How AI and big data improve the investing process

Recently published, Release 1 of the AI Handbook offers “guided tours” of the state of data science and machine learning applications in the financial sector through in-depth analyses from writers at Robeco, Goldman Sachs, and Neuberger Berman. Advances in natural language processing and generation are discussed in the context of investments, particularly ESG analysis, by contributors from Applied AI, AllianceBernstein, Off-Script Systems, and Two Centuries Investments.

Ahead-of-the-curve research on trading with machine learning and big data from Virtu Financial and Man Group will be included in Release II of the AI Handbook, which will be released in April. Ping An and NVIDIA will provide in-depth analyses of chatbot, knowledge graph, and AI infrastructure from the standpoint of investments, including intelligent customer service, rapid AI, and use cases in investment management. APG Asset Management is a case study of Symbolic AI.

The AI Handbook is based on practical and tested solutions, published from the viewpoint of the industry.

“The industry’s needs have grown from asking for proof that AI and big data work, to asking for an action plan that can provide support to firms’ strategy as machine learning methodologies rapidly become mainstream. The AI Handbook is the latest in a series of CFA Institute research aimed at equipping practitioners and policymakers with the tools to evaluate and incorporate AI and big data techniques with the highest standards,” Larry Cao, CFA, Senior Director of Research at CFA Institute.

“There is no single best operating model for data science integration that fits all asset management firms. Technologies must be customized to fit organizational culture, structure, core value proposition, strategic prioritization, and budgeting methods. The handbook offers a companion to support firms to start, refine, or plan the next phase of their data science journey,” Cao added.

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