In the rapidly evolving landscape of capital markets, leveraging advanced data analytics has become a cornerstone for front office innovation. Traditional systems can't keep up with the deluge of information, leaving investment professionals struggling to gain a competitive edge.

Financial institutions face challenges in developing and backtesting trading strategies, calibrating models, and performing causal risk scenario calculations. According to an IDC report, over 70% of data in an organization is unstructured, such as news and financial filings, and contains significant untapped value. This webinar reveals how you can transform your decision-making capabilities and sharpen your alpha generation strategies with a powerful combination of the NVIDIA and KX platforms to harness the full potential of your datasets.

The challenges associated with achieving high accuracy, low costs, low latency, and effective governance in capital markets can be addressed by increasing model training speed, improving data quality, and deploying large language models (LLMs). Using techniques like retrieval augmented generation (RAG) with vector embeddings, fine-tuned hybrid language models, and temporal inferencing for quantitative analysis enhances insight reliability and reduces costs. NVIDIA and KX empower financial institutions to optimize quant research, accelerate alpha returns, refine trading strategies, and streamline risk management by building a cost-effective "AI factory."

Join this webinar to discover how KX and NVIDIA can revolutionize capital markets operations to make faster, more informed, and more accurate decisions in real time to sharpen competitive edge and uncover new sources of alpha.

• How to leverage KX's KDB.AI, powered by the KDB+ time-series database, with NVIDIA NIM™, part of NVIDIA AI Enterprise, to address industry challenges to developing trading strategies.

• The key components of capital markets, including data processing, advanced model training leveraging machine learning and neural nets, and model deployment.

• How these technologies empower hedge funds, asset managers, and banks to make more informed, data-driven decisions than with traditional sources.

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