| Description |
1 online resource |
| Contents |
Executive summary -- 1. Artificial intelligence, machine learning and big data in financial services -- 2. AI/ML, big data in finance: benefits and impact on business models/activity of financial sector paticipants -- 3. Emerging risks from the use of AI/ML/Big data and possible risk mitigation tools -- 4. Policy responses and implications -- References -- Notes |
| Summary |
"AI applications in finance may create or intensify financial and non-financial risks, and give rise to potential financial consumer and investor protection considerations. The use of AI amplifies risks that could affect a financial institution’s safety and soundness, given the lack of explainability or interpretability of AI model processes, with potential for pro-cyclicality and systemic risk in the markets. The difficulty in understanding how the model generates results could create possible incompatibilities with existing financial supervision and internal governance frameworks, while it may even challenge the technology-neutral approach to policymaking. AI may present particular risks of consumer protection, such as risks of biased, unfair or discriminatory consumer results, or data management and usage concerns. While many of the potential risks associated with AI in finance are not unique to AI, the use of AI could amplify such vulnerabilities given the extent of complexity of the techniques employed, the dynamic adaptability of AI-based models and their level of autonomy for the most advanced AI applications." -- executive summary, page 7 |
| Notes |
Title from title screen, viewed 16 March 2022. |
| Bibliography |
Includes bibliographical references |
| Subject |
Artificial intelligence.
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Finance -- Technological innovations.
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Financial services industry -- Information technology.
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Machine learning -- Finance.
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Big data. -- Finance.
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| Form |
Electronic book
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