Using a GPU (Graphics Processing Unit) can accelerate trading by allowing for faster processing of large amounts of data. This can be particularly useful for traditional banks, capital market firms and fintech companies that rely on data-intensive trading algorithms and need to process large amounts of data in real-time. Running machine learning algorithms: Machine learning algorithms can be computationally intensive, and a GPU can speed up the training process. This can be especially useful for developing and testing trading strategies that rely on machine learning. Data processing: A GPU can process large amounts of data quickly, which can be useful for tasks such as real-time data analysis and market monitoring.

FREMONT, CA: Interrelated factors of technological advances, regulations, and market sentiments are shaping the present and the future of capital market firms in Europe. The wide spectrum of businesses that come under the umbrella term of capital markets is set to focus on different sets of digital capabilities to expand operations and enhance profitability. However, there has been consistency in trends that highlight the popular adoption of certain advanced technologies. Some of these technological trends, along with how capital market companies have interpreted them are mentioned in this article. One of the basic requirements for today's capital market firms in Europe is the digital infrastructure.

The pace of transformation in the capital markets is accelerating. How are firms keeping up and staying ahead? Leveraging automation and choosing the right providers is essential. Here is the guide for business leaders. FREMONT, CA: The pursuit of enhancing automation in capital markets goes way back in time.

The pace of transformation in the capital markets is accelerating. How are firms keeping up and staying ahead? Leveraging automation and choosing the right providers is essential. Here is the guide for business leaders. FREMONT, CA: The pursuit of enhancing automation in capital markets goes way back in time.

How Artificial Intelligence will revolutionize financial services is a hot topic among Wall Street technologists. But, just as a home renovation might be delayed by the discovery of extensive foundation problems that need to be repaired first, the financial services industry must improve the quality of its data before it can realize the benefits of AI. Early front-office AI applications, such as Deutsche Bank using AI to predict equity pricing, have won headlines. But there is also significant momentum around applying AI to post-trade processing, compliance and risk management: Instead of manually searching for a needle in a haystack to learn why a trade failed to identify a real issue, AI can pre-emptively flag problems and solve the exception. However, while many capital markets firms have explored AI initiatives, few of these pilot programs (less than 15% according to Forrester Research) have made it into production to yield real business value.

According to a recently released IDC spending guide, worldwide Cognitive Systems and Artificial Intelligence revenues are forecast to surge past USD 47Billion in 2020. According to another research firm, Opimas Research, in 2017, financial firms alone will spend more than USD 1.5 billion on artificial intelligence (AI) related technologies and by 2021, USD 2.8 billion, representing an increase of a whopping 75%. Capital Markets, like every other space, is seeing a surge in technological solutions that are coming of age and delivering increased performance- especially in areas of advanced analytics, real time trade-processing platforms and improved regulatory compliance. These technological solutions in a way, have come as a panacea for Capital Market firms, which are grappling with increasing compliance costs and shrinking bottom lines. Thanks to these macroeconomic factors, Capital Market firms are increasingly looking towards advanced technology solutions like AI to increase employee efficiency and aid faster decision making.