Abstract
This paper focuses broadly on the application of various types of AI technology in the buy-side of financial services and more specifically on the application of AI to financial portfolio management. Current market volatility in response to the COVID-19 pandemic has given new urgency to the perennial challenge of achieving quality investment returns, and the ever-present trade-off between return and risk that all portfolio managers have to master. The complexity and volume of relevant information today, and the rate of change in the current environment, have only heightened the need for smarter financial choices. Various types of AI may be used to respectively achieve higher portfolio returns, increase operational efficiency, and enhance the customer experience. Successful AI usage will always involve an optimum mix of machine-provided and human-based services, where the AI enhances and accelerates human portfolio decision-making and saves labor costs.
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Notes
- 1.
The preference for avoiding losses over generating equivalent gains.
- 2.
The interpretation of new information to confirm preexisting beliefs.
- 3.
While machine learning is imprecise used these days as a synonym for AI, it is more correctly a subset of AI, and represents a specific approach to AI.
- 4.
A form of evolutionary computation—see Sect. 9.2.1.
- 5.
A form of evolutionary computation—see Sect. 9.2.1
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Byrum, J. (2022). AI in Financial Portfolio Management: Practical Considerations and Use Cases. In: Babich, V., Birge, J.R., Hilary, G. (eds) Innovative Technology at the Interface of Finance and Operations. Springer Series in Supply Chain Management, vol 11. Springer, Cham. https://doi.org/10.1007/978-3-030-75729-8_9
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