Artificial intelligence applications in finance: a survey
X Li, A Sigov, L Ratkin, LA Ivanov… - Journal of Management …, 2023 - Taylor & Francis
Finance is in our daily life. We invest, borrow, lend, budget, and save money. Finance also
provides guidelines for corporation and government spending and revenue collection …
provides guidelines for corporation and government spending and revenue collection …
Credit scoring models using ensemble learning and classification approaches: a comprehensive survey
Credit scoring models are developed to strengthen the decision-making process specifically
for financial institutions to deal with risk associated with a credit candidate while applying for …
for financial institutions to deal with risk associated with a credit candidate while applying for …
[HTML][HTML] Automated machine learning: AI-driven decision making in business analytics
M Schmitt - Intelligent Systems with Applications, 2023 - Elsevier
The realization that AI-driven decision-making is indispensable in today's fast-paced and
ultra-competitive marketplace has raised interest in industrial machine learning (ML) …
ultra-competitive marketplace has raised interest in industrial machine learning (ML) …
Evolutionary extreme learning machine with novel activation function for credit scoring
The term credit scoring is extensively used in credit industries for decision making and
measuring the risk associated with an applicant. It uses applicants' historical data for credit …
measuring the risk associated with an applicant. It uses applicants' historical data for credit …
Bagging supervised autoencoder classifier for credit scoring
Automatic credit scoring, a crucial risk management tool for banks and financial institutes,
has attracted much attention in the past few decades. As such, various approaches have …
has attracted much attention in the past few decades. As such, various approaches have …
A focal-aware cost-sensitive boosted tree for imbalanced credit scoring
W Liu, H Fan, M Xia, M Xia - Expert Systems with Applications, 2022 - Elsevier
Credit scoring is an effective tool for banks or lending institutions to identify potential bad
lenders and creditworthy applicants. Boosting ensemble approaches have made appealing …
lenders and creditworthy applicants. Boosting ensemble approaches have made appealing …
Kirti: A blockchain-based credit recommender system for financial institutions
SB Patel, P Bhattacharya, S Tanwar… - IEEE Transactions on …, 2020 - ieeexplore.ieee.org
In this paper, we propose KiRTi, a deep-learning-based credit-recommender scheme for
public blockchain to facilitate smart lending operations between prospective borrowers (PB) …
public blockchain to facilitate smart lending operations between prospective borrowers (PB) …
Deep learning vs. gradient boosting: Benchmarking state-of-the-art machine learning algorithms for credit scoring
M Schmitt - arXiv preprint arXiv:2205.10535, 2022 - arxiv.org
Artificial intelligence (AI) and machine learning (ML) have become vital to remain
competitive for financial services companies around the globe. The two models currently …
competitive for financial services companies around the globe. The two models currently …
Gas chromatographic retention index prediction using multimodal machine learning
DD Matyushin, AK Buryak - Ieee Access, 2020 - ieeexplore.ieee.org
Gas chromatography is a widely used method in analytical chemistry and metabolomics.
Using gas chromatography, vaporizable compounds can be separated for their further …
Using gas chromatography, vaporizable compounds can be separated for their further …
A multi-level classification and modified PSO clustering based ensemble approach for credit scoring
Credit scoring is a statistical technique that guides financial institutions to make informed
decisions regarding the extension of loans to customers based on cautious examination of …
decisions regarding the extension of loans to customers based on cautious examination of …