arXiv:2607.04184v1 Announce Type: new Abstract: Market manipulation is the dubious practice of manipulating stock prices in order to make a quick profit, which truly degrades confidence on trading platforms. We implemented an unsupervised fraud-detection toolkit that begins with K-Means++ clustering to address this issue. A dataset of roughly one million financial transactions from 2012 to 2024 is used. In order to identify fraudulent trades and categorize them using market practice heuristic thresholds, the study suggests a clustering-based pipeline. The method highlights 2.02% of trades as s
The increasing sophistication of financial markets and the volume of transactions necessitate advanced AI-driven methods to detect manipulation, moving beyond traditional rule-based systems.
This development indicates a growing capability for financial institutions and regulators to employ AI for market surveillance, enhancing market integrity and investor confidence by identifying and deterring illicit activities.
The adoption of unsupervised AI for fraud detection shifts the paradigm from reactive, historical analysis to more proactive, real-time identification of suspicious trading patterns, potentially lowering the threshold for detection.
- · Financial Regulators
- · Stock Exchanges
- · Ethical Traders
- · AI/ML Solution Providers
- · Market Manipulators
- · Fraudulent Trading Firms
Reduced instances of market manipulation and increased penalties for offenders.
Heightened investor confidence and more efficient capital allocation due to fairer markets.
The development of adversarial AI techniques to circumvent detection, leading to an 'AI arms race' in financial surveillance.
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Read at arXiv cs.AI