representing the financial system - nitrd

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Representing the Financial System Mark D. Flood Office of Financial Research NITRD Big Data Working Group: 3 rd Workshop on an Open Knowledge Network: Enabling the Community to Build the Network Natcher Conference Center, National Institutes of Health Bethesda, Md.: October 4–5, 2017 Views expressed in this presentation are those of the speaker(s) and not necessarily of the Office of Financial Research.

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Representing the Financial System

Mark D. FloodOffice of Financial Research

NITRD Big Data Working Group: 3rd Workshop on an Open Knowledge Network: Enabling the Community to Build the Network

Natcher Conference Center, National Institutes of HealthBethesda, Md.: October 4–5, 2017Views expressed in this presentation are those of the speaker(s) and not necessarily of the Office of Financial Research.

Views expressed in this presentation are those of the speaker(s) and not necessarily of the Office of Financial Research.2

Disclaimer

Views and opinions expressed are those of the speaker(s) and do not necessarily represent official OFR positions or policy.

Views expressed in this presentation are those of the speaker(s) and not necessarily of the Office of Financial Research.3

Markets are not waiting for lawyers

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S&P

500

Trad

ing

Volu

me

(Inde

xed,

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0)

Moo

re's

Law

(Ind

exed

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Year

Inexorable Force of Technological InnovationComputing Power and Financial Activity, 1970-2015 Moore's Law

< Left axis

S&P 500 Index VolumeRight axis >

Population

Image source: Census Bureau, Standard & Poor’s, Intel Corporation, OFR analysis

Views expressed in this presentation are those of the speaker(s) and not necessarily of the Office of Financial Research.4

Traditional Measurement

Firm-level financial statementsHighly standardized

– FASB– GAAP– Basel capital rules

Backward looking– Historical/fair value– Monovalent

Market transaction informationPre-trade transparency

– Quotes and spreads– Limit orders

Post-trade transparency– Transaction prices– Volumes

Image source : OFR analysis

Views expressed in this presentation are those of the speaker(s) and not necessarily of the Office of Financial Research.5

Focus on Contracts

Positions & Portfolios

Legal Entities

Contracts

Instruments

Relationships

Messages

Transactions

Image source : OFR analysis

Views expressed in this presentation are those of the speaker(s) and not necessarily of the Office of Financial Research.6

Modeling organisms - cribbing from biology• Population characteristics

• Phenotyping

• Genotyping

Measuring Relationships at Three Levels

Interaction networks in harvester antsImage source : Pinter-Wollman, et al. (2011)

Image source : Wikipedia

Image source : Wikipedia

DRAFT/SENSITIVE/PRE-DECISIONAL - FOR DISCUSSION PURPOSES ONLY7

Wells Fargo’s acquisition of Wachovia

Wells Fargo 2006

Wachovia 2006Image source : FFIEC (2015), OFR analysis

Presenter
Presentation Notes
Entities are classified by type (BHC, FHC, DEO, National Charter) Black connects notes of same entity type (homogeneous edges); red is different (heterogeneous edges)

DRAFT/SENSITIVE/PRE-DECISIONAL - FOR DISCUSSION PURPOSES ONLY8

Wells Fargo & Co. acquires Wachovia Corp. in 2008• Wachovia was the fourth largest bank holding company at the time • Wachovia faced a troubled mortgage portfolio and depositor withdrawals

Flood, Kenett, Lumsdaine, and Simon (2017), “The Complexity of Bank Holding Companies”

Wells Fargo’s acquisition of Wachovia

Wells Fargo 2010

Image source : FFIEC (2015), OFR analysis

Presenter
Presentation Notes
Entities are classified by type (BHC, FHC, DEO, National Charter) Black connects notes of same entity type (homogeneous edges); red is different (heterogeneous edges)

DRAFT/SENSITIVE/PRE-DECISIONAL - FOR DISCUSSION PURPOSES ONLY9

Case Study: Wells Fargo 1986-2016

BHC node, edge counts

Quotient cycle ranks

Image source : FFIEC, OFR analysis

Presenter
Presentation Notes
We quotient by entity type and geographic location and compute cycle ranks for quotient graphs in each quarter, from 1996Q1 to 2006Q2 -- Greater variability than a size-based measure provides -- Consistent with intuition that complexity spikes and then declines over time as a firm becomes more integrated/rationalized In this particular example jurisdiction doesn’t changes as Wells is acquiring (e.g., in same state) but entity detects these acquisitions.

DRAFT/SENSITIVE/PRE-DECISIONAL - FOR DISCUSSION PURPOSES ONLY10

FEIII project – ambiguous (RSSD, LEI) pairs

Scoring: ❌=No match ✔=Match ❓=Ambiguous ∅=ID missing

ID Root Modifier Street City State Expert 1 Expert 3RSSD ID: 606046

bancorpsouth bank 201 south spring street tupelo ms

❌ ✔LEI: Q7C315HKI8VX0SSKBS64

bancorpsouth bank 1 mississippi plaza tupelo ms

RSSD ID: 3192960

zions trust, national association

salt lake city ut

❓ ∅LEI: 8WH0EE09O9V05QJZ3V89

zions first national bank 1 south main street salt lake city ut

RSSD ID: 3338357

ojai community bank, 402 west ojai avenue, suite 102

ojai ca

❌ ✔LEI: 5493006EYJ8EDSZFXG70

ocb bancorp 402 west ojai avenue suite 102

ojai ca

RSSD ID: 688079

wells fargo bank northwest

national association

2389 washington boulevard ogden ut

❓ ❌LEI: 549300RFXISSEVCFN040

wells fargo bank northwest, (737 msn 34596 trust)

national association

260 north charles lindbergh drive mac: u1240-026

salt lake city ut

Views expressed in this presentation are those of the speaker(s) and not necessarily of the Office of Financial Research.11

Phenotyping Relationships

Proposed Rule – Qualified Financial Contracts (QFC)• Maintain detailed data on qualified financial contracts

• Deliverable to primary regulator within 24 hours of a request• QFCs have special treatment under FDIC receivership Defining a QFC:• Securities, commodities, forwards, repos, swaps• 102 attributes at contract or counterparty level

• Position-level terms and conditions• Master agreement• Collateral details

Defining a Records Entity – If a party to a QFC, and:• Party to an open QFC, and:

• Could threaten the financial stability of the U.S.,• Designated systemically important financial market utility, or• Total assets exceeding $50 billion; or• Affiliated with a firm that matches the above Image source : OFR analysis

QFC Records Entity

C

B

A

QFC

QFC

?? ?FDIC

? ??

Views expressed in this presentation are those of the speaker(s) and not necessarily of the Office of Financial Research.12

Contract as Automaton

Deterministic Finite Automaton (DFA) as a chain of event and consequence:

– Start state (q0) at the top– Terminal states (3) at bottom– “Happy” or intended path traced

in green– More “interesting” ramifications

traced in black

Flood and Goodenough (2015), “Contract as Automaton”

Image source: OFR analysis

Views expressed in this presentation are those of the speaker(s) and not necessarily of the Office of Financial Research.13

Contract as Data

State Space (27) Event Alphabet (20) Transitions (45)

Q Σ δ

Image source: OFR analysis

Image source: OFR analysis

Views expressed in this presentation are those of the speaker(s) and not necessarily of the Office of Financial Research.14

Regulation and semantic structure

Form PF embeds significant structure• 11 pages of instructions• 10 pages of definitions

Image source: Form PF and Form ADV (SEC, 2011)

Form PF

Form ADV

Refers to

Structure in Form ADV• 25 pages of instructions• 8 pages of definitions

Views expressed in this presentation are those of the speaker(s) and not necessarily of the Office of Financial Research.15

Ontology for Form PF

Image source: OFR analysis

Fan and Flood (2016), “An Ontology of Form PF,” DSMM'16 Proceedings, ACM SIGMOD

Views expressed in this presentation are those of the speaker(s) and not necessarily of the Office of Financial Research.16

Gratitude

Thanks!