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| Natura: | Recurso digital |
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Zenodo
2026
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| Accesso online: | https://doi.org/10.5281/zenodo.18213920 |
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| _version_ | 1866901213237215232 |
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| author | Ganesh Marimuthu |
| author_facet | Ganesh Marimuthu |
| contents | <p>The foreign exchange cross-currency trading sector is being faced with the enduring problems that are related to the realization of old technological infrastructure that compromises the competitiveness of institutions and efficiency in operations. The legacy systems that are typified by virtualized desktop systems, remote application delivery systems, batch-processing middleware systems, and monolithic server platforms impose significant latency, restrict real-time risk visibility, and constrain advanced execution capabilities that are necessary in the modern market. These technological limitations are in the form of delayed price discovery, poor quality of execution, higher operating expenses, and increased regulatory exposure. The shift to the modern infrastructure based on low-latency networking, distributed architecture using microservices, artificial intelligence-based decision management systems, and real-time risk management platforms resolves the essential constraints of the legacy environment. The machine learning approaches allow high-level functions such as smart routing of orders, predictive liquidity analytics, dynamic pricing optimization, and detection of anomalies that are beyond modern rule-based systems. A combination of kernel-bypass networking, event processing models, GPU-accelerated computing, and cloud native deployment architecture develops scalable, sustainable trading systems that can handle market data and place orders with response time on the order of a microsecond. Continuous monitoring of the exposure and detection of behavior patterns that are critical to regulatory compliance and prevention of risk before it occurs is achieved through real-time risk engines and AI-enhanced surveillance systems. The modernization framework provides quantifiable benefits in various areas such as the quality of execution, the precision of pricing, efficiency of operations, satisfaction by clients, and being competitive against electronically advanced market participants in the ever-technological-oriented financial markets.</p> |
| format | Recurso digital |
| id | zenodo_https___doi_org_10_5281_zenodo_18213920 |
| institution | Zenodo |
| language | |
| publishDate | 2026 |
| publisher | Zenodo |
| record_format | zenodo |
| spellingShingle | Modernizing Foreign Exchange Cross-Currency Trading: Challenges of Outdated Banking Infrastructure and the Path Toward Artificial Intelligence-Driven Low-Latency Technology Ganesh Marimuthu <p>The foreign exchange cross-currency trading sector is being faced with the enduring problems that are related to the realization of old technological infrastructure that compromises the competitiveness of institutions and efficiency in operations. The legacy systems that are typified by virtualized desktop systems, remote application delivery systems, batch-processing middleware systems, and monolithic server platforms impose significant latency, restrict real-time risk visibility, and constrain advanced execution capabilities that are necessary in the modern market. These technological limitations are in the form of delayed price discovery, poor quality of execution, higher operating expenses, and increased regulatory exposure. The shift to the modern infrastructure based on low-latency networking, distributed architecture using microservices, artificial intelligence-based decision management systems, and real-time risk management platforms resolves the essential constraints of the legacy environment. The machine learning approaches allow high-level functions such as smart routing of orders, predictive liquidity analytics, dynamic pricing optimization, and detection of anomalies that are beyond modern rule-based systems. A combination of kernel-bypass networking, event processing models, GPU-accelerated computing, and cloud native deployment architecture develops scalable, sustainable trading systems that can handle market data and place orders with response time on the order of a microsecond. Continuous monitoring of the exposure and detection of behavior patterns that are critical to regulatory compliance and prevention of risk before it occurs is achieved through real-time risk engines and AI-enhanced surveillance systems. The modernization framework provides quantifiable benefits in various areas such as the quality of execution, the precision of pricing, efficiency of operations, satisfaction by clients, and being competitive against electronically advanced market participants in the ever-technological-oriented financial markets.</p> |
| title | Modernizing Foreign Exchange Cross-Currency Trading: Challenges of Outdated Banking Infrastructure and the Path Toward Artificial Intelligence-Driven Low-Latency Technology |
| url | https://doi.org/10.5281/zenodo.18213920 |