The visual analysis of financial data

doi:10.1017/CBO9780511997730.012

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22 - The visual analysis of financial data

from PART V - DATA MANAGEMENT TECHNOLOGIES

Victoria L. Lemieux ,

Brian Fisher and

Edited by

Dilip Krishna and

Victoria L. Lemieux: Affiliation:
University of British Columbia’s iSchoo
Brian Fisher: Affiliation:
Simon Fraser University
Thomas Dang: Affiliation:
University of British Columbia
Dilip Krishna: Affiliation:
Deloitte & Touche, LLP

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Summary

Introduction

Financial risk analysis is cognitively complex and demands analysis and interpretation of diverse and often sizeable data sources. Whether the goal is to analyze systemic, market, liquidity, credit or operational types of risk, it is often the case that financial risk analysis and decision-making require rivers of data to be contextualized and analyzed across multiple dimensions on an almost real-time basis. The methods and technologies used to synthesize and analyze this flood of data, and to turn the resulting information into useful insights, are still few and far between. Traditional analytic methods and tools often force people to formalize their thoughts early in the process, and to adapt their way of working to the rigidity of mathematical formulas or computational methods. In contrast, risk analysis frequently requires open-ended exploration of large volumes of complex data, detection of previously unknown patterns, changes or anomalies, and seeking solutions to open-ended and even ill-defined questions. It is these challenges that visual analysis of financial data is designed to meet. Visual analysis technologies have the potential to reduce the time it takes to analyze complex financial data, to bring financial risk managers and decision makers to new understanding of their financial risks and to aid them in communicating about such risks. The goal of this chapter is to introduce the visual analytics approach, and to explore how it might support financial risk analysis and decision making.

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Type: Chapter
Information: Handbook of Financial Data and Risk Information II
Software and Data
, pp. 279 - 326

DOI: https://doi.org/10.1017/CBO9780511997730.012 [Opens in a new window]

Publisher: Cambridge University Press

Print publication year: 2014

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