Review 2024XGBoost-B-GHM: An Ensemble Model with Feature Selection and GHM Loss Function Optimization for Credit Scoring 2023Blockchain technology adaptation and organizational inertia: moderating role between knowledge management processes and supply chain resilience 2022Risk Measurement of the Financial Credit Industry Driven by Data 2022Peer-to-peer lending platform risk analysis: an early warning model based on multi-dimensional information 2023Internet Financial Credit Scoring Models Based on Deep Forest and Resampling Methods 2023Investigating the Determinants of New Technology Entrepreneurial Performance: an Empirical Study with PLS-SEM and MGA 2022An Intelligent omnichannel assortment model to manage webrooming: an optimization approach

Explore the map →

Papers that cite the same references — the relational fallback while embeddings are still backfilling.

Imported from OpenAlex (CC0) — nothing here is generated.