Management Practice Insights
DOI: 10.59571/mpi.v3si1.9
Year: 2025, Volume: 3, Issue: Special Issue 1, Pages: 52-57
Original Article
Kunjana Malik 1, Shalini Talwar 2, Rishi Naik 3
1 Associate Professor in the Finance and Accounting Department at SPJIMR.
2 Professor in the Finance and Accounting Department at SPJIMR.
3 Student at IIT Mumbai.
Correspondence
Received Date:10 October 2024, Accepted Date:27 May 2025, Published Date:30 June 2025
If you work in finance—whether as an economist, policymaker, risk manager, portfolio manager, or analyst—you are always trying to stay prepared for the next financial crisis, knowing that the interconnectedness of global economies means a crisis anywhere could quickly ripple across markets and impact you. Predicting financial crises, however, has always been a challenge. Traditional models struggle to capture the complexity of global markets and how quickly shocks spread across regions and asset classes. To tackle this, research by Samitasa, Kampouris, and Kenourgios has found a powerful new approach: integrating network analysis and machine learning to create a robust Early Warning System (EWS) for financial crises.1 By mapping the financial system as a network of interconnected assets, their model identifies key nodes—countries or assets—that act as primary transmission points for financial contagion. Further reinforcing the importance of machine learning methods, recent research by Bluwstein and team demonstrates that non-linear machine learning models consistently outperform traditional regression-based approaches in crisis prediction.2 Their findings highlight critical indicators—credit growth and the yield curve slope—as essential inputs for identifying financial vulnerabilities.
Both studies underscore the need for data-driven, adaptive systems, powered by machine learning and informed by network dynamics, to improve crisis preparedness.
1 Aristeidis Samitas, Elias Kampouris, and Dimitris Kenourgios, “Machine Learning as an Early Warning System to Predict Financial Crisis,” International Review of Financial Analysis 71 (October 1, 2020): 101507, https://doi.org/10.1016/j.irfa.2020.101507.
2 Kristina Bluwstein et al., “Credit Growth, the Yield Curve and Financial Crisis Prediction: Evidence from a Machine Learning Approach,” Journal of International Economics 145 (November 1, 2023): 103773, https://doi.org/10.1016/j.jinteco.2023.103773.
3 Renae Merle, “A Guide to the Financial Crisis — 10 Years Later,” The Washington Post, October 9, 2018, https://www.washingtonpost.com/business/economy/a-guideto-the-financial-crisis--10-years-later/2018/09/10/114b76baaf10-11e8-a20b-5f4f84429666_story.html.
4 Federal Deposit Insurance Corporation (FDIC), “Overview,” in Crisis and Response: An FDIC History, 2008–2013, n.d., https://www.fdic.gov/resources/publications/crisisresponse/book/crisis-response.pdf.
5 “500,000 Jobs Lost to Recession in 3 Months: Govt,” Business Standard, January 25, 2013, https://www.businessstandard.com/article/economy-policy/500-000-jobs-lost-torecession-in-3-months-govt-109020400164_1.html.
6 Government of India, “State of the Economy: Economic Growth During 2008-09,” in Economic Survey 2008-2009, 2025, https://www.indiabudget.gov.in/budget_archive/es200809/chapt2009/chap12.pdf.
7 IMF, “The IMF-FSB Early Warning Exercise,” January 2023, https://www.imf.org/en/About/Factsheets/Sheets/2023/Early -Warning-Exercise.
8 Edmond Alphandéry, “The Euro Crisis,” Fondation Robert Schuman, Schuman Papers and Interviews, May 14, 2012, https://www.robert-schuman.eu/en/european-issues/240-theeuro-crisis.
9 Katie Allen, “Why Is China's Stock Market in Crisis?,” The Guardian, July 8, 2015, sec. Business, https://www.theguardian.com/business/2015/jul/08/chinastock-market-crisis-explained.
10 Sue Lannin, “Panic on China's Share Market as Stocks Lose $3.7 Trillion,” ABC News, July 3, 2015, https://www.abc.net.au/news/2015-07-03/panic-on-chinasshare-market-as-stocks-lose-$3-7-trillion/6594316.
11 “5 Biggest Stock Market Crashes In India,” Grip Invest, May 26, 2023, https://www.gripinvest.in/blog/5-biggest-stock-marketcrashes-in-india.
12 Sharon Wu, “Here's How Interest Rates Impact Gold Prices,” CBS News, October 21, 2024, online edition, sec. Money Watch, https://www.cbsnews.com/news/heres-how-interest-ratesimpact-gold-prices/.
13 Sean Galea-Pace, “IBM Watson: How AI Is Transforming the Supply Chain,” May 18, 2020, https://supplychaindigital.com/technology/ibm-watson-howai-transforming-supply-chain.
14 “Siemens Energy Standardizes Predictive Maintenance Operations on InfluxDB,” InfluxData (blog), September 26, 2024, https://www.influxdata.com/blog/siemens-energystandardizes-predictive-maintenance-influxdb/.
© 2025 Published by SPJIMR. This is an open-access article under the CC BY license (https://creativecommons.org/licenses/by/4.0/)
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