AI Applications in Investment Management
Artificial intelligence (AI) has the potential to massively impact investment firms, analysts, investors and the overall wealth management industry.
Through their use of vast data sets, extending everywhere from satellite technology and sensors to consumer and macroeconomic data, AI and machine learning have the ability to shift investors’ views on traditional financial data. AI has the potential to generate considerable competitive advantages and inform investment decisions.
According to a 2017 report from JPMorgan (NYSE:JPM), machine learning will have an impact on both quantitative and fundamental investors. A number of companies are integrating predictive analytics, learning algorithms, AI solutions, expert systems and numerous data points into their systems.
For example, there is sentiment analysis firm Social Alpha, whose former CEO, Prem Melville, worked on IBM Watson. The firm is suited for the quantitative and fundamental investing camps, the report notes. Social Alpha provides clients with both market sentiment indicators and volatility indicators.
Rick Roche, managing director of Little Harbour Advisors, spoke to the Investing News Network (INN) about AI’s integration into the investment management sector.
Roche discussed AI uses, such as non-traditional data sources, relevance determination and macroeconomic analysis, risk modeling and natural language processing (NLP).
AI algorithms are being coalesced with human intelligence for investment managers and actors in the financial services industry. Fund managers and private equity firms are applying AI analytics to their portfolio decision making, management processes and future risk perspectives.
Here’s a look at three primary applications of AI and machine learning for investing, according to Roche.
