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Data science and AI in FinTech: An overview [article]

Longbing Cao, Qiang Yang, Philip S. Yu
2021 arXiv   pre-print
The research on data science and AI in FinTech involves many latest progress made in smart FinTech for BankingTech, TradeTech, LendTech, InsurTech, WealthTech, PayTech, RiskTech, cryptocurrencies, and  ...  Smart FinTech is the new-generation FinTech, largely inspired and empowered by data science and new-generation AI and (DSAI) techniques.  ...  About the edition on DSAI in FinTech There are several initiatives on AI and data science in finance and FinTech, such as the special track on AI in FinTech organized in IJCAI'2020 2 and the panel on AI  ... 
arXiv:2007.12681v2 fatcat:jntzuwaktjg2hmmjypi5lvyht4

Data science and AI in FinTech: an overview

Longbing Cao, Qiang Yang, Philip S. Yu
2021 International Journal of Data Science and Analytics  
The research on data science and AI in FinTech involves many latest progress made in smart FinTech for BankingTech, Trade-Tech, LendTech, InsurTech, WealthTech, PayTech, RiskTech, cryptocurrencies, and  ...  Smart FinTech is the new-generation FinTech, largely inspired and empowered by data science and artificial intelligence (DSAI) techniques.  ...  -to what extent can autonomous, personalized and precision finance possibly transform personal finance, corporate finance, public finance and Internet finance?  ... 
doi:10.1007/s41060-021-00278-w fatcat:4qo3swacjbaaxh56p5bvhmjzqa

IFZ FINTECH STUDY 2022. An Overview of Swiss FinTech [article]

Thomas Ankenbrand, Denis Bieri, Moreno Frigg, Timon Kronenberger, Levin Reichmuth
2022 Zenodo  
After the size of the Swiss FinTech industry, measured in terms of the number of active Swiss FinTech companies, increased year on year in the past, a decline was recorded for the first time in 2021.  ...  Despite this seemingly negative development, there are also positive trends, such as the record high in venture capital activity.  ...  / Automatisation / Robotics; AI / Big Data = Analytics / Big Data / Artificial Intelligence.  ... 
doi:10.5281/zenodo.6420737 fatcat:bzlyvvz6lbcl7cho7s4knzzx2m

Frontiers in Service Science: Fintech Operations—An Overview of Recent Developments and Future Research Directions

Baile Lu, Shuai Hao, Michael Pinedo, Yuqian Xu
2021 Service Science  
In this paper, we provide a survey of recent developments in the fintech (financial technology) industry, focusing on the operational structures, the technologies involved, and the operational risks associated  ...  In particular, we discuss payment systems, algorithmic trading, robo-advisory, crowdfunding, and peer-to-peer lending. In the conclusion section, we discuss various promising research directions.  ...  Kang (2018) provides an overview of mobile payments within the fintech environment and discusses the security challenges of mobile payments.  ... 
doi:10.1287/serv.2021.0270 fatcat:l27qrn3gvfbjljjukpriblrvay

The Fintech Trilemma

Chris Brummer, Yesha Yadav
2017 Social Science Research Network  
financial technology (or 'fintech") in the post-crisis era.  ...  This Article offers a new theoretical framework for understanding and regulating fintech by showing how the supervision of financial innovation is invariably bound by what can be described as a policy  ...  novel types of data in the design of fintech products; (ii) the automation of algorithmic programs that often showcase advances in artificial intelligence (AI) and machine learning; and (iii) the emergence  ... 
doi:10.2139/ssrn.3054770 fatcat:oigdgu6xwbgafiozf3mf6ehs5m

Deep Reinforcement Learning: An Overview [article]

Yuxi Li
2018 arXiv   pre-print
We give an overview of recent exciting achievements of deep reinforcement learning (RL). We discuss six core elements, six important mechanisms, and twelve applications.  ...  Next we discuss core RL elements, including value function, in particular, Deep Q-Network (DQN), policy, reward, model, planning, and exploration.  ...  See Stoica et al. (2017) for systems challenges for AI. Nature in May 2015 and Science in July 2015 featured survey papers on machine learning/AI. Science Robotics launched in 2016.  ... 
arXiv:1701.07274v6 fatcat:x2es3yf3crhqblbbskhxelxf2q

{'en_US': 'Key Pillars for FinTech and Cybersecurity'}

Mircea Constantin Șcheau, Călin Mihail Rangu, Florin Vasile Popescu, Daniel Mihail Leu
2022 Acta Universitatis Danubius: Oeconomica  
We will provide an overview on the pace in which cybercrime in the financial sector grew in intensity as FinTech moved towards an end-to-end approach, the most common cyber threats which affect the financial  ...  The financial technology companies found themselves in the position to leverage advancements in fields such as data analytics and artificial intelligence as well as the new financial paradigm brought by  ...  Fintech companies integrate AI, blockchain, and financial science technologies in the financial sector to make them more secure, faster and more efficient.  ... 
doaj:d007f655539c4f98b6db27ed8261b1c0 fatcat:vtfcgexm2bd3xmxsmo7nkgwgte

AI Lifecycle Models Need To Be Revised. An Exploratory Study in Fintech [article]

Mark Haakman, Luís Cruz, Hennie Huijgens, Arie van Deursen
2021 arXiv   pre-print
Thus, the same development processes and standards in software engineering ought to be complied in artificial intelligence systems.  ...  We have found that the following stages have been overlooked by previous lifecycle models: data collection, feasibility study, documentation, model monitoring, and model risk assessment.  ...  Acknowledgments The authors would like to thank Irene Wijk, Shiler Khedri, and Elvan Kula for their willing contributions to this project.  ... 
arXiv:2010.02716v2 fatcat:5jdwun5e3zaxlpllfybbfl6uem

Machine Learning Behind The Scenes: An Exploratory Study in Fintech

Mark Haakman, Luís Cruz, Hennie Huijgens, Arie van Deursen
2020 Zenodo  
We analyze existing lifecycle models in the literature and refine them by adding stages for data collection, a feasibility study, documentation, model monitoring, and a sub-stage of model risk assessment  ...  fintech perspective, including a feasibility study, documentation, model evaluation, and model monitoring.  ...  ACKNOWLEDGMENTS The authors would like to thank Irene, Shiler, and Mieke, for their willing contributions to this project.  ... 
doi:10.5281/zenodo.3941476 fatcat:foab77kakrabvd4u67pgkhhqjy

Federated Learning for Privacy-Preserving: A Review of PII Data Analysis in Fintech

Bibhu Dash
2022 Zenodo  
There has been tremendous growth in the field of AI and machine learning. The developments across these fields have resulted in a considerable increase in other FinTech fields.  ...  The data analysis capabilities of AI and its cyber security functions have ensured that privacy has increased significantly.  ...  INTRODUCTION The fields of machine learning and data science have been described to have an essential role in science.  ... 
doi:10.5281/zenodo.7061473 fatcat:mg3mhhy4j5b4fgpngb4q3mg5wq

Shapley Feature Selection

Alex Gramegna, Paolo Giudici
2022 FinTech  
We propose to integrate an explainable AI approach, based on Shapley values, to provide more accurate information for feature selection.  ...  We test our proposal in a real setting, which concerns the prediction of the probability of default of Small and Medium Enterprises.  ...  Data Availability Statement: Not applicable. Conflicts of Interest: The authors declare no conflict of interest.  ... 
doi:10.3390/fintech1010006 fatcat:kie7gvgmajcctmtb7vnmq2lhwy

NLP in FinTech Applications: Past, Present and Future [article]

Chung-Chi Chen, Hen-Hsen Huang, Hsin-Hsi Chen
2020 arXiv   pre-print
Both formal documents and informal textual data are analyzed to understand corporate customers and personal customers.  ...  After summarizing the past and the recent challenges, we highlight several promising future research directions in the trend of FinTech and the open finance tendency.  ...  In this paper, we provide an overview of the applications and the related approaches in the FinTech trend, and blueprint promising future research directions for NLP and finance researchers.  ... 
arXiv:2005.01320v1 fatcat:74hgnfpkbjbxzn5asnhxynu72q

Fintech, Regtech and Suptech: Three Dimensional Approaches to Digital Finance

2021 Nepalese Journal of Management Science and Research  
There are three stages in the implementation of digital finance viz., Fintech, Regtech and Suptech.  ...  'Fintech' is an application of Technology for financial services that include; digital payments and e-money, international remittances, personal and business loans, peer-topeer lending platforms, crowd  ...  Figure Figure 2: The Framework of Fintech Figure Figure 3: An Overview of Regtech 2 The framework of fintech: Figure 2 depicts the framework of Fintech Credit card was invented in 1950.  ... 
doi:10.53056/njmsr-2021.001.1 fatcat:q2jgq5i5lvf27a3pnovzxdwsrm

An overview of NexusLinguarum use cases: Current status and challenges

Sara Carvalho, Ilan Kernerman
2021 Zenodo  
In addition, it describes the cooperation with the other WGs of NexusLinguarum. URL: https://lexicala.com/review/2021/an-overview-of-nexuslinguarum-use-cases-current-status-and-challenges/  ...  Working Group 4 (WG4) of the NexusLinguarum COST Action – European network for Web-centred linguistic data science (CA18209) – is dedicated to applying and validating the Action's methodologies and technologies  ...  Use Cases in Life Sciences Overview. The area of Life Sciences is broad and heterogeneous.  ... 
doi:10.5281/zenodo.5729078 fatcat:t3z3chvtmjbofdyk72wxzofmku

Fintech Risk Management: A Research Challenge for Artificial Intelligence in Finance

Paolo Giudici
2018 Frontiers in Artificial Intelligence  
Fintech solutions that make use of big data analytics, artificial intelligence and blockchain technologies are currently introduced at an unprecedented rate.  ...  concerns to apply regulations in an effective and efficient way and which protect consumers and investors.  ...  Research in Big data and Blockchain, but also in AI more generally, neatly connects to other Frontiers' journals, such as Frontiers in Big Data and Frontiers in Blockchain.  ... 
doi:10.3389/frai.2018.00001 pmid:33733089 pmcid:PMC7861247 fatcat:lvjxkqnycbeahgddn3aozz5inu
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