1 / 34

The Use of Interactive Data Views in Corporate Financial Reporting

The Use of Interactive Data Views in Corporate Financial Reporting. Diane J. Janvrin ISU Accounting Finance Research Workshop May 4, 2009

shubha
Download Presentation

The Use of Interactive Data Views in Corporate Financial Reporting

An Image/Link below is provided (as is) to download presentation Download Policy: Content on the Website is provided to you AS IS for your information and personal use and may not be sold / licensed / shared on other websites without getting consent from its author. Content is provided to you AS IS for your information and personal use only. Download presentation by click this link. While downloading, if for some reason you are not able to download a presentation, the publisher may have deleted the file from their server. During download, if you can't get a presentation, the file might be deleted by the publisher.

E N D

Presentation Transcript


  1. The Use of Interactive Data Views in Corporate Financial Reporting Diane J. Janvrin ISU Accounting Finance Research Workshop May 4, 2009 Thanks to Bill Dilla and Robyn Rasche (UNLV) for helpful discussions, Mike Doran for assistance in data collection, Andrea Biagolni, Courtney Ekeler, Leslie Pease, and Pat Wagaman for material preparation assistance.

  2. Overview Motivation Research Questions Methodology Preliminary Results Discussion/Conclusion

  3. Interactive Data Views Process of allowing users to select presentation format and type of information they find as most relevant Allows users to disaggregate financial statement information and select only the information they view as most relevant. Some allow users to perform selected calculations

  4. Interactive Data Views May help decision makers overcome information overload by reducing large data sets into simple visuals Shifts cognitive load to the human perceptual system through graphics

  5. Key Terms Visual representation Selection, transformation, and presentation of data (including spatial, abstract, physical, or textual) in a visual format that facilitates exploration and understanding (Lurie and Mason 2007) Visualization tools Intermediate step in converting data into insight Data characteristics such as dimensionality, scale (categorical, ordinal, and metric) and cardinality (binary vs massively categorical variables) affect which tools are appropriate.

  6. Categories of Information Visualization (Yi et al. 2007) • Select • Mark data item as interesting • Explore • View other data items • Reconfigure • View different arrangement of data • Encode • View different representation of data • Abstract/Elaborate • View data in more or less detail • Filter • View data conditionally • Connect • View related items of data

  7. Visualization Tools Early use in genetics and biology Business applications lag the sciences by as much as 10 years (West 1995) Today, used in marketing efforts (Lurie and Mason 2007) Beginning to see usage in external financial reporting – maybe internal reporting

  8. IDV Examples • SEC web site • Executive Compensation • Interactive Financial Reports • http://viewerprototype1.com/viewer • Financial Explorer • http://209.234.225.154/viewer/home/ • Corporate web sites • Stock price information • http://www.ford.com/about-ford/investor-relations/investment-information/stock-chart • Enumerate - financial and non-financial information • http:///www.enumerate.com • http://production.investis.com/bp2/ia/annualdata2007/

  9. SEC Executive Compensation Viewer

  10. SEC Interactive Financial Reports

  11. SEC Interactive Financial Reports

  12. SEC Financial Explorer IBM

  13. SEC Financial Explorer Pfizer

  14. Corporate Website – Stock information Ford

  15. Corporate Web site – Financial and non-financial information

  16. Corporate Web site – Financial and non-financial information

  17. Data transformations Potentially affect the ultimate insights derived from the data The problem visual representations may allow users to see patterns and outliers easier, make certain information more salient and other information less salient, and show detailed information on specific alternatives (i.e. improve decision quality) however, visual representation may accentuate biases in decision making and lower performance by increasing attention to particular attributes or less diagnostic information

  18. Current Research Exploratory study examining whether nonprofessional investors perceive that IDVs present unaudited information distorted information Second study examining whether viewing distorted changes in financial information in IDV format impacts nonprofessional investor judgment

  19. Exploratory Study • Examines issues (i.e. unaudited information / distorted information ) raised by the Pozen Committee (SEC 2008) • Examines perceived system quality (Ahn et al. 2007)

  20. Presentation of Unaudited Information • Important issues related to presentation of financial information using IDVs • Should assurance be provided by a third party? • If not, should financial statement preparers indicated information is unaudited? • Do users realize presented information is unaudited? • Hodge 2001 found answer is no

  21. Research Questions – Presentation of Unaudited Information • RQ: Do investors perceive that IDVs present unaudited financial information?

  22. Presentation of Distorted Information • Some IDVs may distort the underlying financial information • SEC Financial Explorer atomic models • Will user decisions be impacted by distorted financial information? • Arunachalam et al. 2002 found yes

  23. Research Questions – Presentation of Distorted Information • RQ: Do investors perceive that IDVs present distorted financial information?

  24. First Study • 154 students enrolled in intermediate accounting or accounting information systems at large public university • Examined four IDVs • Provided responses to general statements based on issues raised by the Pozen Committee (SEC 2008) and technology acceptance statements regarding perceived system quality (Ahn et al. 2007)

  25. Results • Unaudited / distortion • System Quality

  26. Second Study • Examines whether viewing distorted changes in financial information in IDV format impacts nonprofessional investor judgment

  27. Second Study • 154 students enrolled in accounting information systems at large public university • 20 CPAs attending continuing education session • Trained to use SEC Interactive Financial Explorer IDV • Examined nine scenarios involving IDVs • Financial information displayed: revenue, expenses, and income • All components increased, decreased, varied • In each scenario, one IDV displayed the change in financial information appropriately and one IDV distorted the change in financial information • Based on this limited information, participants were asked to make an investment decision

  28. Sample Scenario • Income greater • https://www.bus.iastate.edu/djanvrin/IDV/part2incomegreater.asp • Income smaller • https://www.bus.iastate.edu/djanvrin/IDV/part2incomesmaller.asp • Income varied • https://www.bus.iastate.edu/djanvrin/IDV/part2incomevaried.asp

  29. Results • Investment choice • Post project data

  30. Summary Implications for General Decision Making Visualization has potential to offer decision makers ways to improve efficiencies reduce costs gain new insights make data more accessible increase satisfaction At same time, visualization may accentuate biases in decision making

  31. Implications for Financial Statement Preparers Rendering issues Do you present audited or unaudited information? Materiality at data level

  32. Implications for Financial Statement Auditors Is audited information presented? How do users determine if information is audited? i.e., disclaimer or presence of audit report? Materiality at data level

  33. Implications for Financial Statement Users Provides data in preferred format (i.e., table, graph, or both) Allows user to view only the data user determine is relevant Facilitates comparison between companies between periods between divisions / products May accentuate biases; highlight less relevant information

  34. Conclusions Interactive data views –tool preparers to communicate financial information and for users to acquire and evaluate financial information May have both positive and negative consequences to decision making Any questions?

More Related