Rise of the Machines? AI and Big Data in Asset Management
Rise of the Machines? AI and Big Data in Asset Management
The digital data explosion and recent refinements in both artificial intelligence (AI) and machine learning techniques present both challenges and opportunities across the entire asset management value chain. Despite significant media coverage suggesting otherwise, recent actual survey responses suggest that the investment industry is still in the relatively early stages of adoption of advanced technologies, and that human intervention remains important.
Recent IT industry data estimates that data production in 2020 will be 44 times greater than it was a decade earlier, and the number of connected devices will be three times that of the global population by 2021. Investors face a number of challenges in how they approach implementation and integration of AI and big data analysis across both front and back office applications before they begin to reap any of the potential benefits. Savvy Investor presents a selection of the best white papers which investigate the topic.
FEATURED PAPERS
AI Pioneers In Investment Management (CFA Institute, 2019)
This report and survey from the CFA Institute finds surprisingly few participants currently exploiting artificial intelligence (AI) and big data applications in their investment process. Interviews with a number of institutions who are already using the technologies (AI pioneers) may offer some guidance for those considering taking the next steps.
Using AI to power the retirement savings plan of the future (Invesco, 2019)
For compliance reasons, this paper is only accessible in certain geographies
In this recent paper, Invesco discusses how technological advances in artificial intelligence (AI) might be applied to retirement plan design with the aim of improving participant engagement and satisfaction.
AI IN ASSET MANGEMENT
Artificial Intelligence in Investment Management (Meketa Group, 2019)
Meketa explores how artificial intelligence (AI) in investing can take many forms, but in the majority of cases, it mainly 'adds value' by expanding upon or improving, existing processes.
The Ubiquity of Data: Challenges and Opportunities for Asset Managers (Lazard)
Lazard investigates the proliferation of big data, and suggests how it might be utilised in several of the processes involved in asset mangement.
Machine Learning in Asset Management (2019)
A number of trading strategies and portfolio optimisation techiques that have been developed from machine learning are presented in this SSRN paper.
Video: Investment Decision Making in an AI World (CFA Institute, 2019)
This video by the CFA Institute explains some of the basic terminologies used and then attempts to chart a map of the artificial intelligence (AI) landscape.
AI in Finance: Opportunities and risks you need to know (Intech, 2019)
For compliance reasons, this paper is only accessible in certain geographies
Intech's short guide presents investors with an insight into some of the risks and opportunities presented by artificial intelligence (AI) in an asset management context.
How Technology is Creating the Next-Generation Wealth Manager (Forbes, 2019)
A recent Forbes survey investigates the use of artificial intelligence (AI) and sophisticated analysis amongst wealth managers and suggests that future success lies in its considered deployment and integration in order to enhance the client experience.
Machine Learning for Investment Managers (SimCorp, 2019)
SimCorp presents four innovative cases for the use of artificial intelligence within the investment management industry.
AI IN INDUSTRY
The digital toolbox: emergency care for our health care system (Robeco, 2019)
Robeco's paper explores how the use of a 'digital toolbox' comprising artificial intelligence (AI), genomics and the use of sensors might help to transform the health care system.
Artificial Intelligence: Real opportunity (Franklin Templeton, 2019)
For compliance reasons, this paper is only accessible in the EMEA region
Franklin Templeton suggests that in the artificial intelligence (AI) sphere, the most successful companies are likely to be those a) retaining ownership of, or controlling access to distinct datasets and b) with the ability to interrogate and learn from such data.
Biannual global analysis of investment in fintech (KPMG, 2019)
KPMG's biennual report highlights significant developments and trends within the global fintech industry, whilst attempting to explore some of the key issues and challenges that it currently faces.
Future-Proofing Your Asset Allocation in the Age of Mega Trends (BNY Mellon/CREATE-Research, 2019)
In this extensive report, CREATE - Research and BNY Mellon offer an insight into how the asset management industry is currently responding to two 'mega-trend' challenges, those of artifical intelligence (AI) and climate change.
Swimming in data lakes and running through random forests (LGIM blog, 2019)
For compliance reasons, this paper is NOT accessible in the United States and Canada
LGIM's Quant Strategist presents his interpretation of the terms artificial intelligence (AI) and machine learning.
