Robo-Advisors in the Financial Services Industry: Recommendations for Full-Scale Optimization, Digital Twin Integration, and Leveraging Natural Language Processing Trends
| dc.contributor.author | Bonelli, Marco I. | |
| dc.contributor.author | Sipahi Döngül, Esra | |
| dc.date.accessioned | 2023-10-10T06:20:01Z | |
| dc.date.available | 2023-10-10T06:20:01Z | |
| dc.date.issued | 2023 | |
| dc.department | Sağlık Bilimleri Fakültesi | |
| dc.description.abstract | Robo-advisors are a digital tool that has become popular in the financial services industry in recent years. These tools are used to manage investment portfolios and provide financial planning services. Robo-advisors have an important place in the relationship between businesses and financial services. Since the last few decades, the financial services industry has witnessed numerous innovative practices leading to the transformation of the sector amidst the rapid growth of disruptive technologies such as artificial intelligence, block chain and cloud technology, augmented reality, and virtual reality. The robotic automation process has further enhanced the ease and speed with which the consumers are being catered. Robo-advisory technology is designed to provide automated investment software for retail investors who lack the capital or expertise to hire a personal financial advisor. Robo-advisors usually evaluate new clients' risk tolerance and construct globally diversified portfolios using the principles of Modern Portfolio Theory. This study utilizes past data, behavioral studies, theories, and current market trends to develop recommendations for the robo-advisory industry in the US and globally. The first recommendation proposes utilizing fullscale optimization during the portfolio construction phase. The second recommendation focuses on incorporating digital twin capabilities into the software to benefit both robo-advisors and their clients. Lastly, the report forecasts the growth of Financial Technology companies improving Natural Language Processing via AI chatbots and how robo-advisors could leverage this trend. | |
| dc.identifier.doi | 10.1109/ICVR57957.2023.10169615 | |
| dc.identifier.endpage | 275 | en_US |
| dc.identifier.isbn | 979-835034581-0 | |
| dc.identifier.scopusquality | N/A | |
| dc.identifier.startpage | 268 | en_US |
| dc.identifier.uri | https:/dx.doi.org10.1109/ICVR57957.2023.10169615 | |
| dc.identifier.uri | https://hdl.handle.net/20.500.12451/11111 | |
| dc.indekslendigikaynak | Scopus | |
| dc.language.iso | en | |
| dc.publisher | Institute of Electrical and Electronics Engineers Inc. | |
| dc.relation.ispartof | 2023 9th International Conference on Virtual Reality, ICVR 2023 | |
| dc.relation.publicationcategory | Konferans Öğesi - Uluslararası - Kurum Öğretim Elemanı | |
| dc.rights | info:eu-repo/semantics/closedAccess | |
| dc.subject | Artificial Intelligence | |
| dc.subject | Chabots | |
| dc.subject | Enterprises | |
| dc.subject | Full-scale Optimization | |
| dc.subject | Modern Portfolio Theory | |
| dc.subject | Natural Language Processing | |
| dc.subject | Retail Investors | |
| dc.subject | Robo-advisors | |
| dc.title | Robo-Advisors in the Financial Services Industry: Recommendations for Full-Scale Optimization, Digital Twin Integration, and Leveraging Natural Language Processing Trends | |
| dc.type | Conference Object |
