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.

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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

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Finding Pension Information in a Regulatory Filing
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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

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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

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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

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Contact Information

• Mark Schnitzer
• mark.schnitzer_at_morganstanley.com