The online trading firm XTX Markets plans to build a substantial data center in Finland. This decision marks a significant departure from the current trend among financial institutions, which typically outsource their IT needs to major technology firms in Silicon Valley.
According to the Financial Times, the London-based market maker will construct a data center with a 250-megawatt capacity in Finland's Kajaani District. The first phase of this facility will be equipped with computing capabilities totaling 22.5MW.
Strategic Nordic Location
XTX's decision to establish its data center in Finland is due to the affordable electricity and the cool climatic conditions in the Nordic country. The region has emerged as a favorable destination for hosting data because there is less need for extensive cooling systems.
XTX's move to build its own data center reflects the firm's decision to maintain autonomy over its technological infrastructure. This approach contrasts with that of competitors like Citadel Securities, which have opted to use the cloud services of companies like Google for data storage and algorithm testing.
XTX Markets heavily relies on processing power to execute its algorithmic trading strategies. The company reportedly uses 25,000 graphics processing units computational resources to drive its operations.
Joshua Leahy, XTX's Chief Technology Officer, told the FT that the company secured the Kajaani site to boost its computing capacity. In Europe, data center space is limited, with demand surpassing supply. The market maker already operates a supercomputer based in Iceland.
Exploring New Technology
In February, XTX Markets unveiled an AI program in New York City that aims to advance research in algorithmic trading by merging finance with AI technology. This program promises to be a hub for exploring opportunities at the intersection of finance and machine learning.
The AI Residency Program, spearheaded by XTY Labs, offers two categories: Junior AI Residents and Senior AI Residents. These residents undertake research projects spanning 6 to 12 months. The focus of the program is to develop machine learning algorithms for the financial sector.
