modernizing compliance via regtech · modernizing compliance via regtech moderator: walter...

Modernizing Compliance via RegTech

Moderator: Walter Zebrowski, CPA, JD, Chairman, Regulatory Compliance Association Senior Fellow from Practice:

Danielle Ryea, Executive Director, Financial Services/Regulatory Compliance

Guest Lecturers:

C. Ryan Munson, Senior Manager, Financial Services/Regulatory Technology Lead

Matthew Taverni, Corporate Compliance Senior Manager at MFS Investment Management

Anuj Puri, Senior Manager, Regulatory Compliance

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Introduction: Today’s Presenters

Danielle Ryea is an Executive Director in the

Advisory Services practice. She has over 18

years of direct regulatory experience. In her

role as a branch chief at the SEC, Danielle led

routine, cause and risk-targeted

examinations of registered investment

advisers, investment companies, and broker-

dealers to assess compliance with federal

securities laws and regulations.

Danielle focuses on Wealth & Asset

Management clients leading engagements to

optimize Compliance and Supervision

functions through operating model

enhancements and RegTech applications.

Danielle M. Ryea

Managing Director, Ernst & Young

Direct: +1 212 773 0160

Email: [email protected]

Ryan currently co-leads EY’s Regulatory

Technology campaign supporting wealth and

asset managers in the selection, implementation

and use of RegTech solutions to enhance firms’

compliance and supervision programs.

Ryan is a Senior Manager in EY’s Advisory

Services practice. He has over 19 years of

experience as a management consultant within

the Financial Services Industry. Areas of

specialty include operational process

improvement, technology implementations, and

non-financial regulatory reporting. Ryan holds a

Master’s Degree in Management Information

Systems from Stevens.

C. Ryan Munson

Senior Manager, Ernst & Young

Direct: +1 215 448 5551



Introduction: Today’s Presenters

Matthew Taverni is an assistant vice

president at MFS Investment Management®

("MFS®"). He leads the compliance

governance programs team within the

Compliance Department and is responsible

for maintaining MFS' US compliance,

managing the regulatory compliance

aspects of MFS' committee governance

structure, and overseeing a team focusing

on data analytic activities to enhance

department-wide monitoring capabilities.

Matthew Taverni

Corporate Compliance Senior Manager

at MFS Investment Management


Anuj Puri is a Senior Manager in the Financial

Services Advisory practice of Ernst & Young

LLP. He has 14 years of experience consulting

for financial institutions and information

technology firms in the Capital Markets domain.

Anuj is currently leading the Reg BI

implementation efforts at a large wealth

management client. He is responsible for

assessing the Reg BI impact on the client’s

engagement models and business activities,

defining the requirements for the process and

system changes and updates to the process

flows required to comply with Regulation Best

Interest.

Anuj Puri

Senior Manager, Ernst & Young

Direct: +1 201 551 6197



Agenda

Introduction

Today’s Objective

Introduction to RegTech

Maturity Model

RegTech Capabilities

Enhancing Compliance Process through RegTech

RegTech Business Case

Maturing RegTech Challenges

1

2

3

4

5

6

7

8


Today’s Learning Objectives

Define RegTech within asset management compliance

Apply RegTech maturity model to an asset management compliance program

Define potential core and leading RegTech capabilities for an asset management

compliance program

Assess and prioritize opportunities to implement RegTech capabilities based on cost,

complexity, available resources, and return on investment/benefit

List critical elements of a business case supporting a RegTech proof-of-concept

investment/exercise

Recognize potential RegTech implementation challenges and identify methods to

overcome them


Introduction to RegTech

New technologies that facilitate the delivery of regulatory requirements more efficiently and effectively than existing

capabilities. This technology ranges from complementing existing compliance, audit, and risk workflows to replacing

and wholly automating them through leveraging cutting-edge technologies like artificial intelligence, machine

learning, and the blockchain.

Compliance and supervision leaders are facing real challenges of:

increasing oversight

reducing costs, and

utilizing existing infrastructure/technologies that cannot keep up with new regulations

As a result, firms are finding a need to assess the effectiveness of current regulatory compliance and

supervision technology applications and evaluate the emerging capabilities of RegTech.

Regulatory Technology, or RegTech, is drawing significant focus and investments from regulators,

technology providers, and financial institutions in the wealth and asset management industry. Given the

technology’s potential to disrupt and enhance compliance and supervision processes and systems,

both large and mid-size firms have recently started to explore RegTech solutions to achieve greater

agility, better productivity, and lower costs within the compliance and supervisions functions.

What is RegTech?


Introduction to RegTech: Key Characteristics and Common Applications Key Characteristics

Agility – cluttered and intertwined data sets can be decoupled and organized through ETL

(Extract, Transfer Load) technologies

Speed – reports can be configured and generated quickly

Integration – short timeframes to get solution up and running

Analytics – RegTech uses analytic tools to intelligently mine existing “big data” data sets and

unlock their true potential e.g. using the same data for multiple purposes.

Common Applications in Asset Management

• Legislation/Regulation gap analysis tools

• Regulatory Monitoring

• Policy Management

• Compliance universe tools

• Identity verification

• Management Information tools

• Transaction reporting tools

• Regulatory reporting tools

• Activity monitoring tools

• Training tools

• Risk data warehouses

• Case management tools

• Transaction monitoring


Introduction to RegTech: Regulatory History

2015: At a governmental level, the FCA was the first governmental body

to establish and promote the term RegTech, defining it as: "RegTech is a

sub-set of FinTech that focuses on technologies that may facilitate the

delivery of regulatory requirements more efficiently and effectively than

existing capabilities".

2010: Regulators began in earnest to explore and investment emerging analytical

capabilities and other newer surveillance technologies to enhance their own

oversight and examination programs

SEC -

NEAT (National Examination Automation Tool

MIDAS (Market Information Data Analytics System) : for analyzing equity

market data

2018 : Regulators around the globe are driving RegTech innovation by

supporting the development of advanced solutions in a controlled

environment, sometimes referred to as a ‘Regulatory Sandbox.’ Such facilities

allow regulators to get hands-on with new ideas, understand them, shape

them if appropriate, and generate insights to feed back into mainstream

regulatory activities.

20

Maturity Model

Where does your firm stand?


RegTech Maturity Model: Overview

The use of artificial intelligence, robotics and machine learning are

leading practices within regulatory compliance.

Many firms are at the beginning of that journey and will need to

strengthen their organizations’ regulatory compliance functions by

maturing their foundational technologies.


RegTech Maturity Model: Limited and Core

Most firms have Limited and Core RegTech capabilities utilizing standard business and

office suite software programs.

Limited

Characteristics

► Manual monitoring and testing processes

► Limited workflow/case management capabilities

► Issue-based reporting

Examples

► Pivot tables, filters, limited reporting

1 Core

Characteristics

► Disparate systems, lacking integration and communication capabilities

► On-demand management reporting

► Minimally efficient workflows

Examples

► Semi-automated processes and workflows, fragmented data analytics, siloed management reporting

.

2


RegTech Maturity Model: Enhanced and Leading

Fewer firms have Enhanced RegTech capabilities utilizing advanced analytics

and some automation for routine processes. Leading RegTech capabilities are

primarily roadmap items.

Enhanced

Characteristics

► Enterprise-based technologies that support both lines of business (LOB) and enterprise needs

► Standard reports for both LOB and enterprise purposes

► Streamlined processes

Examples

► Robotics, natural language processing, advanced analytics, continuous monitoring

3 Leading

Characteristics

► Integrated technology infrastructure

► Full automation of compliance processes

► Insightful management intelligence reporting

Examples

► Artificial intelligence, machine learning, predictive analytics

4


RegTech Maturity Model: Regulatory Expectations

As the next generation of regulatory

obligations and expectations

becomes more sophisticated, the

convergence of RegTech and the

associated capabilities to meet

regulatory demands creates the

necessity for firms to evaluate their

current technology solutions.

“… These RegTech tools have the

potential to fundamentally transform

how securities industry participants

perform their compliance

obligations.”

FINRA, “Technology Based Innovations for Regulatory Compliance

(“RegTech”) in the Securities Industry,” September 2018

Overall, regulators are likely looking for firms

to leverage RegTech capabilities where it

makes sense.

Key is to ‘right-size’

• Balance between technology spend and

compliance program / risk management

need

Factors that may influence what the ‘right-size’

is could be:

• AUM

• Strategy

• Size of firm (employees)

• Jurisdictional footprint

25

RegTech Capabilities How to incorporate RegTech for different-sized firms


RegTech Capabilities: Overview

CAPABILITIES BENEFITS MATURITY

► Utilizes diverse data to perform

complex analyses

► Assists in making decisions and

exploring new and emerging risks

► Identify patterns

► Allow employees to focus on

making complex decisions

► Unlocking insights from data through

intuitive reports that allows users to

explore and drill-down into the data

► Provide real-time insights

► Empower business stakeholders

► Automates certain activities (e.g.,

manipulating data)

► Runs unattended

► Reduce costs, errors & cycle time

► Increase economies of scale

► Extract insights and content from

digitized documents ► Facilitate digitization of processes

► Analyze, understand and derive

meaning from unstructured text data

► Enable automated review of

documents and other unstructured

text data

► Using machine learning to classify,

cluster and make recommendations

► Enable automation and signal

extraction

► Connect disparate data-sources

based on relationships and core

connections

► Increased efficiency for storing,

processing and querying data

► Execute tasks, communicate self-

learning and make sophisticated

recommendations

► Facilitate decision making and

provides higher accuracy for

automating more complex tasks

Data Analytics

Visualization & Self-Service

Analytics

Robotics Process

Automation

Transcription & Feature

Extraction

Natural Language

Processing

Fundamental Machine Learning

Knowledge Graphs

Deep Learning

Core

Enhanced

Leading


RegTech Capabilities: Core Maturity

Data Analytics

Capabilities

► Utilizes diverse data to perform complex analyses

► Assists in making decisions and exploring new and emerging risks

Benefits

► Identify patterns

► Allow employees to focus on making complex decisions

1


RegTech Capabilities: Enhanced Maturity

Transcription & Feature Extract

Capabilities

►Extract insights and content from digitized documents

Benefits

►Facilitate digitization of processes

1 Natural Language

Processing

Capabilities

►Analyze, understand and derive meaning from unstructured text data

Benefits

►Enable automated review of documents and other unstructured text data

2


RegTech Capabilities: Leading Maturity

Knowledge Graphs

Capabilities

►Connect disparate data-sources based on relationships and core connections

Benefits

►Increased efficiency for storing, processing and querying data

1 Deep Learning

Capabilities

►Execute tasks, communicate self-learning and make sophisticated recommendations

Benefits

►Facilitate decision making and provides higher accuracy for automating more complex tasks

2


Enhancing Compliance Process through RegTech: Illustrative Use Cases:

Analytics Enabler Value Provided to Compliance Process

Marketing and

Advertising Review

► NLP

► Machine Learning

► Enables marketing material review automation and significantly reduced manual effort in

review process

► Streamlines workflow processes and sophisticated routing based on complexity of

documents

Conflicts of Interest

Management

► Data Analytics

► Visualization & Self-

Service Analytics

► Automate oversight related to conduct risk areas (e.g., personal trading, gifts and

entertainment, outside business activities and political contributions)

► Ability to target key risk areas to identify training gaps

Expense Allocation

► Robotics Process

Automation

► Enables increased governance of expenses with the automated collection of

referential data (e.g., deal status, equity source) and by establishing a relationship between

deal codes in multiple reporting systems

► Provides increased accuracy in allocations with automated calculations

Email Surveillance

► NLP


Automation

► Utilizes contextual analysis to reduce false positives as compared to a traditional lexicon-

based approach

► Decreases email review time by automating standard review process for email alerts

► Utilizes graph analytics to detect relationships between words and individuals

► Leverages advanced analytics and models to pinpoint suspicious e-communications

Anti-Money

Laundering/

OFAC


Automation

► Machine Learning

► Automates OFAC screening searches of entries against an optimized set of government

watch lists for reduced false positives

► Alert optimization using machine learning techniques


Enhancing Compliance Process through RegTech: Buy vs. Build

Consider Buy vs. Build

Build: Design

• Document business and

functional requirements

needed to meet strategy

objectives

• Design and plan integration

with current infrastructure

and create a proof of

concept

• Develop to meet business

and functional requirements

Buy: Vendor Selection

• Document business and

functional requirements

needed to meet strategy

objectives

• Conduct RFP and due

diligence on vendor

technologies and solutions

factoring in ease of

implementation, integration

capabilities, and data

sourcing requirements

Disadvantage

Buy

Build

32

How to Get Started


Reg-Tech Business Case: Key Elements

Effort

Resources (FTEs and Consultants)

required to accomplish the task

Parties Involved

List of stakeholders across

Compliance, IT, Business,

Legal, Risk, Audit, Etc.

Timeframe

The overall timeframe of the RegTech

business case

Licensing Costs

Licensing costs associated with the

RegTech technology platform

Retail Costs

Retail costs associated

with the RegTech

business case

Output/Demo

Illustrative output of the

RegTech solution

Opportunity

The opportunity that

founded the RegTech

business case

Benefits Benefits from carrying out

the RegTech business case


RegTech Business Case: Opportunity Scan Assessment

# Compliance

Process Value

Risk

Profile Notes

1

Review of

prospectus

changes

Medium Medium Minimal records and applications

associated with test

2

Develop a self

service portal for

data queries

High Low Could leverage ServiceNow?

Minimal risk area

3

Create

compliance data

hub to normalize

data fit-for-

purpose

High Medium Data quality is critical

Wide-ranging impact

4

Employ AI tools

to comply with

CRD rules

Medium Medium High cost of implementation

5

Automate review

of marketing

materials

High High

Automate to reduce review time, greater

speed to market

High scrutiny by regulator

6

Create

Compliance

reporting and

dashboards

Medium Medium Improve management reporting

An opportunity scan assessment can be used to identify potential use cases with the highest efficiency gains. Throughout the

assessment, selected compliance processes are assessed for efficiency opportunities and risk factors. The output –

represented below - represents a graphical view of the assessment scores for each area, where the most ideal candidates will

be indicated with the highest efficiency gains and highest risk mitigation can be achieved.

Val

ue

Risk Factor

High Low

1

2

High

3 4

5

6

Recommendations


RegTech Business Case: Executing a Proof of Concept

• Understand what compliance desires to achieve or what pain points they are solving for

• Identify the expected value or ROI Prove the Need

• Brainstorm ways to solve pain points

• Evaluate each possible solution to determine how it stacks up in reference to cost, competition, timeline, technology challenges, etc.

Map Pain Points to Solutions and Get

Feedback

• Create a prototype that wraps your solution into a rudimentary product

• Once the prototype is built, test it with your interviewees for additional feedback

Prototype Your Solution and Test

• Create a roadmap that incorporate feedback and outlines a recommended step-by-step process for building the product

Design a Roadmap


Maturing RegTech Challenges

Change management: Replacement of legacy systems may disrupt operations, change business processes and necessitate a cultural change

2

Data: Fragmented and poor-quality data delays the implementation and severely impacts the effectiveness of Reg Tech platforms 5

Vendor risk management: Legacy controls, processes and oversight may not meet third- party risk management criteria

4

Talent: Existing resources may lack the skills to realize the full benefits of RegTech tools

3

Strategy: Without an overarching RegTech strategy, implementation dependencies and risks may not be identified

1

Thank You

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