15 November 2019© MARKLOGIC CORPORATION

Taming the regulatory beast

The route towards digital regulation

Dr Giles Nelson

CTO Financial Services, MarkLogic

State of play today

Quantity

Complexity

Divergence

Cost

▪ 374 regulatory initiatives in play by 2021

- 90% applicable to both buy and sell-side firms

▪ Firms still predominantly using a ”project-based,

highly-manual, siloed approach”

- Expediency is expensive

Highlights from 2019 research on the regulatory landscape

Fed

ECBCFTC

BaselFCA

FSBSEC

MAS ASIC

FINTRAC

ESMA

AMF

FSA

SFC

PRA

FINRA

MAS 610Dodd Frank

FRTB

TRIM

AMLD5

BCBS 239LIBOR replacements

EMIR 239

Intolerable complexity

Regulators X Regulations X Bank systems

n3

The path towards “digital regulation”

“Digital regulation is the use of models and

machine-executable regulations that

enable automated querying and reporting

on regulated firms’ transactional, product,

communications and other data sets to

ensure safer markets at a lower cost”

Digital regulation evolution

time

level of

automation

Manual

Digital

Manual processes

Deadline driven

Siloed solutions and data

Some workflow

Manual intervention

Data pooling and sharing

Data and system reuse

Business value exploitation

Real-time reporting

Excel

Paper

Data definitions

Regulation & business line

specific databases/datastores

Industry standards

Machine readable regulation

Regulator to regulated

algorithmic queries

Speech recognition

Behavioral monitoring

IoT

Integrated data hubs

Compliance as an enterprise

competency

Semantic models/ontologies

Static reports

Regulatory sandboxes

Workflow tools

RPA

Machine executable regulation

Compliance data utilities

Robo regs

Executable regulations

Reports

RegTech

Apps

Ad-hoc

reports

A “digital regulation hub”

Models

Policies

Firm

Parties

Transactions

Products

Regulators

Market and reference data Transactions Other operational data

Natural language

processing

Speech recognition

Technologies

Machine learning

Predictive

analytics

Quantitative

models

Standards, e.g. SKOS

FIBO, OWL etc.

Data

Curation

Security

Search

Provenance &

lineage

Finance & risk

Treasury

Compliance

Sales & trading

Regulators

Regulatory

CofE

CFTC, FINRA

FCA, PRA

Data hub capabilities

Multi model support No direct access to

source data sets

“Data first” approach

Provenance and

lineage of data

Data security and

access

Analytics and

machine-learning

1. Digital regulation is a process, not an event

2. Work iteratively

3. Collaborate. Internally, with regulators & peer organizations

4. Break down data silos, don’t create new ones

To conclude – 4 recommendations

15 November 2019© MARKLOGIC CORPORATION

Thank you

giles.nelson@marklogic.com

@gilesnelson