Page 96 - IMDR Journal 2025

Research Article
METHODOLOGY FINDINGS
Mixed-Methods Approach Financial Market Transformations
● AI in Trading
○High-Frequency Trading (HFT) Contributes to 35% of
India's NSE liquidity but amplifies flash crash risks (e.g.,
2024 Adani Group volatility).
○ Credit Scoring Non-traditional data (e.g., farmer crop
yields) improves loan approval rates by 27% in rural Kenya.

Findings of Case Study
HSBC Trade Finance Using Blockchain
The HSBC blockchain implementation in trade finance
demonstrates the technology's ability to simplify
traditionally time-consuming processes. HSBC partnered
with R3's Corda platform to conduct a letter of credit
Figure 1: Deep Technologies and Financial Market Applications
transactions involving Tricon Energy and Reliance
Table 1: Components and Data Sources Industries.The processing timeline was shortened from
nearly a week to under a day, illustrating the blockchain's
potential to make cross-border trade more efficient,
transparent, and traceable. The immutability and real-time
sharing of documents mitigated fraud and duplication risks,
while enhancing compliance and auditability.
AI in Nasdaq Operations
Nasdaq's use of artificial intelligence, particularly in
surveillance and market integrity, reveals the transformative
potential of deep technology. AI algorithms analyze millions
of trades daily, identifying anomalies and potential market
abuse in real time. Machine learning models can adapt to
new patterns and detect fraud more accurately than rule-
based methods. Nasdaq also utilizes AI in predictive
analytics to forecast market trends, enabling investors and
institutions to make informed and timely decisions.
Survey Insights
A survey was undertaken with financial experts and
technologists in India, as well as selected renowned
institutions, to gain thoughts on deep technology in financial
markets.
Key Findings
● Perceived Benefits
○ 85% cited increased operational efficiency.
○ 78% noted improved fraud detection and risk mitigation.
○ 72% believed deep tech enhances decision-making
through advanced analytics.
Figure 2: Digital Payment Penetration in Emerging Markets
● Barriers to Adoption
Analytical Framework
○ 60% identified regulatory uncertainty as a significant
barrier.
○ 54% mentioned high implementation costs.
○ 46% cited a lack of skilled manpower and integration
challenges.
The findings indicate strong confidence in deep tech's
potential, tempered by policy and practical considerations.
Discussion: Trends, Risks, and Policy Implications
● Trends
○ A clear trend toward automation, real-time data analytics,
Figure 3: Analytical Framework for Policy Interventions and decentralized frameworks.

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