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Topic · Accounting

Financial Distress and Bankruptcy Prediction

Financial Distress and Bankruptcy Prediction is a research topic within Accounting. Science Explorer counts 13k research works in it since 1960. 21.1% of them reached the world's top 10% most cited for their field and year.

This cluster of papers focuses on the development and comparison of machine learning models, including neural networks, support vector machines, and ensemble methods, for predicting bankruptcy and assessing credit risk. The research explores various techniques for financial distress prediction, credit scoring, and risk assessment in both corporate and consumer contexts.

  • Bankruptcy Prediction
  • Credit Scoring
  • Machine Learning
  • Financial Distress
  • Neural Networks
  • Support Vector Machines
  • Ensemble Learning
  • Risk Assessment
  • Predictive Modeling
  • Financial Crisis
Research works
13k
fractional, since 1960
In the world top 10%
2.8k
per year above
Top-10% rate
21.1%
share of its works in the world top 10%
Growth, 2013–17 → 2018–22
+70%
the tick is no change

Which countries lead Financial Distress and Bankruptcy Prediction research?

By volume, China and India publish the most (978 and 695 works in 2022–2025).

By volume, 2022–2025

  1. 1 China 978 works
  2. 2 India 695 works
  3. 3 Indonesia 517 works
  4. 4 United States 464 works
  5. 5 Türkiye 163 works
  6. 6 United Kingdom 107 works
  7. 7 Malaysia 78 works
  8. 8 Iran 66 works
  9. 9 ?? 64 works
  10. 10 Italy 62 works

How concentrated that is

The same countries as shares of everything the list above accounts for. A node where two countries do two thirds of the work and one spread evenly across twelve read alike as a ranking and not at all alike here.

China: 30.6%India: 21.8%Indonesia: 16.2%United States: 14.5%6 others listed: 16.9%31%largest
China978 · 30.6%India695 · 21.8%Indonesia517 · 16.2%United States464 · 14.5%6 others listed539 · 16.9%

Shares of the rows listed above, not of the whole node.

Which institutions lead Financial Distress and Bankruptcy Prediction research?

By volume in 2022–2025, Binus University publishes the most Financial Distress and Bankruptcy Prediction research, followed by Saveetha University and SRM Institute of Science and Technology.

Who are the leading researchers in Financial Distress and Bankruptcy Prediction?

The most-cited researchers publishing on Financial Distress and Bankruptcy Prediction include Taghi M. Khoshgoftaar.

  1. 1 Taghi M. Khoshgoftaar United States 2.3k citations

Ranked by citations received across their whole record, among researchers with at least three works on this topic.

Where is Financial Distress and Bankruptcy Prediction research done?

The largest centres of Financial Distress and Bankruptcy Prediction research in 2022–2025 are Beijing (China), Jakarta (Indonesia), Chennai (India) and Shanghai (China). Among places with at least 20 works in it, it is an unusually large share of all research in Greater Noida and Pune.

Largest cities, 2022–2025

  1. 1 Beijing China 159 works
  2. 2 Jakarta Indonesia 85 works
  3. 3 Chennai India 78 works
  4. 4 Shanghai China 77 works
  5. 5 Bandung Indonesia 62 works
  6. 6 Chengdu China 59 works
  7. 7 Surabaya Indonesia 49 works
  8. 8 Pune India 49 works
  9. 9 Bengaluru India 48 works
  10. 10 Guangzhou China 45 works

Where it is the local speciality

  1. Greater NoidaIN · 20.3 works7.5×
  2. PuneIN · 48.8 works5.3×
← less than its size predictsmore →

Location quotient: how much more of its research is in Financial Distress and Bankruptcy Prediction than the world average.

See Financial Distress and Bankruptcy Prediction on the map

Where is the best place to study Financial Distress and Bankruptcy Prediction?

Among universities, judged by research, Binus University, Southwestern University of Finance and Economics and Central University of Finance and Economics score highest, combining excellence, specialisation, size, growth and international reach. Research strength is one signal when choosing where to study; it does not measure teaching.

0%50%100%mean 32.27%fractional works in this node (log) →share in the world top 10% →Binus University: 30, 6.0%Southwestern University of Finance and Economics: 17, 30.0%Central University of Finance and Economics: 16, 34.3%Telkom University: 19, 21.2%Symbiosis International University: 19, 21.5%University of Žilina: 8, 41.7%University of Johannesburg: 10, 71.8%Christ University: 15, 15.7%Hefei University of Technology: 10, 67.2%Saveetha University: 23, 13.3%Central University o…Southwestern Univers…Telkom UniversityBinus University
above the meannear itbelow it

One dot per university in the table below. The upper left is the interesting corner: small places doing unusually strong work.

#UniversityScoreTop 10%SpecialisationWorksGrowth
1 Binus UniversityIndonesia 63.86.0%12.8×30 +187.5%
2 Southwestern University of Finance and EconomicsChina 62.030.0%26.6×17 +63.3%
3 Central University of Finance and EconomicsChina 60.134.3%33.0×16 +28.9%
4 Telkom UniversityIndonesia 58.321.2%8.2×19 +666.7%
5 Symbiosis International UniversityIndia 57.821.5%13.3×19
6 University of ŽilinaSlovakia 55.641.7%16.2×8
7 University of JohannesburgSouth Africa 54.371.8%3.6×10 +20.0%
8 Christ UniversityIndia 50.915.7%10.0×15
9 Hefei University of TechnologyChina 47.467.2%4.2×10 +3.7%
10 Saveetha UniversityIndia 46.013.3%5.4×23

Universities only. Score blends excellence (30%), specialisation (25%), size (20%), growth (15%) and international reach (10%), 2015–2022; growth compares 2010–14 with 2015–19.

Is Financial Distress and Bankruptcy Prediction research growing?

Output in 2018–2022 was 70% higher than in 2013–2017, peaking in 2025. The fastest-growing topics are Financial Distress and Bankruptcy Prediction.

19801990200020102020
grewheldshrank

The same series as a ribbon — one cell per year, darker for more. The line above answers how much; this answers when.

Which topics inside it are moving

Growth and decline on one axis around a shared zero. Two lists side by side hide the thing that matters: whether the growth dwarfs the decline, or the other way round.