With its ability to understand and learn, AI is the technology of the future and not just a passing fad<\/strong>. And this is true not only for capital markets. Association for Financial Markets in Europe (AFME) identifies the ability of Artificial Intelligence (AI) in boosting the prowess and efficiency of multiple functions related to the capital markets<\/a> viz. client communication, compliance, reporting and management of risk, and processing at the back end. An October 2019 report by Greenwich Associates found almost half of professionals in the capital market sector already using AI<\/a>. Echoing AFME\u2019s findings is a report authored by Deloitte in conjunction with the World Economic Forum<\/a> which pinpoints AI\u2019s potential to decentralize capital availability, identify hidden investment avenues, free up human resources for high value operations, better track risk exposure, and empower real time optimization of capital reserves. AFME\u2019s report also sheds light on the possible hazards of AI in capital markets<\/a> viz. unrepresentative data input, escalation of unintended negative consequences, and potential curtailment of transparency. Proper governance, operational control, education-awareness, robust data quality, and standardization can, however, address these issues<\/a>, the AFME report goes on to say.\u00a0<\/p>\n Although we may not realize it yet, we are at the threshold of the knowledge economy, wherein, in all likelihood, analysis of tons of data in order to smoke out precious insights and initiating action based on such insights will be the standard modus operandi of the successful.\u00a0<\/p>\n One tool capable of undertaking all this is Artificial Intelligence (AI). Machines are better than humans when evaluating large quantum of data to spot trends and developments. AI goes a step ahead and makes machines capable of acting on their own on the basis of such evaluation.\u00a0<\/p>\n Specific to capital markets, AI will improve<\/a>: prediction of trigger events, market risk visualization, stock selection algorithms, processing-analysis of natural language, evaluation of liquidity risk, intelligent trade matching, detection of financial crime-misuse, evaluation of main cause of system outages, analysis of expectations to identify needs and opportunities of clients, and regulatory compliance among others.\u00a0<\/p>\n Located at the other end of the spectrum are the hazards of utilizing AI in capital markets. First, any data analysis is as good as the data entered. Unrepresentative data can cause issues because AI will act on the analysis of flawed data<\/a>.\u00a0\u00a0<\/p>\n Second, in the absence of thorough understanding of AI, the risk of unintended negative consequences gets heightened<\/a>. Third, transparency may decline as the logic of some of its decisions becomes hard to comprehend<\/a>.\u00a0\u00a0<\/p>\nAI: Powered by actionable intelligence<\/strong><\/h4>\n
Analysis is only as good as data\u00a0<\/strong><\/h4>\n
Standards and governance: The solutions<\/h4>\n