Fintech adoption dynamics in a pandemic: An experience from some financial institutions in Nigeria during COVID-19 using machine learning approach

Edo, Onome Christopher; Etu, Egbe-Etu; Tenebe, I.T.; Oladele, Oluwarotimi Samuel; Edo, Sílvia; Diekola, Oladapo Ayodeji; Emakhu, Joshua

doi:10.1080/23311975.2023.2242985

Cited by 8 publications

(5 citation statements)

References 95 publications

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“…AI-based metaverse fintech, big data-driven investment decisions, virtual asset and real estate transactions and transferability, AI-powered financial advising, and immersive digital banking (Gonçalves et al, 2023;Li et al, 2023;Rahmani et al, 2023) develop on blockchain and cryptocurrency technologies, financial data modeling and visualization tools, and Internet of Thingsbased digital twins (Ben Romdhane et al, 2023;Lai et al, 2023;Yan, 2023) across the decentralized, scalable, and interoperable infrastructure of the extended reality-and blockchain-based metaverse. AI-enhanced financial, payment, and banking services (Khan et al, 2023;Rahmani et al, 2023;Wang et al, 2023) improve customer experiences and expectations (Jiang, 2023;Lai et al, 2023;Zhao et al, 2023) by managing and leveraging a seamless flow of data (Jareño & Yousaf, 2023;Mirza et al, 2023b;Su & Xu, 2023), boosting revenue and profitability (Gonçalves et al, 2023;Wu et al, 2023;Zheng et al, 2023), and building hyper-personalized and tailored digital products (Awais et al, 2023;Babaei et al, 2023;Ha, 2023) by use of mobile wallets, algorithmic trading tools, cloud-assisted digital systems, and realtime financial data (Edo et al, 2023;He et al, 2023b;Mahmud et al, 2023).…”

Section: Discussionmentioning

confidence: 99%

“…AI IoT-based fintech innovations further green bonds and financial operations, sustainable economic development, clean energy, and business decision-making (Awais et al, 2023;Ha, 2023), shaping green economic growth. Customer service quality influences perceived risk and behavioral intention as regards financial digitalization, electronic payment systems, mobile banking apps and financial transactions (Edo et al, 2023), improving machine learning-based fintech adoption prediction accuracy. Usage continuance intention of value-adding fintech products and services in mobile banking (Mahmud et al, 2023) articulates technological and financial capabilities of sustainable economic development.…”

Section: Discussionmentioning

confidence: 99%

“…AI-based predictive maintenance and product-complexity management, geolocation tracking, machine learning, location intelligence data, and face recognition technologies (Jiang, 2023;Lai et al, 2023;Zhao et al, 2023) can drive transactional engagement, operational data and support, and investment decisions (Jareño & Yousaf, 2023;Mirza et al, 2023b;Su & Xu, 2023) for frictionless mobile transaction experiences. Generative AI, machine learning algorithms, and big data analytics assist financial transaction networks in historical data analysis, payment processing and routing optimization, regulatory filing automation, transaction time and operational cost decrease, high-volume payment flow and spend management, and risk scenario simulation (Edo et al, 2023;He et al, 2023b;Mahmud et al, 2023).…”

Section: Literature Reviewmentioning

confidence: 99%

“…Previous literature has indicated that AI-powered mobile apps, blockchain-based payment services, and financial planning, payment automation, and budgeting tools (Akmal et al, 2023;Osei-Assibey Bonsu et al, 2023;Upreti et al, 2023;Zhao et al, 2023) optimize customized credit products in terms of automated debt payments, refinancing loans, and credit score building (Jareño & Yousaf, 2023;Lai et al, 2023;Mirza et al, 2023b;Su & Xu, 2023), driving operational excellence, providing personalized feedback and targeted coaching (Ben Romdhane et al, 2023;Gonçalves et al, 2023;Li et al, 2023;Rahmani et al, 2023), and delivering increased customer engagement, service, and satisfaction (Edo et al, 2023;He et al, 2023b;Mahmud et al, 2023). We draw systematic comparisons and specify the need to focus on how artificial IoT-based fintech and generative AI algorithms enable banking operations and loan application automatic approval through multi-layer transaction monitoring for instant payments, automation and digitization services, and digital wallets (Caragea et al, 2023;Jareño & Yousaf, 2023;Jiang, 2023;Qiu et al, 2023), leading to hyperpersonalized financial services and products (Awais et al, 2023;Babaei et al, 2023;Ha, 2023) with lowered operational costs and increased sustainable value creation.…”

Section: Introductionmentioning

confidence: 99%

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Big data management algorithms in artificial Internet of Things-based fintech

Andronie,

Iatagan,

Uță

et al. 2023

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Research background: Fintech companies should optimize banking sector performance in assisting enterprise financing as a result of firm digitalization. Artificial IoT-based fintech-based digital transformation can relevantly reverse credit resource misdistribution brought about by corrupt relationship chains. Purpose of the article: We aim to show that fintech can decrease transaction expenses and consolidates firm stock liquidity, enabling excess leverage decrease and cutting down information asymmetry and transaction expenses across capital markets. AI- and IoT-based fintechs enable immersive and collaborative financial transactions, purchases, and investments in relation to payment tokens and metaverse wallets, managing financial data, infrastructure, and value exchange across shared interactive virtual 3D and simulated digital environments. Methods: AMSTAR is a comprehensive critical measurement tool harnessed in systematic review methodological quality evaluation, DistillerSR is harnessed in producing accurate and transparent evidence-based research through literature review stage automation, MMAT appraises and describes study checklist across systematic mixed studies reviews in terms of content validity and methodological quality predictors, Rayyan is a responsive and intuitive knowledge synthesis tool and cloud-based architecture for article inclusion and exclusion suggestions, and ROBIS appraises systematic review bias risk in relation to relevance and concerns. As a reporting quality assessment tool, the PRISMA checklist and flow diagram, generated by a Shiny App, was used. As bibliometric visualization and construction tools for large datasets and networks, Dimensions and VOSviewer were leveraged. Search terms were “fintech” + “artificial intelligence”, “big data management algorithms”, and “Internet of Things”, search period was June 2023, published research inspected was 2023, and selected sources were 35 out of 188. Findings & value added: The growing volume of financial products and optimized operational performance of financial industries generated by fintech can provide firms with multifarious financing options quickly. Big data-driven fintech innovations are pivotal in banking and capital markets in relation to financial institution operational efficiency. Through data-driven technological and process innovation capabilities, AI system-based businesses can further automated services.

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Section: Discussionmentioning

confidence: 99%

Section: Discussionmentioning

confidence: 99%

Section: Literature Reviewmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

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Big data management algorithms in artificial Internet of Things-based fintech

Andronie,

Iatagan,

Uță

et al. 2023

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“…UTAUT's scope has broadened to scrutinize the bedrock factors affecting the intention to use information systems and technology applications (Alkhwaldi et al, 2022;Eneizan et al, 2022). It has found utility in explaining the adoption and usage of various technologies such as online learning management systems, green banking, intelligent elevators, digital health, e-government, advanced driver assistance systems, engineering e-laboratories, and AI-based intelligent products (Almogren & Aljammaz, 2022;Bouteraa et al, 2023;Edo et al, 2023;Rahman et al, 2017;Sohn & Kwon, 2020). In the consumer realm,…”

Section: Introductionmentioning

confidence: 99%

Consumers' behavioral intention toward online shopping in the post‐COVID‐19 period

Khatoon,

Anwar,

Shamsi

et al. 2023

Int J Consumer Studies

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Infectious COVID‐19 transformed the world overnight, freezing all physical activities and forcing the majority toward online mode. Technology came up as a savior to alleviate the consequences of COVID‐19 on the economy, causing a rapid transformation in consumers' behavior, and an overall jump in the sale of e‐commerce could be witnessed globally. This paper aims to explore the factors that caused the transformation in consumers' behavioral attitude (AT) and intention toward online shopping (BITOS). The study integrates the TPB and UTAUT models while adding two additional variables, namely, perceived risks (PR) and perceived benefits (PB), to predict consumers' BITOS. A survey was conducted to collect a sample of 402 consumers Aligarh city, and the National Capital Region of India using the mall intercept sampling method. The data were analysed to establish the measurement model and test the hypothesized structural model with the Smart‐PLS software. The study's findings confirmed that PB, subjective social norms, perceived ease of use, and perceived usefulness positively affect AT and BITOS, whereas PR does not influence AT and BITOS. The study also indicated that AT has a positive effect on BITOS. Concerning AT, it does not mediate the relationship between PR and BITOS; however, it mediates between the direct link PB and BITOS, making it stronger. The study's findings help the E‐commerce industry understand consumers' transformed attitudes/intentions and restructure their strategies to strengthen their online business further. Despite its regional and design limitations, it contributes significantly to the current research on online shopping behavior in India during COVID‐19.

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