Automated explanation of financial data

Research output: Contribution to journalArticleScientificpeer-review

Abstract

We describe a methodology for explanation generation in financial knowledge-based systems. This offers the possibility to generate explanations and diagnostics automatically to support business decision tasks. The central goal is the identification of specific knowledge structures and reasoning methods required to construct computerized explanations from financial data and models. A multistep look-ahead algorithm is proposed that deals with so-called cancelling-out effects, which are a common phenomenon in financial data sets. Our method is an extension of the traditional variance decomposition in accounting. The method was tested on a case-study conducted for Statistics Netherlands involving the comparison of financial figures of firms in the Dutch retail branch.
Original languageEnglish
Pages (from-to)5-19
JournalInternational Journal of Intelligent Systems in Accounting Finance & Management
Volume16
Publication statusPublished - 2009

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Financial data
Retail
Diagnostics
Statistics
Methodology
Knowledge structure
Business support
Financial knowledge
Variance decomposition
Knowledge-based systems
The Netherlands
Financial models

Cite this

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title = "Automated explanation of financial data",
abstract = "We describe a methodology for explanation generation in financial knowledge-based systems. This offers the possibility to generate explanations and diagnostics automatically to support business decision tasks. The central goal is the identification of specific knowledge structures and reasoning methods required to construct computerized explanations from financial data and models. A multistep look-ahead algorithm is proposed that deals with so-called cancelling-out effects, which are a common phenomenon in financial data sets. Our method is an extension of the traditional variance decomposition in accounting. The method was tested on a case-study conducted for Statistics Netherlands involving the comparison of financial figures of firms in the Dutch retail branch.",
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Automated explanation of financial data. / Daniëls, H.A.M.; Caron, E.A.M.

In: International Journal of Intelligent Systems in Accounting Finance & Management, Vol. 16, 2009, p. 5-19.

Research output: Contribution to journalArticleScientificpeer-review

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AB - We describe a methodology for explanation generation in financial knowledge-based systems. This offers the possibility to generate explanations and diagnostics automatically to support business decision tasks. The central goal is the identification of specific knowledge structures and reasoning methods required to construct computerized explanations from financial data and models. A multistep look-ahead algorithm is proposed that deals with so-called cancelling-out effects, which are a common phenomenon in financial data sets. Our method is an extension of the traditional variance decomposition in accounting. The method was tested on a case-study conducted for Statistics Netherlands involving the comparison of financial figures of firms in the Dutch retail branch.

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JO - International Journal of Intelligent Systems in Accounting Finance & Management

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