Abstract
This paper addresses the problem of designing an “intelligent” decision support methodology tool to act as a back end to financial planning. The methodology tool proposes a novel approach to supplementing typical financial strategy formulation projects by utilizing the fuzzy causal characteristics of Fuzzy Cognitive Maps (FCMs) to generate a hierarchical and dynamic network of interconnected profit and loss (P&L) concepts. By using FCMs, the mechanism simulates the efficiency of complex hierarchical financial models with imprecise relationships and external stimuli while quantifying the impact of strategic changes to the overall P&L status. Generic maps that supplement the decision making process demonstrate a roadmap for integrating hierarchical FCMs into the P&L model of typical financial sector enterprises. Preliminary experiments indicate that ex ante reasoning of the impact of strategic changes (actual or hypothetical) to the status of financial performance can be effective and realistic, without employing detailed P&L numerical calculations.
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Xirogiannis, G., Glykas, M., Staikouras, C. (2010). Fuzzy Cognitive Maps in Banking Business Process Performance Measurement. In: Glykas, M. (eds) Fuzzy Cognitive Maps. Studies in Fuzziness and Soft Computing, vol 247. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-03220-2_7
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DOI: https://doi.org/10.1007/978-3-642-03220-2_7
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