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AI/Fintech and Asset Management Businesses

Author

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  • Yasuyuki Kato

    (Director of Research Institute, Money Design Co., Ltd. Research Professor of Tokyo Metropolitan University)

Abstract

In asset management business, AI and Fintech are now widely used. This article introduces a wide range of examples where AI and Fintech are applied to the development of asset management methods. One of the cores of their applied technology is text mining that converts text information into numerical data, which has evolved through deep learning. Big data has dramatically expanded the amount of input data to asset management models, and advanced prediction models have been developed by analyzing these data using deep learning. On the other hand, AI has brought about the harmful effect of making the model a black box. A lot of attempts are also being made to contribute to the investment theory by estimating risk factors with AI optimization technology and big data. Fintech, on the other hand, provides with automated wealth management, which has contributed to the expansion of asset management business for small-sized and inexperienced investors with robot advisors. In addition, the application of big data is progressing even in ESG investment, which has recently attracted a lot of attention.

Suggested Citation

  • Yasuyuki Kato, 2020. "AI/Fintech and Asset Management Businesses," Public Policy Review, Policy Research Institute, Ministry of Finance Japan, vol. 16(4), pages 1-28, August.
    • Handle: RePEc:mof:journl:ppr16_04_04
    as

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    File URL: http://www.mof.go.jp/english/pri/publication/pp_review/ppr16_04_04.pdf
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    References listed on IDEAS

    as
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    4. Paul C. Tetlock, 2007. "Giving Content to Investor Sentiment: The Role of Media in the Stock Market," Journal of Finance, American Finance Association, vol. 62(3), pages 1139-1168, June.
    Full references (including those not matched with items on IDEAS)

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    More about this item

    Keywords

    Fintech; asset management; big data; deep learning; text mining; LSTM; robot advisors; wealth management; ESG;
    All these keywords.

    JEL classification:

    • C1 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods and Methodology: General
    • C4 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods: Special Topics
    • C6 - Mathematical and Quantitative Methods - - Mathematical Methods; Programming Models; Mathematical and Simulation Modeling
    • C8 - Mathematical and Quantitative Methods - - Data Collection and Data Estimation Methodology; Computer Programs
    • G1 - Financial Economics - - General Financial Markets

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