Applying hybrid machine learning algorithms to assess customer risk-adjusted revenue in the financial industry

Machado, Marcos Roberto; Karray, Salma

doi:10.1016/j.elerap.2022.101202

Electronic Commerce Research and Applications

2022

DOI: 10.1016/j.elerap.2022.101202

|View full text |Cite

Applying hybrid machine learning algorithms to assess customer risk-adjusted revenue in the financial industry

Marcos Roberto Machado

Salma Karray²

Help me understand this report

Search citation statements

Order By: Relevance

Paper Sections

Select...

Citation Types

Supporting

Mentioning

Contrasting

Year Published

2024

2025

Publication Types

Select...

Article5

Relationship

Self Cite0

Independent5

Authors

Journals

Cited by 14 publications

References 44 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

Uncovering the themes and trends in crowdfunding research using Latent Dirichlet Allocation

Rejeb,

Appolloni

et al. 2024

Manag Rev Q

View full text Add to dashboard Cite

Crowdfunding (CF) has become a significant force in the entrepreneurial landscape, offering an innovative alternative to traditional financing channels for startups and projects. As the field expands, it is crucial to systematically analyze the existing literature to identify key themes, patterns, and emerging areas of interest. To achieve this goal, this study investigates the CF literature using latent Dirichlet allocation (LDA)-based topic modeling based on 1,678 publications extracted from the Scopus database. The review reveals significant growth in CF research, with top journals spanning diverse disciplines. Eight main topics are identified, including CF campaign success and financing, donation-based CF, social effects of CF, entrepreneurial projects and rewards in CF, financial and fintech aspects of CF, CF project success and performance, P2P lending models and credit risk assessment, and equity CF and venture capital. Several research directions are suggested for each topic to advance the CF field. The theoretical and practical implications are also discussed. To the authors’ best knowledge, this study represents the first systematic analysis of the CF literature using the LDA approach, offering a comprehensive and up-to-date overview of this field and highlighting emerging areas of interest and potential research directions.

show abstract

Uncovering the themes and trends in crowdfunding research using Latent Dirichlet Allocation

Rejeb,

Appolloni

et al. 2024

Manag Rev Q

View full text Add to dashboard Cite

show abstract

Green AI in the finance industry: Exploring the impact of feature engineering on the accuracy and computational time of Machine Learning models

Machado,

Asadi,

de Souza

et al. 2024

Applied Soft Computing

View full text Add to dashboard Cite

Applications of machine learning algorithms to support COVID-19 diagnosis using X-rays data information

Medeiros,

Machado,

de Freitas

et al. 2024

Expert Systems with Applications

View full text Add to dashboard Cite

scite is a Brooklyn-based organization that helps researchers better discover and understand research articles through Smart Citations–citations that display the context of the citation and describe whether the article provides supporting or contrasting evidence. scite is used by students and researchers from around the world and is funded in part by the National Science Foundation and the National Institute on Drug Abuse of the National Institutes of Health.

Contact Info

customersupport@researchsolutions.com

10624 S. Eastern Ave., Ste. A-614

Henderson, NV 89052, USA

This site is protected by reCAPTCHA and the Google Privacy Policy and Terms of Service apply.

Blog Terms and Conditions API Terms Privacy Policy Contact Cookie Preferences Do Not Sell or Share My Personal Information

Made with 💙 for researchers

Part of the Research Solutions Family.

Applying hybrid machine learning algorithms to assess customer risk-adjusted revenue in the financial industry

Cited by 14 publications

References 44 publications

Uncovering the themes and trends in crowdfunding research using Latent Dirichlet Allocation

Uncovering the themes and trends in crowdfunding research using Latent Dirichlet Allocation

Green AI in the finance industry: Exploring the impact of feature engineering on the accuracy and computational time of Machine Learning models

Applications of machine learning algorithms to support COVID-19 diagnosis using X-rays data information

Contact Info

Product

Resources

About