Using artificial intelligence technologies to predict cash flow

Dadteev, Kazbek; Shchukin, Boris A.; Nemeshaev, Sergey

doi:10.1016/j.procs.2020.02.163

Cited by 7 publications

(3 citation statements)

References 3 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…Depending on the quality and quantity of the available time-series transactional data, the selection of machine learning methods for cash flow prediction may vary Dadteev et al (2020). Ensemble methods like XGBoost are particularly suitable when dealing with intricate relationships and feature selection requirements Xie and Zhang (2021).…”

Section: Cash Flow Model Trainingmentioning

confidence: 99%

Decentralized Data and Artificial Intelligence Orchestration for Transparent and Efficient Small and Medium-Sized Enterprises Trade Financing

Alirezaie,

Hoffman,

Zabihi

et al. 2024

JRFM

View full text Add to dashboard Cite

The complexities arising from disparate data sources, conflicting contracts, residency requirements, and the demand for multiple AI models in trade finance supply chains have hindered small and medium-sized enterprises (SMEs) with limited resources from harnessing the benefits of artificial intelligence (AI) capabilities, which could otherwise enhance their business efficiency and predictability. This paper introduces a decentralized AI orchestration framework that prioritizes transparency and explainability, offering valuable insights to funders, such as banks, and aiding them in overcoming the challenges associated with assessing SMEs’ financial credibility. By utilizing an orchestration technique involving symbolic reasoners, language models, and data-driven predictive tools, the framework empowers funders to make more informed decisions regarding cash flow prediction, finance rate optimization, and ecosystem risk assessment, ultimately facilitating improved access to pre-shipment trade finance for SMEs and enhancing overall supply chain operations.

show abstract

Section: Cash Flow Model Trainingmentioning

confidence: 99%

Decentralized Data and Artificial Intelligence Orchestration for Transparent and Efficient Small and Medium-Sized Enterprises Trade Financing

Alirezaie,

Hoffman,

Zabihi

et al. 2024

JRFM

View full text Add to dashboard Cite

show abstract

“…Neural networks aided by AI help firms learn from incoming data and adjust their forecasts based on ongoing understanding, resulting in enhanced accuracy of earnings predictions and observed changes in earnings (Fiserv, 2017;Xinyue et al, 2020). These strategies aim to maximise cash flow by making advance fund predictions, preventing liquidity risks, minimising insurance risk, detecting anomalies in financial data, and adjusting investment strategies (Dadteev et al, 2020;Yang et al, 2019). AI has enabled firms to adopt risk control applications regarding cash flow (Yan & Ouyang, 2018;Yang et al, 2018), helping SMEs in data analytics to recognise and analyse risks controls, offer credit evaluations, and risk strategies (Sood, 2020).…”

Section: Predictions Pricing and Cash Flowmentioning

confidence: 99%

Artificial Intelligence and Reduced SMEs’ Business Risks. A Dynamic Capabilities Analysis During the COVID-19 Pandemic

Drydakis

2022

Inf Syst Front

View full text Add to dashboard Cite

The study utilises the International Labor Organization's SMEs COVID-19 pandemic business risks scale to determine whether Artificial Intelligence (AI) applications are associated with reduced business risks for SMEs. A new 10-item scale was developed to capture the use of AI applications in core services such as marketing and sales, pricing and cash flow. Data were collected from 317 SMEs between April and June 2020, with follow-up data gathered between October and December 2020 in London, England. AI applications to target consumers online, offer cash flow forecasting and facilitate HR activities are associated with reduced business risks caused by the COVID-19 pandemic for both small and medium enterprises. The study indicates that AI enables SMEs to boost their dynamic capabilities by leveraging technology to meet new types of demand, move at speed to pivot business operations, boost efficiency and thus, reduce their business risks.

show abstract

“…In the event of a forecasting error, there may be a cash shortage in one of the currencies or an overflow of bank branch vaults, necessitating additional charges for strengthening or exporting money. Many variables impact money movement, including political, economic, and geographical considerations [102] 32.…”

Section: Cash Flowmentioning

confidence: 99%

Transforming the Capabilities of Artificial Intelligence in GCC Financial Sector: A Systematic Literature Review

Khan

Malik

Alomari

et al. 2022

Wireless Communications and Mobile Computing

View full text Add to dashboard Cite

Identity and access management is a business process framework that makes it easier to maintain genuine user identities and regulate access to sensitive assets. The word “access control” refers to an organization’s policy for authorizing access procedures, the mechanisms that implement and enforce the policy, and the model that the policy and procedures are built on. Adopting new technology may give rise to specific cyber threats that decrease or degrade business operations. The paper has designed to discuss the artificial intelligence-based access control system as a necessary component of governing and safeguarding the financial sector’s information assets in the Gulf Cooperation Council (GCC) region. Due to the dynamic and complicated nature of security rules for access control, organizations that employ web-enabled remote access in conjunction with applications access deployed over several networks face various obstacles, including increased operational complexity and monitoring concerns. Organizations spend a vast budget on securing their business. As the industry trend has shifted to intelligent internet-based companies on the same side, the cyber threat has become a challenge for the researcher to find the solution. A systematic research is conducted to fill the gaps in the existing literature by picking the most relevant research papers (126) from the four most reputable online repositories based on the four research questions specified. These research topics aim to evaluate the current situation from many perspectives and provide new avenues for future study to be studied soon to maintain high security and authenticity inside financial sectors of the GCC’s countries.

show abstract

Using artificial intelligence technologies to predict cash flow

Cited by 7 publications

References 3 publications

Decentralized Data and Artificial Intelligence Orchestration for Transparent and Efficient Small and Medium-Sized Enterprises Trade Financing

Decentralized Data and Artificial Intelligence Orchestration for Transparent and Efficient Small and Medium-Sized Enterprises Trade Financing

Artificial Intelligence and Reduced SMEs’ Business Risks. A Dynamic Capabilities Analysis During the COVID-19 Pandemic

Transforming the Capabilities of Artificial Intelligence in GCC Financial Sector: A Systematic Literature Review

Contact Info

Product

Resources

About