Innovative Credit Risk Assessment: Leveraging Social Media Data for Inclusive Credit Scoring in Indonesia’s Fintech Sector
Andry Alamsyah (),
Aufa Azhari Hafidh and
Annisa Dwiyanti Mulya
Additional contact information
Andry Alamsyah: School of Economics and Business, Telkom University, Bandung 40257, Indonesia
Aufa Azhari Hafidh: School of Economics and Business, Telkom University, Bandung 40257, Indonesia
Annisa Dwiyanti Mulya: School of Economics and Business, Telkom University, Bandung 40257, Indonesia
JRFM, 2025, vol. 18, issue 2, 1-32
Abstract:
The financial technology domain has undertaken significant strides toward more inclusive credit scoring systems by integrating alternative data sources, prompting an exploration of how we can further simplify the process of efficiently assessing creditworthiness for the younger generation who lack traditional credit histories and collateral assets. This study introduces a novel approach leveraging social media analytics and advanced machine learning techniques to assess the creditworthiness of individuals without traditional credit histories and collateral assets. Conventional credit scoring methods tend to rely heavily on central bank credit information, especially traditional collateral assets such as property or savings accounts. We leverage demographics, personality, psycholinguistics, and social network data from LinkedIn profiles to develop predictive models for a comprehensive financial reliability assessment. Our credit scoring methods propose scoring models to produce continuous credit scores and classification models to categorize potential borrowers—particularly young individuals lacking traditional credit histories or collateral assets—as either good or bad credit risks based on expert judgment thresholds. This innovative approach questions conventional financial evaluation methods and enhances access to credit for marginalized communities. The research question addressed in this study is how to develop a credit scoring mechanism using social media data. This research contributes to the advancing fintech landscape by presenting a framework that has the potential to transform credit scoring practices to adapt to modern economic activities and digital footprints.
Keywords: financial technology; credit scoring; social media analytics; alternative data Sources; creditworthiness; financial inclusion (search for similar items in EconPapers)
JEL-codes: C E F2 F3 G (search for similar items in EconPapers)
Date: 2025
References: View references in EconPapers View complete reference list from CitEc
Citations:
Downloads: (external link)
https://www.mdpi.com/1911-8074/18/2/74/pdf (application/pdf)
https://www.mdpi.com/1911-8074/18/2/74/ (text/html)
Related works:
This item may be available elsewhere in EconPapers: Search for items with the same title.
Export reference: BibTeX
RIS (EndNote, ProCite, RefMan)
HTML/Text
Persistent link: https://EconPapers.repec.org/RePEc:gam:jjrfmx:v:18:y:2025:i:2:p:74-:d:1582131
Access Statistics for this article
JRFM is currently edited by Ms. Chelthy Cheng
More articles in JRFM from MDPI
Bibliographic data for series maintained by MDPI Indexing Manager ().