Build Smarter Trading Systems and Save Resources Hedge funds, asset managers, and exchanges increasingly look to AI for building algorithmic trading systems, which are powered by advances in GPUs and cloud computing. Unlike conventional algorithmic trading, which requires programmers to update rules, ML- based systems can learn peak trading patterns based on past data while also responding to current market conditions and continuously evaluating their own performance. Price and volume predictions are common uses, and ML models are also capable of adjusting quickly to market volatility. Meanwhile, analysts involved in portfolio optimization can use natural language processing (NLP) to extract a higher quantity of relevant information from unstructured data faster than ever before, reducing the need for labor-intensive research. AI is essential for mining knowledge from constantly updating sources—from brokerage reports to social media—with diligence and speed that can’t be matched by staff. These capabilities provide quick, accurate insights that are now more accessible, even for non-technical financial managers. Realizing the Potential of AI in Financial Services | 5