Abstract
Artificial intelligence (AI) is rapidly transforming the global financial services industry. As a group of related technologies that include machine learning (ML) and deep learning (DL), AI has the potential to disrupt and refine the existing financial services industry. I review the extant academic, practitioner and policy related AI literature. I also detail the AI, ML and DL taxonomy as well as their various applications in the financial services industry.
A literature survey of AI and financial services cannot ignore the econometric aspects and their implications. ML methods are all about algorithms, rather than asymptotic statistical processes. Unlike maximum likelihood estimation, ML’s framework is less unified. To that end, I will discuss the ML approaches of unsupervised and supervised learning.
A literature survey of AI and financial services cannot ignore the econometric aspects and their implications. ML methods are all about algorithms, rather than asymptotic statistical processes. Unlike maximum likelihood estimation, ML’s framework is less unified. To that end, I will discuss the ML approaches of unsupervised and supervised learning.
| Original language | English |
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| Place of Publication | London |
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| Publisher | The Alan Turing Institute |
| Number of pages | 50 |
| DOIs | |
| Publication status | Published - 2019 |
| MoE publication type | D4 Published development or research report or study |
Keywords
- 512 Business and Management