The Fintech Cascade: Conceptualising App-Driven Herd Behaviour in the Indian Stock Market through Nudge Theory

The rapid proliferation of mobile trading and investment applications has transformed the way Indian retail investors access equity markets. Discount broking platforms, gamified user interfaces, and algorithm-driven notification systems have lowered participation costs while reshaping the psychological environment in which investment decisions are made. This conceptual paper proposes the “FinTech Cascade” framework, which integrates nudge theory with informational and reputational herd-behaviour models to explain how the choice architecture embedded in Indian investment applications may amplify herd behaviour among retail investors. Drawing on an integrative review of behavioural economics, financial herding, and digital choice-architecture literature, the paper identifies four structural gaps in existing research: the absence of an India-specific, app-level theoretical model; insufficient attention to the interaction between gamification and cultural risk attitudes; the lack of a unifying construct linking micro-level nudges to macro-level market cascades; and an underdeveloped regulatory vocabulary for distinguishing beneficial nudges from exploitative “dark nudges” in financial applications. The proposed framework conceptualises four sequential, cyclically reinforcing stages- nudge exposure, cognitive shortcut activation, social-proof amplification, and cascade materialisation- through which individual-level digital nudges may aggregate into collective market behaviour, subject to identification challenges discussed in Section 7. The paper introduces the dark-to-constructive nudge ratio as an operational regulatory construct and concludes with theoretical, managerial, and policy implications, along with an agenda for future empirical validation in the Indian context

Nudge Theory; Digital Nudging; Herd Behaviour

1. ANI. (2026, May 23). SEBI cracks down on finfluencer pump-and-dump network; warns retail investors against social media stock tips. ANI News. https://aninews.in/news/business/sebi-cracks-down-on-finfluencer-pump-and-dump-network-warns-retail-investors-against-social-media-stock-tips20260523110908/ [Google Scholar] [Crossref]

2. Banerjee, A. V. (1992). A simple model of herd behaviour. The Quarterly Journal of Economics, 107(3), 797–817. https://doi.org/10.2307/2118364 [Google Scholar] [Crossref]

3. Barber, B. M., Huang, X., Odean, T., & Schwarz, C. (2022). Attention-induced trading and returns: Evidence from Robinhood users. The Journal of Finance, 77(6), 3141–3190. https://doi.org/10.1111/jofi.13183 [Google Scholar] [Crossref]

4. Barberis, N., & Thaler, R. (2003). A survey of behavioural finance. In G. M. Constantinides, M. Harris, & R. M. Stulz (Eds.), Handbook of the economics of finance (Vol. 1, pp. 1053–1128). Elsevier. https://doi.org/10.1016/S1574-0102(03)01027-6 [Google Scholar] [Crossref]

5. Berkeley Technology Law Journal. (2026). The gamification of investments: A comparative approach between the US and EU. Berkeley Technology Law Journal. https://btlj.org/2025/11/the-gamification-of-investments-a-comparative-approach-between-the-us-and-eu/ [Google Scholar] [Crossref]

6. Bharti, N. S., & Kumar, A. (2025). Thematic review and discussion of research on herd behaviour in capital markets: Highlighting the gaps and proposing future research avenues. SAGE Open. https://doi.org/10.1177/21582440251319995 [Google Scholar] [Crossref]

7. Bikhchandani, S., & Sharma, S. (2000). Herd behaviour in financial markets. IMF Staff Papers, 47(3), 279–310. https://www.imf.org/external/pubs/ft/staffp/2001/01/bikhchan.htm [Google Scholar] [Crossref]

8. Bikhchandani, S., Hirshleifer, D., & Welch, I. (1992). A theory of fads, fashion, custom, and cultural change as informational cascades. Journal of Political Economy, 100(5), 992–1026. https://doi.org/10.1086/261849 [Google Scholar] [Crossref]

9. Brignull, H. (2023). Deceptive design. https://www.deceptive.design/ [Google Scholar] [Crossref]

10. Business Standard. (2025, December 8). Overall tally of Dmat accounts in India hits 21 crore. Business Standard. https://www.business-standard.com/markets/capital-market-news/overall-tally-of-dmat-accounts-in-india-hits-21-crore-125120800942_1.html [Google Scholar] [Crossref]

11. Business Standard. (2025, March 20). Only 2% of finfluencers Sebi-registered, yet 33% give stock recommendations. Business Standard. https://www.business-standard.com/markets/news/only-2-of-finfluencers-sebi-registered-yet-33-give-stock-recommendations-125032001196_1.html [Google Scholar] [Crossref]

12. Business Standard. (2026, July 28). 33% finfluencers recommend stocks but only 6% are Sebi registered: Report. Business Standard. https://www.business-standard.com/finance/news/33-finfluencers-recommend-stocks-but-only-6-are-sebi-registered-report-126072801516_1.html [Google Scholar] [Crossref]

13. Chang, E. C., Cheng, J. W., & Khorana, A. (2000). An examination of herd behaviour in equity markets: An international perspective. Journal of Banking & Finance, 24(10), 1651–1679. https://doi.org/10.1016/S0378-4266(99)00096-5 [Google Scholar] [Crossref]

14. Chapkovski, P., Khapko, M., & Zoican, M. (2024). Trading gamification and investor behaviour [Manuscript]. University of Toronto. https://doi.org/10.1287/mnsc.2022.02650 [Google Scholar] [Crossref]

15. Christie, W. G., & Huang, R. D. (1995). Following the pied piper: Do individual returns herd around the market? Financial Analysts Journal, 51(4), 31–37. https://doi.org/10.2469/faj.v51.n4.1918 [Google Scholar] [Crossref]

16. Devenow, A., & Welch, I. (1996). Rational herding in financial economics. European Economic Review, 40(3–5), 603–615. https://doi.org/10.1016/0014-2921(95)00073-9 [Google Scholar] [Crossref]

17. DT Next. (2025, November 25). Demat accounts in India hit record 185 million in 2024. DT Next. https://www.dtnext.in/news/business/demat-accounts-in-india-hit-record-185-million-in-2024-818612 [Google Scholar] [Crossref]

18. Gupta, P., & Kohli, B. (2021). Herding behaviour in the Indian stock market: An empirical study. Indian Journal of Finance, 15(5–7), 86–99. https://doi.org/10.17010/ijf/2021/v15i5-7/164495 [Google Scholar] [Crossref]

19. Hofstede Insights. (n.d.). Country comparison: India. Retrieved September 2026, from https://www.theculturefactor.com/country-comparison-tool?countries=india [Google Scholar] [Crossref]

20. Hwang, S., & Salmon, M. (2004). Market stress and herding. Journal of Empirical Finance, 11(4), 585–616. https://doi.org/10.1016/j.jempfin.2004.04.003 [Google Scholar] [Crossref]

21. Jaakkola, E. (2020). Designing conceptual articles: Four approaches. AMS Review, 10(1–2), 18–26. https://doi.org/10.1007/s13162-020-00161-0 [Google Scholar] [Crossref]

22. Kahneman, D., & Tversky, A. (1979). Prospect theory: An analysis of decision under risk. Econometrica, 47(2), 263–291. https://doi.org/10.2307/1914185 [Google Scholar] [Crossref]

23. Kanojia, S. (2020). Impact of herding on the returns in the Indian stock market: An empirical study. Review of Behavioural Finance, 14(1), 115–129. https://doi.org/10.1108/RBF-01-2020-0017 [Google Scholar] [Crossref]

24. Kumar, A., Bharti, M., & Bansal, S. (2016). An examination of herding behaviour in an emerging economy: A study of Indian stock market. Global Journal of Management and Business Research, 16(5), 1–9. https://doi.org/10.13140/RG.2.2.22754.58562 [Google Scholar] [Crossref]

25. MacInnis, D. J. (2011). A framework for conceptual contributions in marketing. Journal of Marketing, 75(4), 136–154. https://doi.org/10.1509/jmkg.75.4.136 [Google Scholar] [Crossref]

26. Mathur, A., Acar, G., Friedman, M. J., Lucherini, E., Mayer, J., Chetty, M., & Narayanan, A. (2019). Dark patterns at scale: Findings from a crawl of 11K shopping websites. Proceedings of the ACM on Human-Computer Interaction, 3(CSCW), 1–32. https://doi.org/10.1145/3359183 [Google Scholar] [Crossref]

27. Molla, S. A., & Das, S. (2024). Financial literacy in India: Insights from national financial literacy and inclusion survey (NCFE-FLIS) 2019 report. International Journal of Commerce and Management Research, 10(6), 63–68. https://www.managejournal.com/archives/2024/vol10/issue6/10139 [Google Scholar] [Crossref]

28. Nair, M. A., Balasubramanian, P., & Yermal, L. (2017). Factors influencing herding behaviour among Indian stock investors. In 2017 International Conference on Advances in Computing, Communication and Control (ICAC3) (pp. 1–6). IEEE. https://doi.org/10.1109/ICAC3.2017.8318774 [Google Scholar] [Crossref]

29. National Centre for Financial Education. (2019). Financial literacy and inclusion in India: NCFE-FLIS 2019 final report. National Centre for Financial Education. https://ncfe.org.in/wp-content/uploads/2023/12/NCFE-2019_Final_Report.pdf [Google Scholar] [Crossref]

30. National Institute of Securities Markets. (2026). Retail derivatives trading in India: SEBI’s alarming findings and regulatory measures. NISM. https://www.nism.ac.in/blog/equity-linked-exchange-traded-derivative-contracts-the-retail-rush-and-regulatory-measures/ [Google Scholar] [Crossref]

31. Prosad, J. M., Kapoor, S., & Sengupta, J. (2012). An examination of herd behaviour: An empirical Evidence from Indian equity market. International Journal of Trade, Economics and Finance, 3(2), 154–157. https://doi.org/10.7763/IJTEF.2012.V3.190 [Google Scholar] [Crossref]

32. Rakovic, I., & Inal, Y. (2023). Dark finance: Exploring deceptive design in investment apps. In J. Abdelnour Nocera, M. Kristín Lárusdóttir, H. Petrie, A. Piccinno, & M. Winckler (Eds.), Human-computer interaction – INTERACT 2023 (Lecture Notes in Computer Science, Vol. 14142, pp. 291–312). Springer. https://doi.org/10.1007/978-3-031-42280-5_20 [Google Scholar] [Crossref]

33. SBI Securities. (2024). Total number of demat accounts in India exceed 17.10 crore mark. SBI Securities. https://www.sbisecurities.in/blog/indias-demat-accounts-growth-crossed-17-crore-mark [Google Scholar] [Crossref]

34. Scharfstein, D. S., & Stein, J. C. (1990). Herd behaviour and investment. The American Economic Review, 80(3), 465–479. https://econpapers.repec.org/RePEc:aea:aecrev:v:80:y:1990:i:3:p:465-79 [Google Scholar] [Crossref]

35. Schneider, C., Weinmann, M., & vom Brocke, J. (2018). Digital nudging: Guiding online user choices through interface design. Communications of the ACM, 61(7), 67–73. https://doi.org/10.1145/3213765 [Google Scholar] [Crossref]

36. Securities and Exchange Board of India. (2023a, January 25). Analysis of profit and loss of individual traders dealing in equity F&O segment. SEBI. https://www.sebi.gov.in/reports-and-statistics/research/jan-2023/study-analysis-of-profit-and-loss-of-individual-traders-dealing-in-equity-fando-segment_67525.html [Google Scholar] [Crossref]

37. Securities and Exchange Board of India. (2023b, May 19). Risk disclosure with respect to trading by individual traders in Equity Futures & Options Segment (Circular No. SEBI/HO/MIRSD/MIRSD-PoD-1/P/CIR/2023/73). SEBI. https://www.sebi.gov.in/legal/circulars/may-2023/risk-disclosure-with-respect-to-trading-by-individual-traders-in-equity-futures-and-options-segment_71426.html [Google Scholar] [Crossref]

38. Securities and Exchange Board of India. (2025, May 29). Measures for enhancing trading convenience and strengthening risk monitoring in equity derivatives (Circular No. SEBI/HO/MRD/TPD-1/P/CIR/2025/79). SEBI. https://www.sebi.gov.in/legal/circulars/may-2025/measures-for-enhancing-trading-convenience-and-strengthening-risk-monitoring-in-equity-derivatives_94293.html [Google Scholar] [Crossref]

39. Thaler, R. H., & Sunstein, C. R. (2008). Nudge: Improving decisions about health, wealth, and happiness. Yale University Press. https://books.google.com/books/about/Nudge.html?id=dSJQn8egXvUC [Google Scholar] [Crossref]

40. Weinmann, M., Schneider, C., & vom Brocke, J. (2016). Digital nudging. Business & Information Systems Engineering, 58(6), 433–436. https://doi.org/10.1007/s12599-016-0453-1 [Google Scholar] [Crossref]

41. Welch, I. (2022). Retail raw: Wisdom of the Robinhood crowd and the COVID crisis. The Journal of Finance, 77(4), 1489–1527. https://doi.org/10.1111/jofi.13113 [Google Scholar] [Crossref]

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