Deep Natural Language Processing in unstructured big data analysis and insights extraction - A quantitative study

Dash, Bibhu; Swayamsiddha, Swati; Ali, Azad

doi:10.1109/isssc56467.2022.10051524

Cited by 2 publications

(1 citation statement)

References 7 publications

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“…The growth rates are calculated based on the previous year's market size. In the antediluvian year 2016, AI applications in finance had already begun to gain momentum, commanding a market value of $1.9 billion [Dash, 2022]. Since that temporal juncture, the landscape has undergone a metamorphosis akin to a digital renaissance, bearing witness to a surge in the adoption of predictive analytics, machine learning algorithms, and the mellifluous articulation of Natural Language Processing (NLP).…”

Section: Figure 1: Global Fintech Market Yearly Growth Rate From 2016...mentioning

confidence: 99%

Advancements of AI and Machine Learning in FinTech Industry (2016-2020)

Kamuangu

2024

JEFAS

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The confluence of Artificial Intelligence (AI) and Machine Learning (ML) with the Financial Technology (FinTech) sector has ushered in a paradigm shift, fundamentally altering the contours of financial services. This scholarly endeavor undertakes a meticulous scrutiny of the evolutionary trajectory of AI and ML within the FinTech domain spanning the pivotal period of 2016 to 2020. Inextricably interwoven with notions of efficiency, security, and innovation, this exploration traverses the realms of operational processes, anti-fraud mechanisms, the bespoke landscape of personalized financial services, and the overarching influence on financial institutions. The canvas of this inquiry unfurls its historical panorama by anchoring in the pre-2016 epoch, elucidating the nascent manifestations of AI applications in finance. A discerning lens is cast upon pivotal technologies and algorithms that formed the bedrock of subsequent advancements. The narrative then unfurls to encapsulate the ascendancy of predictive analytics, the assimilation of both supervised and unsupervised learning paradigms, and the nuanced integration of Natural Language Processing (NLP) in the discerning analysis of financial data. Venturing into the substantive body of discourse, the examination scrutinizes specific strides, notably the assimilation of Robotic Process Automation (RPA) for the augmentation of operational efficiency. A close inspection follows the evolutionary trajectory of AI-driven algorithms tailored for the prophylaxis of fraud, fortifying the bulwarks against malfeasance within the financial ecosystem. Furthermore, the intricate tapestry of personalized financial services unfolds through the prism of recommendation systems, showcasing a nuanced blend of tailored financial offerings.

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Section: Figure 1: Global Fintech Market Yearly Growth Rate From 2016...mentioning

confidence: 99%