AI-Driven Financial Risk Management: Machine Learning Applications in Emerging Markets

AI-Driven Financial Risk Management in Emerging Markets This research paper examines how artificial intelligence improves financial risk prediction in developing countries. We collected data from 850 finance professionals in India, Brazil, and South Africa during early 2026. Key results:- AI models 28% more accurate than traditional methods- Better detection of risky loans during economic crises- Identifies problems traditional models miss Methods: Neural networks, random forests, cross-validation testing. Main finding: AI systems can save emerging markets $1.8 trillion in potential losses by 2030. Published in:International Journal of Management and Organisational Research (IJMOR)Volume 1, Issue 1, March 2026Publisher: IFMOR (Section 8 Company)Keywords: AI finance, risk management, machine learning, emerging markets

Authors

Publication Details

Journal
Zenodo (CERN European Organization for Nuclear Research)
Published
2026-03-20
DOI
https://doi.org/10.5281/zenodo.19136554
Primary Topic
Financial Distress and Bankruptcy Prediction
Type
article
Field-Weighted Citation Impact
0.00
Controls
|||
ALL TIME
JAN
FEB
MAR
APR
MAY
JUN
JUL
AUG
SEP
OCT
article

AI-Driven Financial Risk Management: Machine Learning Applications in Emerging Markets

Pankaj Balwantrao Chaudhari, Ravindra Borkar
Zenodo (CERN European Organization for Nuclear Research)
Financial Distress and Bankruptcy Prediction
article

AI-Driven Financial Risk Management: Machine Learning Applications in Emerging Markets

Pankaj Balwantrao Chaudhari, Ravindra Borkar
article en

Abstract

AI-Driven Financial Risk Management in Emerging Markets This research paper examines how artificial intelligence improves financial risk prediction in developing countries. We collected data from 850 finance professionals in India, Brazil, and South Africa during early 2026. Key results:- AI models 28% more accurate than traditional methods- Better detection of risky loans during economic crises- Identifies problems traditional models miss Methods: Neural networks, random forests, cross-validation testing. Main finding: AI systems can save emerging markets $1.8 trillion in potential losses by 2030. Published in:International Journal of Management and Organisational Research (IJMOR)Volume 1, Issue 1, March 2026Publisher: IFMOR (Section 8 Company)Keywords: AI finance, risk management, machine learning, emerging markets

Zenodo (CERN European Organization for Nuclear Research)
Partnerships for the goals
Openalex Percentile: Top 14%
Financial Distress and Bankruptcy Prediction
AI Navigator

Ask Laika to Summarize, Analyze, and Connect papers live on the map.

Summarize Papers & Methodologies

Extract key findings, datasets, and comparative methods across publications.

Benchmark Rankings & Visual Analytics

Rank top research institutions, authors, funders, topics, and journals by Field-Weighted Citation Impact (FWCI) and paper volume with instant charts.

Connect Distant Disciplines

Bridge topological clusters on the map to find hidden collaborative intersections.