Changing the World of Financial Analysis

Mark Schnitzer

XBRL Analyst Supply Chain Chair

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

Why are Investors Interested in XBRL? XBRL is useful to us in two ways

1. We can integrate the data that we bring in directly into our models

2. 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

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

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

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.

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

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.

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

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

Finding Pension Information in a Regulatory Filing

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

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

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

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

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

Contact Information Mark Schnitzer mark.schnitzer@morganstanley.com