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Fixing a Leaky Bucket
Observations on the Global LEI System
http://ontology2.com/
May 10, 2016
Major points
• The number of paid up LEI registrations has been flat over the last
year
• LEIs attrition is overwhelmingly due to a failure to re-register as
compared to mergers and dissolutions
• Occasional glitches are observed in data supplied by LOUs, such as
disappearing records and invalid status codes, but things are getting
better
Methodology
• Ontology2 technology
• Break down conventional data (XML in this case) into facts
• PLUS: Apply a “theory of time and change” to facts
• EQUALS: Bitemporal capability (what did he know and when did he know it?)
• Covers all data from the C-LEI era
• 350x the data volume of other LEI analysis to date!
LMAX Disruptor
Inside
High-speed, High-throughput execution fabric
10 million messages per second+
Batch or interactive execution – keeps several steps ahead of competition
Commonsense knowledge base and rules bend instead of break in face of dirty data
Based on map of problem, automatically constructs and tears down resources in cloud;
multiscale architecture applies common strategies to large and small problems
Exception Handling and Case Management for continuous improvement
Issued LEI
records in
good standing
Lapsed LEI
Records
(not renewed)
30,000 records dropped
in one-day glitch
(see next page!)
recordcount
From this LOU
30,000 missing records
Glitch tracked down on GLEIF web site
RETIRED (out of business)
DUPLICATE (of another record)
MERGED (with another
record)
This is a count of invalid LEI record
statusess: these are sometimes
misspelled, such as “ANULLED”
There was a burst of these early on,
but the problem is largely controlled
today.
PENDING_TRANSFER
TRANSFERRED
ANNULLED
CANCELED
(rare indeed!)
Data Dictionary from:
Fixing a leaky bucket; Observations on the Global LEI System

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Fixing a leaky bucket; Observations on the Global LEI System

  • 1. Fixing a Leaky Bucket Observations on the Global LEI System http://ontology2.com/ May 10, 2016
  • 2. Major points • The number of paid up LEI registrations has been flat over the last year • LEIs attrition is overwhelmingly due to a failure to re-register as compared to mergers and dissolutions • Occasional glitches are observed in data supplied by LOUs, such as disappearing records and invalid status codes, but things are getting better
  • 3. Methodology • Ontology2 technology • Break down conventional data (XML in this case) into facts • PLUS: Apply a “theory of time and change” to facts • EQUALS: Bitemporal capability (what did he know and when did he know it?) • Covers all data from the C-LEI era • 350x the data volume of other LEI analysis to date! LMAX Disruptor Inside High-speed, High-throughput execution fabric 10 million messages per second+ Batch or interactive execution – keeps several steps ahead of competition Commonsense knowledge base and rules bend instead of break in face of dirty data Based on map of problem, automatically constructs and tears down resources in cloud; multiscale architecture applies common strategies to large and small problems Exception Handling and Case Management for continuous improvement
  • 4. Issued LEI records in good standing Lapsed LEI Records (not renewed) 30,000 records dropped in one-day glitch (see next page!) recordcount
  • 5. From this LOU 30,000 missing records Glitch tracked down on GLEIF web site
  • 6. RETIRED (out of business) DUPLICATE (of another record) MERGED (with another record)
  • 7. This is a count of invalid LEI record statusess: these are sometimes misspelled, such as “ANULLED” There was a burst of these early on, but the problem is largely controlled today.