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Leveraging XBRL Technology to Improve the Transparency of Financial Information Don Inscoe Associate Director FDIC Statistics Branch May 12, 2004 Auckland,

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Presentation on theme: "Leveraging XBRL Technology to Improve the Transparency of Financial Information Don Inscoe Associate Director FDIC Statistics Branch May 12, 2004 Auckland,"— Presentation transcript:

1 Leveraging XBRL Technology to Improve the Transparency of Financial Information Don Inscoe Associate Director FDIC Statistics Branch May 12, 2004 Auckland, New Zealand XBRL: "Exchanging Business Information" 9 th XBRL International Conference

2 # 2 Topics  Background for XBRL-enabled change  Evidence that demand for information increases as it becomes more timely  Measuring the time value of information  Easier access to information boosts demand

3 # 3 Background  U.S. bank regulators have collected financial information from banks for 70 + years, please see for information on how information collections have evolved  Banks are “called upon” each quarter to submit financial reports to regulators  Bank financial statements “Call Reports” have been published on since 1998  Data is available in interactive analytical format back to 1992,  Agencies have electronic databases back to 1972

4 # 4 Call Report History

5 # 5 Today’s Call Report  Nearly 8,400 banks file each quarter  Most banks are required to file reports within 30 days  Each report contains approximately 1,200 variables  The agencies apply about 1,100 tests “edits” to each report to correct errors before publication  More detailed information filed by large and complex banks

6 # 6 Call Report modernization  FFIEC (Federal Financial Institutions Examination Council) Call Report agencies: FDIC (Federal Deposit Insurance Corporation) FRB (Federal Reserve Board) OCC (Office of the Comptroller of the Currency)  What is being created? CDR (Central Data Repository) Collection, validation and distribution of Call Report data submitted by banks

7 # 7 Call Report modernization (con’t)  When will it go into effect? Implementation is planned for the Submission of Call Report data for September 30, 2004  How will it work? Call vendors receive XBRL taxonomies from FFIEC Vendors write collection software Banks complete Call Reports and file data to FFIEC via Internet

8 # 8 Call Report modernization (con’t)  What benefits are expected from the XBRL-enabled system? Banks will submit more accurate Call Reports Agency's mechanical review replaced by more strategic process to identify and improve reporting Information released sooner and in more useful formats Easier to make changes, add new data series Development of new products enabled by more timely data disclosed in open extensible standard

9 # 9 Data users  Public access of Call Report data serves wide spectrum of interests  Users include: banking personnel, investors, corporate treasury managers, news organizations, public policy leaders, academic researchers...  Common thread among all is interest in most current possible insight into the financial state of banks and thrifts

10 # 10 Banks’ financial data  Bank Call Report data typifies many classes of information where “fresher” is more useful  The data in these reports is then released to the public  Nearly 8,400 FDIC-insured banks reported at the end of 2003

11 # 11 The demand for information increases as it becomes more timely  Before 2003, Call Reports were not released until all reports had been submitted and edited by regulators  Reports were held until agencies analyzed data and issued press releases  Reports were not released until about 65 days after the quarter ending date  Last year, the process was changed so that reports are released in weekly batches, so almost all reports are now published within 50 days after the quarter ends

12 # 12 Agencies receive most Call Reports within 30 Days … This graph shows the cumulative number of Call Reports received each day after the report date – most are received within 30 days.

13 # 13 … then it takes 30 more days to edit and publish all reports Agencies must resolve edit exceptions before Call Reports are published.

14 # 14 WebTrends shows more users obtaining more data… Three month moving average number of hits to data pages and number of users

15 # 15 … and use increases when new data is posted to website  Interest peaks just before and just after initial release  Bulk Call Report release (3Q02) typified by increased access activity over moderate time span  Staggered Call Report release (3Q03) shows higher, but more irregular use

16 # 16 Demand for Call Reports declines as they become older “Hits” reflect use of most- recent and prior quarter reports, note that hits diminish sharply as data ages, but year- end data always has higher use Unique 0 2,000 4,000 6,000 8,000 10,000 30,000 90,000 180,000 Number of Hits Mar.Jun. Sep. Dec.Mar.Jun. Sep. Dec.Mar.Jun. Sep. Dec.Mar.Jun. Sep. Dec.Mar.Jun. Sep. Dec.Mar.Jun.Sep. 200120001999199820032002 ~ ~ ~ ~ Hits 160,322 51,269 ~ ~ “Unique” = IP Addresses Both lines indicate use of most- recent and prior quarter Call Reports; note that hits diminished from 160,000 (September 2003 Call) to fewer than fewer than 2,000 (1998)

17 # 17 Measuring the time value of information  The new XBRL-enabled process will allow banks to fix data problems before they submit their report  This enhanced business process will enable regulators to release data just after it is received  Reports can be published “straight through processing” sooner after receipt, thereby improving timeliness  Analytical model uses WebTrends statistics to provide a relative measure of how the value of information diminishes as information becomes dated (or “stale”)

18 # 18 blue line green line When CDR is implemented, all Call Reports will be released within 30+ days (blue line) in contrast to 50+ days in current system (green line)

19 # 19 Time value of the data  Given users’ interest in timely data, its value to them declines as time passes  This value reaches a minimum immediately prior to the next quarterly release  User’s interest over the course of a typical quarter is illustrated in the following

20 # 20 Use of FDIC’s Call Report website Data page hits usually drop sharply within 3 – 4 weeks after new Call Report data is published

21 # 21 Rationales for modeling time value  Provides generalized basis for evaluating website use data  Smoothes out variations and artifact observed in website access  Can be independent of particular metric used to measure website use (hits, visits, unique IP addresses, etc.)  Can quantify benefits vs. costs of changes

22 # 22 Modeling assumptions  Value of multi-quarter repository peaks immediately after new quarter of data is added  This value declines continuously, reaching a minimum immediately before the next quarter’s update  Residual value of historical data is small compared to that of current quarter

23 # 23 Other modeling and fitting assumptions  Between updates, value is lost continuously as time passes  Rate of value loss is proportional to current value (fresh data loses value more quickly than stale data)  User interest in accessing website provides appropriate empirical observations of data’s inherent value

24 # 24 Model form  Assumptions described previously lead to exponential model to measure the change in data’s value over the quarter V(t) = V 0 e -Kt + V res  Model is : V(t) = V 0 e -Kt + V res where V(t) V(t) is the value of the repository at time, t V 0 V 0 is the change in value between updates V res V res is the residual value of the repository just before an update “e” “e” is the exponential function (2.731…) K K is the decay rate (“reciprocal lifetime”)

25 # 25 Example of analytical model using data shown previously

26 # 26  will measure improvement when data is published sooner (“straight- through processing”)  details to be provided at XBRL International presentation Model will estimate value gained by efforts to make data more timely

27 # 27 Future strategies  CDR replaces current Call Report collection process CDR implementation targeted for September 2004 Call Report Data to be published immediately after receipt (once we are comfortable with the new CDR)  Call Report taxonomy to published using open BASI (Bank and Savings Institutions) standard Open standard mapped to legacy taxonomy (facilitates data sharing among different users and data sources)

28 # 28 FDIC Call Report concepts for “Cash and Balances Due” vary by form FFIEC Call Report data has been published using Federal Reserve “MDRM” data element names since the early 1980’s Equivalent items can have different prefixes RCFD RCON Prefix:

29 # 29 Equivalent BASI Concepts for “Cash and Balances Due” do not vary Call Reports and BASI have a number of common concepts

30 # 30 FFIEC 031 Call Report Cash and Balances Due FFIEC 041 Call Report Cash and Balances Due XBRL Banking and Savings Institutions Taxonomy Cash and Balances Due Taxonomy tagging: map common concepts to enable comparisons of Call Reports with other GAAP sources

31 # 31 Common concepts can be mapped using FDIC and BASI labels to support legacy systems and enable comparison with other GAAP supply sources Consolidated Report of Condition Schedule RC – Balance Sheet Form 31Form 41 Noninterest-bearing balances and currency and coinRCFD0081RCON0081 Interest-bearing balancesRCON0071RCFD0071 Example shows how “Cash and Balances due” taxonomy provides link between different standards Form 31Form 41BASI Bank and Savings InstitutionsRCFD0081RCON0081CashCashEquivalentsAssets RCON0071RCFD0071InterestBearingDepositsBanks

32 # 32 Taxonomy tagging FFIEC 031 Call Report Cash and Balances Due FFIEC 041 Call Report Cash and Balances Due XBRL Banking and Savings Institutions Taxonomy Cash and Balances Due

33 # 33 Finis

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