Transcript Leveraging Technology to Improve the Transparency of

XBRL: "Exchanging Business Information"
9th XBRL International Conference
Leveraging XBRL
Technology to Improve
the Transparency of
Financial Information
Don Inscoe
Associate Director
FDIC Statistics Branch
May 12, 2004
Auckland, New Zealand
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
#2
Background
 U.S. bank regulators have collected financial information from banks
for 70+ years, please see
http://www2.fdic.gov/hsob/Milestone.asp?EntryTyp=40
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
www.fdic.gov since 1998
 Data is available in interactive analytical format back to 1992,
www2.fdic.gov/sdi
 Agencies have electronic databases back to 1972
#3
Call Report History
Call Reports are
provided to the
public on magnetic
tape
Computerization
begins
Reporting requirements
become more consistent
with public reporting
FFIEC established - requirements
Coordinate Call Reporting
Data made available
via the Internet
FDIC publishes
annual statistics
FDIC Established
and empowered to
collect information
Public demand
increase
Banks are provided
with comparative
reports
Computerized
surveillance systems
are implemented
UBPR developed
...
1933
1934
1954
1960
Agencies adopted
GAAP
...
1967
1971
1977 1979
1982 1986
1996 1997
#4
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
#5
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
#6
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
#7
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
#8
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
#9
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
# 10
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
# 11
Agencies receive most Call
Reports within 30 Days …
9,000
# of Call Reports
8,000
7,000
This graph shows the
cumulative number of Call
Reports received each day
after the report date – most
are received within 30 days.
6,000
5,000
4,000
3,000
2,000
1,000
1
3
5
7
9
11
13
15
17
19
21
23
25
27
29
# of days after quarter end
# 12
… then it takes 30 more days to
edit and publish all reports
# of CALL Reports
9,000
8,000
7,000
Agencies must
resolve edit
exceptions before
Call Reports are
published.
7963
8392
7035
6,000
5,000
5921
4,000
3,000
3715
2,000
1,000
1448
24
31
37
45
52
55
# of days afte r quarte r e nd
# 13
WebTrends shows more users
obtaining more data…
25,000
45,000
Average Numberof Hits to Data
Pages Each Week
Hits
40,000
20,000
Visits
35,000
30,000
15,000
25,000
20,000
10,000
Three month moving
average number of hits to
data pages and number
of users
15,000
10,000
5,000
5,000
0
2/11/2001
Average Number of Visits from
Different IP Addresses Each Week
50,000
0
6/11/2001 10/11/2001
2/11/2002
6/11/2002 10/11/2002
2/11/2003
6/11/2003 10/11/2003
History - Month/Week Ending Day/Year
# 14
… and use increases when new
data is posted to website
Website Activity
9,000
100
8,000
Hits per Day - 3rd Quarter, 2003
(3Q03)
7,000
Average Hits
 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
120
80
6,000
5,000
60
4,000
40
3,000
Hits per Day - 3rd Qtr, 2002
(3Q02)
2,000
20
1,000
0
0
1
11
21
31
41
51
61
71
81
Days after Quarter End
Series1
Series5
Percentage of Institutions Released (3Q03 Data)
Percentage of Institutions Released (3Q02 Data)
# 15
Portion of Quarter's Data Available (%)
10,000
Demand for Call Reports declines
as they become older
Number of Hits
180,000
160,322
Hits
90,000
30,000
10,000
8,000
6,000
~
~
Both lines indicate use of mostrecent and prior quarter Call
“Hits”Reports;
reflect
use
mostnote
thatof
hits
diminished
from quarter
160,000
recent
and prior
(September 2003 Call) to fewer
reports,
that2,000
hits
diminish
than note
fewer than
(1998)
51,269
~
~
~
~
sharply as data ages, but yearend data always has higher
use“Unique” = IP Addresses
4,000
2,000
Unique
0
Mar. Jun. Sep. Dec. Mar. Jun. Sep. Dec. Mar. Jun. Sep. Dec. Mar. Jun. Sep. Dec. Mar. Jun. Sep. Dec. Mar. Jun. Sep.
1998
1999
2000
2001
2002
2003
# 16
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”)
# 17
# of Call Reports
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)
9,000
8,000
7,000
6,000
5,000
4,000
3,000
2,000
1,000
-
8,392
7,963
8,392
7,035
5,921
3,715
Current
1,448
CDR
7
1
24
31
38
45
52
55
# of days
# 18
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
# 19
Number of "Hits" to Website's Data Pages
Use of FDIC’s Call Report
website
100,000
80,000
Data page hits usually
drop sharply within 3
– 4 weeks after new
Call Report data is
published
60,000
40,000
20,000
0
0
1
2
3
4
5
6
7
8
9
10
Weeks after Release
# 20
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
# 21
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
# 22
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
# 23
Model form
 Assumptions described previously lead to exponential
model to measure the change in data’s value over the
quarter
 Model is:
where
V(t) = V0e-Kt + Vres
V(t) is the value of the repository at time, t
V0 is the change in value between updates
Vres is the residual value of the repository just before an update
“e” is the exponential function (2.731…)
K is the decay rate (“reciprocal lifetime”)
# 24
Example of analytical model
using data shown previously
Proportion of Quarter's Website Access Occuring During Each
Week
Normalized Value (1.0 at update
time)
1
0.9
0.8
Exponential Model
0.7
0.6
0.5
Weekly "Hits" to Website's
Data Pages (as a fraction of
all hits during the quarter)
0.4
0.3
0.2
0.1
0
0
1
2
3
4
5
6
7
8
9
10
Weeks after Release
# 25
Model will estimate value
gained by efforts to make data
more timely
 will measure improvement when
data is published sooner (“straightthrough processing”)
 details to be provided at XBRL
International presentation
# 26
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)
# 27
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
RCON
Prefix:
RCFD
# 28
Equivalent BASI Concepts for
“Cash and Balances Due” do not vary
Call
Reports
and
BASI
have a
number
of
common
concepts
# 29
Taxonomy tagging: map common concepts
to enable comparisons of Call Reports with
other GAAP sources
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
# 30
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 31
Form 41
Noninterest-bearing balances and currency and coin
RCFD0081
RCON0081
Interest-bearing balances
RCON0071
RCFD0071
Form 31
Form 41
BASI Bank and Savings
Institutions
RCFD0081
RCON0081
CashCashEquivalentsAssets
RCON0071
RCFD0071
InterestBearingDepositsBanks
# 31
Taxonomy
tagging
XBRL Banking and Savings
Institutions Taxonomy
Cash and Balances Due
FFIEC 041 Call Report
Cash and Balances Due
Form 031 –
Institutions with
Foreign Offices
FFIEC 031 Call Report
Cash and Balances Due
XBRL Banking and Savings Institutions
Taxonomy
Cash and Balances Due
Form 041 –
Domestic
Offices
# 32
Finis
# 33