Artificial intelligence (AI) and machine learning techniques are finding their way into financial services. Ranging from operational efficiencies to more effective detection of fraud and money laundering, firms are embracing techniques that find patterns, learn from them and can subsequently act on signals coming out of large volumes of data. According to Martijn Groot, VP Marketing and Strategy, Asset Control, the most promising, and potentially lucrative, use cases are in investment management though. Among the groups that benefit most are hedge fund managers and other active investors who increasingly rely on AI and machine learning to analyse large data sets for actionable signals that support a faster; better-informed decision-making process. Helping this trend is the increased availability of data sets that provide additional colour and that complement the typical market data feeds from aggregators, such as Bloomberg or Refinitiv, range from data gathered through web scraping, textual analysis of news, social media and earnings calls. Data is also gathered through transactional information from credit card data, email receipts and point of sale (POS) data.