Artificial intelligence-based blockchain-driven financial default prediction
- URL: http://arxiv.org/abs/2410.00044v1
- Date: Fri, 27 Sep 2024 17:51:48 GMT
- Title: Artificial intelligence-based blockchain-driven financial default prediction
- Authors: Junjun Huang,
- Abstract summary: blockchain and artificial intelligence technology are playing a huge role in all walks of life.
This study offers financial institutions new thoughts on financial technology in terms of credit risk mitigation and financial system stabilization.
- Score: 0.43512163406552007
- License: http://creativecommons.org/licenses/by-nc-sa/4.0/
- Abstract: With the rapid development of technology, blockchain and artificial intelligence technology are playing a huge role in all walks of life. In the financial sector, blockchain solves many security problems in data storage and management in traditional systems with its advantages of decentralization and security. And artificial intelligence has huge advantages in financial forecasting and risk management through its powerful algorithmic modeling capabilities. In financial default prediction using blockchain and artificial intelligence technology is a very powerful application. Blockchain technology guarantees the credibility of data and consistency on all nodes, and machine learning builds a high-level default prediction model through detailed analysis of big data. This study offers financial institutions new thoughts on financial technology in terms of credit risk mitigation and financial system stabilization.
Related papers
- Redefining Finance: The Influence of Artificial Intelligence (AI) and Machine Learning (ML) [2.3931689873603594]
With rapid transformation of technologies, the fusion of Artificial Intelligence (AI) and Machine Learning (ML) in finance is disrupting the entire ecosystem.
The segments of financial institutions which are getting heavily influenced are retail banking, wealth management, corporate banking & payment ecosystem.
arXiv Detail & Related papers (2024-10-21T12:32:17Z) - IT Strategic alignment in the decentralized finance (DeFi): CBDC and digital currencies [49.1574468325115]
Decentralized finance (DeFi) is a disruptive-based financial infrastructure.
This paper seeks to answer two main questions 1) What are the common IT elements in the DeFi?
And 2) How the elements to the IT strategic alignment in DeFi?
arXiv Detail & Related papers (2024-05-17T10:19:20Z) - DAM: A Universal Dual Attention Mechanism for Multimodal Timeseries Cryptocurrency Trend Forecasting [3.8965079384103865]
This paper presents a novel Dual Attention Mechanism (DAM) for forecasting cryptocurrency trends using multimodal time-series data.
Our approach integrates critical cryptocurrency metrics with sentiment data from news and social media analyzed through CryptoBERT.
By combining elements of distributed systems, natural language processing, and financial forecasting, our method outperforms conventional models like LSTM and Transformer by up to 20% in prediction accuracy.
arXiv Detail & Related papers (2024-05-01T13:58:01Z) - Machine Learning for Blockchain Data Analysis: Progress and Opportunities [9.07520594836878]
blockchain datasets encompass multiple layers of interactions across real-world entities, e.g., human users, autonomous programs, and smart contracts.
These unique characteristics present both opportunities and challenges for machine learning on blockchain data.
This paper serves as a comprehensive resource for researchers, practitioners, and policymakers, offering a roadmap for navigating this dynamic and transformative field.
arXiv Detail & Related papers (2024-04-28T17:18:08Z) - AlphaFin: Benchmarking Financial Analysis with Retrieval-Augmented Stock-Chain Framework [48.3060010653088]
We release AlphaFin datasets, combining traditional research datasets, real-time financial data, and handwritten chain-of-thought (CoT) data.
We then use AlphaFin datasets to benchmark a state-of-the-art method, called Stock-Chain, for effectively tackling the financial analysis task.
arXiv Detail & Related papers (2024-03-19T09:45:33Z) - Generative AI-enabled Blockchain Networks: Fundamentals, Applications,
and Case Study [73.87110604150315]
Generative Artificial Intelligence (GAI) has emerged as a promising solution to address challenges of blockchain technology.
In this paper, we first introduce GAI techniques, outline their applications, and discuss existing solutions for integrating GAI into blockchains.
arXiv Detail & Related papers (2024-01-28T10:46:17Z) - A Blockchain Solution for Collaborative Machine Learning over IoT [0.31410859223862103]
Federated learning (FL) and blockchain technologies have emerged as promising approaches to address these challenges.
We present a novel IoT solution that combines the incremental learning vector quantization algorithm (XuILVQ) with blockchain technology.
Our proposed architecture addresses the shortcomings of existing blockchain-based FL solutions by reducing computational and communication overheads while maintaining data privacy and security.
arXiv Detail & Related papers (2023-11-23T18:06:05Z) - Exploration of Hyperledger Besu in Designing Private Blockchain-based
Financial Distribution Systems [0.7366405857677227]
This article focuses on the development of an innovative consortium blockchain based financial distribution application.
It demonstrates the diverse applications of blockchain, ranging from remittances to lending and investments in finance to data administration in healthcare and supply chain tracking.
The investigation sheds light on the combination of consortium blockchain controlled access and Hyprledger Besu comprehensive functionality.
arXiv Detail & Related papers (2023-11-14T19:18:16Z) - Designing an attack-defense game: how to increase robustness of
financial transaction models via a competition [69.08339915577206]
Given the escalating risks of malicious attacks in the finance sector, understanding adversarial strategies and robust defense mechanisms for machine learning models is critical.
We aim to investigate the current state and dynamics of adversarial attacks and defenses for neural network models that use sequential financial data as the input.
We have designed a competition that allows realistic and detailed investigation of problems in modern financial transaction data.
The participants compete directly against each other, so possible attacks and defenses are examined in close-to-real-life conditions.
arXiv Detail & Related papers (2023-08-22T12:53:09Z) - Can ChatGPT Forecast Stock Price Movements? Return Predictability and Large Language Models [51.3422222472898]
We document the capability of large language models (LLMs) like ChatGPT to predict stock price movements using news headlines.
We develop a theoretical model incorporating information capacity constraints, underreaction, limits-to-arbitrage, and LLMs.
arXiv Detail & Related papers (2023-04-15T19:22:37Z) - Data science and AI in FinTech: An overview [102.56893575390569]
Smart FinTech is largely inspired and empowered by data science and new-generation AI and (DSAI) techniques.
The research on data science and AI in FinTech involves many latest progress made in smart FinTech for BankingTech, TradeTech, LendTech, InsurTech, WealthTech, PayTech, RiskTech, cryptocurrencies, and blockchain.
arXiv Detail & Related papers (2020-07-10T01:10:37Z)
This list is automatically generated from the titles and abstracts of the papers in this site.
This site does not guarantee the quality of this site (including all information) and is not responsible for any consequences.