Changing the World of Financial Analysis

1. Changing the World of Financial Analysis Mark Schnitzer XBRL Analyst Supply Chain Chair

2. XBRL will Benefit Companies, Analysts and Investors • Timely • Reliable: accurate and well-defined • Direct from the company • Machine readable • Future applications will allow deeper automatic analysis

3. Why are Investors Interested in XBRL? • XBRL is useful to us in two ways • We can integrate the data that we bring in directly into our models • If the data we send out is in XBRL inside a RIXML document then it will be easier for our clients to integrate it with published company data • If companies provide financial information in XBRL, we will use it

4. How an Analyst Will Use XBRL • Analysts integrate the data from companies with information from financial intermediaries directly into their Excel spreadsheets • Data can be collated and aggregated easily • Broad surveys can be automated, e.g. pension analysis • Strategists can aggregate reliable sector and market data • Sell side analysts can publish to buy side portfolio managers and analysts in a standard format using XBRL and RIXML

5. XBRL Will Enable Better Financial Analysis • Improve data quality • Direct access to as reported data • Data validation on entry • Global access to timely data • Reduce re-keying of data • Reduce cost of information • Enable a new paradigm of financial applications • Sophisticated analysis • Should not be apparent to the investor that they are even working with XBRL

6. Analysts Live in Spreadsheets • Build a spreadsheet model with historical and forecasted income statement, balance sheet and cash flow statement for every company under coverage. • Model is the basis for valuation and investment decisions. • Model is used to build investment thesis or corporate finance decision. • Data from companies is keyed in. • Analysts incorporate data from multiple data sources into their models. • Integration of data sources occurs on the desktop. • Critical data in the model typically comes from the company.

7. Data Sources • Financial information providers • Lack of transparency into as reported data • Time lag between creation and delivery to market • Direct from the company • Discovery of data can be time consuming and difficult • Inconsistent locations and methodologies • No guarantee of permanency • Stock Exchanges • Tightly coupled with capital markets • Regulatory repositories • Authoritative and permanent

8. XBRL Will Improve Models • Analysts typically type earnings data into spreadsheet models. • Can take hours to enter data. • Analysts need to compare analyst forecast, company earnings release, consensus earnings and final published earnings. • Time is important. • Cannot wait for information providers to distribute data. • Need in time for conference call. • Error-free data • Mistakes cost money. • Analysts do not need to spend time checking the keyed-in data.

9. Web Services Are Critical • Moving from document centric electronic paper world (forms) to virtual documents based on evolving taxonomies • Mapping of spreadsheets to data sources provides: • Transparency • Ability to audit • Ease of discovery • Alternatives, such as web pages and downloadable spreadsheets, diminish the value of the data to the investment community

10. Typical Pensions Project • Surveyed pension exposure of 250 companies • 5 companies per day meant 10 weeks initial data collection • Time from idea to report was too long • XBRL will shorten time to market • Near-instant data collection • Less need to update out-of-date information • Less intensive data collection means • More ideas make it into reports • Shorter turnaround • More time can be spent on in-depth analysis

11. Finding Pension Information in a Regulatory Filing

12. Advantages for the Analysts • Faster integration of data into models • Clearer linkage to source documents • Fewer data entry and transposition errors • Greater reliance on the reported data

13. Portfolio Manager/Analyst • Background • Deals with vendor-packaged information in proprietary formats • Still re-keying information into spreadsheets and databases • Expensive to maintain financial models • Opportunity for XBRL • Vendor feeds will be uniform and consistent with company-provided information • Re-keying will be reduced by reliance on company tagged information • Integrate analyst forecasts with data from companies and information providers using web services

14. Retail Investor • Background • Uses popular financial information sites, e.g. Yahoo • May lack the expertise to process content in regulatory filings • Need assistance to find critical hints in reported details and financial footnotes • Opportunity for XBRL • Provide expert systems to take investor through key ratios and valuation techniques • “Red flag” some potential issues

15. Next Generations of Investor Applications • Will be unlike anything we see today • Investors today have access to financial statements but not understanding • Where does an investor find revenue? SPEs? • What is the difference between revenue and income? • Investor tools will be more powerful than even the in-depth analyst models that currently exist • Functionality will be available to all investors • Insight will become more important than spreadsheet skills

16. Conclusion: XBRL makes markets more efficient • Better informed investors • More accessible information for regulators • Greater access to global markets • Lower cost of information • Higher valued added analytics • More informed investment decisions • Lower cost of capital

17. Contact Information • Mark Schnitzer • mark.schnitzer@morganstanley.com