Flexible categorization for auditing using formal concept analysis and
Dempster-Shafer theory
- URL: http://arxiv.org/abs/2210.17330v1
- Date: Mon, 31 Oct 2022 13:49:16 GMT
- Title: Flexible categorization for auditing using formal concept analysis and
Dempster-Shafer theory
- Authors: Marcel Boersma, Krishna Manoorkar, Alessandra Palmigiano, Mattia
Panettiere, Apostolos Tzimoulis, Nachoem Wijnberg
- Abstract summary: We study different ways to categorize according to different extents of interest in different financial accounts.
The framework developed in this paper provides a formal ground to obtain and study explainable categorizations.
- Score: 55.878249096379804
- License: http://creativecommons.org/licenses/by/4.0/
- Abstract: Categorization of business processes is an important part of auditing. Large
amounts of transnational data in auditing can be represented as transactions
between financial accounts using weighted bipartite graphs. We view such
bipartite graphs as many-valued formal contexts, which we use to obtain
explainable categorization of these business processes in terms of financial
accounts involved in a business process by using methods in formal concept
analysis. The specific explainability feature of the methodology introduced in
the present paper provides several advantages over e.g.~non-explainable machine
learning techniques, and in fact, it can be taken as a basis for the
development of algorithms which perform the task of clustering on transparent
and accountable principles. Here, we focus on obtaining and studying different
ways to categorize according to different extents of interest in different
financial accounts, or interrogative agendas, of various agents or sub-tasks in
audit. We use Dempster-Shafer mass functions to represent agendas showing
different interest in different set of financial accounts. We propose two new
methods to obtain categorizations from these agendas. We also model some
possible deliberation scenarios between agents with different interrogative
agendas to reach an aggregated agenda and categorization. The framework
developed in this paper provides a formal ground to obtain and study
explainable categorizations from the data represented as bipartite graphs
according to the agendas of different agents in an organization (e.g.~an audit
firm), and interaction between these through deliberation.
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