Legal Entity Identifiers, Financial Reference Data and the need for Universality and Standards

The need for Quality Hierarchal LEI data, DTI?? and other emerging Universal Financial data standards (UTI, UPI, et al) are enabled thru advanced contextual graph models plus exploitation of Blockchain technological disruptive capability

Ontology24/7/2016

Bill Freeman, Paul Houle , Allan Grody, patent pending

Daily, GlEIF concatenates and archives the data

Financial Stability Board,

CFTC,OFR, Treasury

Reg Oversight Committee,

Basil, EC, Global regulators

Global Legal Entity Identifier Foundation

Local Operating Units

LOUs register entities and supply data files to GLEIF

established oversees

Global LEI System(GLEIS): A Work in ProcessCurrent State Under Stress

• Individual Records are supposed to be updated at least yearly, but lapse rates for such updating is 25%

• (although they should LEI records must be updated sooner for corporate actions to make the GLEIS relevant for use as golden copy for internal use by financial institutions

• Ultimately Needed : Real-time , streaming data analytics to monitor SIFI, trading , and the buildup of systemic risk capital adequecy

• LOUs publish daily updates, which are consolidated daily by the GLEIF. Process and data variables at LOU’s problematic (i.e. ___________, ____________, __________) Note;add examples please

• A complete snapshot of the data is kept every day, giving a valuable record of system history

Ontology24/7/2016

Current Challenges Uncertain use and value of LEIs in recording transactions in Trade Repositories (TRs)–

tens of billions of transactions have been sent to TRs with no way of validating LEI’s usefulness and quality

Different Internal Data and Communication Models at LOU’s will prohibit advanced technology deployment if not standardized

LEIs as mechanism to aggregate data on a hierarchical relationship basis is being put off to an uncertain outcome

The use of the GLEIS for aggregating financial transaction data for systemic risk analysis, the key objective for regulators, is not yet accommodated in either the rule making or the design of the GLEIS

The promise to financial industry members of straight-through-processing, significant infrastructure cost reduction and risk mitigation is not being realized, nor is it being identified in industry plans – near term or in the future

Little standard operating Procedure Manual Mutual Funds Ignored ( oretty much ) if not Challenging to understand the quality of information, sources and audit

Reference Data As Seen By Financial IT

Trading software

Entity data Product data

Trade data

AnalyticsReporting

Risk management

Straight-through processing (risk elimination)• Needs immediate reaction to changes

affecting entitiesAnalytics, Reporting (Risk management)• Need to understand current state AND

also what reference data was relevant to the trade at the time

Ontology24/7/2016

Current LEI System is Not Fast,Scalable or Secure

Update Rates Suffer

5 days of daily updates requires 5 copies of the data5 days of hourly updates requires 120 copies of the data (Note: assume you are

showing a single LOU example – how many hours of operation to get to the calculations shown? Needs better example

… and hourly might not be fast enough to keep up with real-time trading and changing conditions under stress situations

Ontology24/7/2016

Next-Generation LEI System

Global Legal Entity Identifier Foundation

manages

Blockchain run collectively by Local

Operating Units

Blocks in chain represent changes to reference data published by Local Operating Units in conjunction with their registrants and their

customers

We get best of both worlds:Global update of reference data updated on a

few second timescale AND

Complete historical record at time of trade (keep block id for exact reference!)

Ontology24/7/2016

Ontology2 Technology Enhances Blockchain

“Lambda Architecture” operation (“Superbatch” ) to process updates in either a large batch (whole database) or in small batches (one block) Perfect for Blockchain! Ablility to accept or reject changes from blockchain to

minimize the effect that incorrect or malicious data from blockchain impacts operations, reporting or analysis

Semantic capability to represent, reason, and work with multiple representations of a situation (integrate blockchain-sourced reference data with legacy and future systems)

Ontology24/7/2016

Index CloudNew Index Construction Never Conflicts With Production

time

Old index (multiple copies for throughput & availability)

Source data

Test

Clone

New Index

Manage andrecover

resources

Ontology24/7/2016

Intelligent Index ( ML ) plus Real-Time Index Build can be self correctingEffortless and efficient scalability

Message Queue

Bulk Datatime stamped master data

small real-time index

large bulk index

merger

RESULTS

Ontology24/7/2016

New approach to data managementA FRAMEWORK FOR DATA QUALITY

Multiple sources of instance data

Factsclassifications

Reference data…

ExamplesTest Data

Training DataRequirements

Quality metrics

Ontology24/7/2016