"Intelligent" finance and treasury management: what we can expect
The result's identifiers
Result code in IS VaVaI
<a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F62156489%3A43110%2F20%3A43916628" target="_blank" >RIV/62156489:43110/20:43916628 - isvavai.cz</a>
Alternative codes found
RIV/61989100:27510/19:10243528
Result on the web
<a href="https://doi.org/10.1007/s00146-019-00919-6" target="_blank" >https://doi.org/10.1007/s00146-019-00919-6</a>
DOI - Digital Object Identifier
<a href="http://dx.doi.org/10.1007/s00146-019-00919-6" target="_blank" >10.1007/s00146-019-00919-6</a>
Alternative languages
Result language
angličtina
Original language name
"Intelligent" finance and treasury management: what we can expect
Original language description
Artificial intelligence poses a particular challenge in its application to finance/treasury management because most treasury functions are no longer physical processes, but rather virtual processes that are increasingly highly automated. Most finance/treasury teams are knowledge workers who make decisions and conduct analytics within often dynamic frameworks that must incorporate environmental considerations (foreign exchange rates, GDP forecasts), internal considerations (growth needs, business trends), as well as the impact of any actions on related corporate decisions which are also highly complex (e.g., hedging, investing, capital structure, liquidity levels). Artificial intelligence in finance and treasury is thus most analogous to the complexity of a human nervous system as it encompasses far more than the automation of tasks. Similar to the human nervous system, AI systems in finance/treasury must manage data quickly and accurately, including the capture and classification of data and its integration into larger datasets. At present, the AI network neural system has been gradually improved and is widely used in many fields of treasury management, such as early warning of potential financial crisis, diagnosis of financial risk, control of financial information data quality and mining of hidden financial data, information, etc.
Czech name
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Czech description
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Classification
Type
J<sub>SC</sub> - Article in a specialist periodical, which is included in the SCOPUS database
CEP classification
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OECD FORD branch
50206 - Finance
Result continuities
Project
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Continuities
I - Institucionalni podpora na dlouhodoby koncepcni rozvoj vyzkumne organizace
Others
Publication year
2020
Confidentiality
S - Úplné a pravdivé údaje o projektu nepodléhají ochraně podle zvláštních právních předpisů
Data specific for result type
Name of the periodical
AI & Society
ISSN
0951-5666
e-ISSN
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Volume of the periodical
35
Issue of the periodical within the volume
3
Country of publishing house
GB - UNITED KINGDOM
Number of pages
12
Pages from-to
715-726
UT code for WoS article
000490035700001
EID of the result in the Scopus database
2-s2.0-85074460377