Evolutionary Computing Applied to Solve Some Operational Issues in Banks

Krishna, Gutha Jaya; Ravi, Vadlamani

doi:10.1007/978-3-030-01641-8_3

Cited by 4 publications

(1 citation statement)

References 30 publications

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“…In [11] a survey is given on solving some other banking related issues (such as portfolio optimization, bankruptcy prediction and FOREX rate prediction) using evolutionary computing. A stochastic model for a payment and settlement system capable of processing payments in real time is presented in [1] by the example of the Clearinghouse of the Bank of Lithuania.…”

Section: Introductionmentioning

confidence: 99%

Evolutionary solving of the debts’ clearing problem

Păatcaş

Bartha

2019

Acta Universitatis Sapientiae, Informatica

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The debts' clearing problem is about clearing all the debts in a group of n entities (persons, companies etc.) using a minimal number of money transaction operations. The problem is known to be NP-hard in the strong sense. As for many intractable problems, techniques from the field of artificial intelligence are useful in finding solutions close to optimum for large inputs. An evolutionary algorithm for solving the debts' clearing problem is proposed.

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Section: Introductionmentioning

confidence: 99%

Evolutionary solving of the debts’ clearing problem

Păatcaş

Bartha

2019

Acta Universitatis Sapientiae, Informatica

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High Utility Itemset Mining and Inventory Management: Theory and Use Cases

Krishna

2023

Smart Innovation, Systems and Technologies

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AI in Finance: Challenges, Techniques, and Opportunities

Cao

2022

ACM Comput. Surv.

114

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AI in finance refers to the applications of AI techniques in financial businesses. This area has attracted attention for decades, with both classic and modern AI techniques applied to increasingly broader areas of finance, economy, and society. In contrast to reviews on discussing the problems, aspects, and opportunities of finance benefited from specific or some new-generation AI and data science (AIDS) techniques or the progress of applying specific techniques to resolving certain financial problems, this review offers a comprehensive and dense landscape of the overwhelming challenges, techniques, and opportunities of AIDS research in finance over the past decades. The challenges of financial businesses and data are first outlined, followed by a comprehensive categorization and a dense overview of the decades of AIDS research in finance. We then structure and illustrate the data-driven analytics and learning of financial businesses and data. A comparison, criticism, and discussion of classic versus modern AIDS techniques for finance follows. Finally, the open issues and opportunities to address future AIDS-empowered finance and finance-motivated AIDS research are discussed.

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Evolutionary Computing Applied to Solve Some Operational Issues in Banks

Cited by 4 publications

References 30 publications

Evolutionary solving of the debts’ clearing problem

Evolutionary solving of the debts’ clearing problem

High Utility Itemset Mining and Inventory Management: Theory and Use Cases

AI in Finance: Challenges, Techniques, and Opportunities

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