Project Details
Project Description
Algorithmic systems (artificial intelligence, machine learning, and all data science technologies) have been rapidly growing in various industries due to its ability to identify patterns and trends that may not be apparent to human decision-makers, and to make decisions faster than humans. In financial sector, algorithmic systems are used to facilitate financial inclusion of marginalized and underserved communities. However, there are also concerns about ethical and social implications of algorithmic systems as they may be based on data that is historically biased or incomplete. This is especially relevant for high-risk algorithmic systems which have significant impact on individuals or society such as algorithmics systems used in finance. Consequently, the four critical dimensions of governance, ethical, legal, and social implications (GELSI) have become more important as government and organizations worldwide explore the potential of the technology. While previous research has proposed guidelines for the GELSI dimension in algorithmic systems, these guidelines primarily relate to general applications. The application of algorithmic systems in finance should be given special consideration because of the inherently risky and restrictive conditions. Our study will produce a GELSI framework for algorithmic systems in the financial technology domain.
Our proposed research method involves conducting numerous interviews to gain comprehensive and meaningful insights into the GELSI dimension of algorithmic systems in the fintech sector. We expect to interview 15 experts comprising those from financial authorities and central bank, finance industry, information technology experts and legal practitioners and professors. We will use interpretive phenomenological analysis (IPA), which delves into participants' personal and social domains by examining the meaning they attach to experiences, events, and conditions (Smith et al., 2009). We will follow the six principles of the interpretive field approach (Klein and Myers, 1999). i.e. the Fundamental Principle of the Hermeneutic, The Principle of Contextualization, The Principle of Abstraction and Generalization, The Principle of Interaction between the Researchers and the Subjects, The Principle of Dialogical Reasoning, and The Principle of Multiple Interpretations. Our study will highlight the critical role of financial authorities in strengthening their regulatory oversight and monitoring functions to ensure that algorithmic systems in the fintech industry are safe and beneficial for all stakeholders.
Our proposed research method involves conducting numerous interviews to gain comprehensive and meaningful insights into the GELSI dimension of algorithmic systems in the fintech sector. We expect to interview 15 experts comprising those from financial authorities and central bank, finance industry, information technology experts and legal practitioners and professors. We will use interpretive phenomenological analysis (IPA), which delves into participants' personal and social domains by examining the meaning they attach to experiences, events, and conditions (Smith et al., 2009). We will follow the six principles of the interpretive field approach (Klein and Myers, 1999). i.e. the Fundamental Principle of the Hermeneutic, The Principle of Contextualization, The Principle of Abstraction and Generalization, The Principle of Interaction between the Researchers and the Subjects, The Principle of Dialogical Reasoning, and The Principle of Multiple Interpretations. Our study will highlight the critical role of financial authorities in strengthening their regulatory oversight and monitoring functions to ensure that algorithmic systems in the fintech industry are safe and beneficial for all stakeholders.
| Status | Finished |
|---|---|
| Effective start/end date | 18/04/23 → 31/12/23 |