The Use of Artificial Intelligence...AUTOMATION / CHAT BOTS is an AI which conducts a conversation...

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The Use of Art i f ic ial Intel l igencein Asset ManagementS h o r e l i n e C o n s u l t i n g I n d u s t r y R e s e a r c h

S e p t e m b e r 2 0 1 9

2© Copyright Shoreline Consulting Pty Ltd 2© Copyright Shoreline Consulting Pty Ltd

C o n t e n t s

1

ABOUT SHORELINE

SURVEY RESULTS

SUMMARY FINDINGS

INTRODUCTION AND APPROACH

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PROFILE OF RESPONDENTS

I n t r o d u c t i o n a n d a p p r o a c h t o t h e 2 0 1 9 a s s e t m a n a g e m e n t A I u s a g e s u r v e y

0% 10% 20% 30% 40%

< $10b

$10 - $40b

$40 - $80b

$80 - $150b

> $150b

Asset Managers (75%)

Asset Owners (25%)

PARTICIPATING FIRMS

Shoreline Consulting has conducted industry research for the past two years

into the use of Artificial Intelligence (AI) by asset managers and asset owners.

Designed to be an indicator of how far the asset management industry is progressing

with its AI journey, we have carefully collected data across a range of organisations to check

the actual use of and attitude towards AI relative to the mostly vendor and consultant

driven reports in the media.

RATIONALE SCOPE

Our research is focused on answering three key questions:

What is the actual usage of AI by the asset management industry in the region?How is it being used?What benefits are being realised?

For the purposes of our survey we have kept the definition of AI simple - AI are systems that can perform tasks that typically require human intelligence. See Slide 10 for our 7 categorisations of AI.

Our survey responses come from 48 asset management firms operating across

markets in Australia, NZ and Asia. This compares to 38 firms in 2018.

Participating firms include asset managers ranging from global players down to

boutiques, sovereign wealth funds, pension / superannuation funds, and insurance firms.

Survey respondents have included a mix of CIO’s, portfolio managers, COO’s, technology

leaders, and data specialists.

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2 0 1 9 s u m m a r y f i n d i n g s

ALPHA ENHANCEMENT & EFFICIENCY ARE THE CLEAR BENEFIT DRIVERS

The majority of firms are realising benefits, mainly through enhanced investment outcomes and operational efficiencies, whilst a third of firms are not yet sure of the benefits.

INVESTMENT IN THE FRONT OFFICE IS THE PRIORITY

Spend in the front office is by far the priority and has increased from 2018, with Predictive Analytics and Machine Learning the main types of AI applied. Front office use cases fall into two main categories – investment decision support and investment process automation.

AI USE IS INCREASING

The use of AI is increasing, with many still in the early stages of adoption. Internal capability development is the preferred method for implementation and applying AI to the right problem remains critical to success.

THE HYPE IS FADING

The AI hype is starting to settle, with a noticeable shift in the attitude of firms on the role of AI from transformational in 2018 to just another technology choice in this year's survey.

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T h e R o l e o f A I

The AI hype is starting to settle, with a noticeable shift in the attitude of firms on the role of AI from transformational in 2018 to just another technology choice in this year's survey

BusinessTransformationalInsignificant

Another technology

AI will transform the way we operate and compete

AI will be required to stay competitive

AI is another technology choice to enable our business

AI will make no meaningful change to our business

We are unlikely to use AI over the next 5 years

2 0 1 9 2 0 1 8

16%

26%

54%

2%

2%

• In 2018, the majority felt the impact of AI would be more toward the transformational end of the spectrum.

• In 2019, there is a marked increase in respondents signalling that ‘it’s another technology choice to enable our business’.

• Those using AI believe it will be transformational –with more than 80% indicating so.

• Of those that believed AI was another technology solution, few have actual AI experience with only 13% using AI.

• Similar to 2018, firms that believe AI’s future role will be insignificant are all small Asset Managers (FUM <$10bn).


C u r r e n t U s e o f A I

The use of AI is increasing with many still in their early stages of adoption and implementation; with problem definition / identification to be a key success criteria.`

of respondents are intending to start adopting AI within 12 months.

of respondents are using some form of AI, up 15% from 2018

36% 50% 14%

U S E R S C O N S I D E R I N G N O N - S T A R T E R S

of respondents have no plans to adopt AI, for the reasons below.

FIRM TYPES & SOURCING88% are Asset Managers

59% have AUM >$150bnFirms are building internal

AI capability with most using in-house staff

CONVERSION FROM 201821% of those from 2018 that

indicated they would use AI within the next 12 months did become

AI users in 2019

WHY NOT AI?43% Not currently a priority

29% Unclear how to apply / where to start

14% No suitable problems for AI

14% More research on use required


79%

64%

43%

36%

21%

21%

21%

0% 20% 40% 60% 80% 100%

Predictive analytics

Machine Learning

Robotic Process Automation

Sentiment Analysis

Chat Bots

Natural Language Processing

Deep Learning

P r i o r i t y o f A I I n v e s t m e n t

Spend in the front office is by far the priority and has increased from 2018, with Predictive Analytics and Machine Learning the main types of AI applied.

I N V E S T M E N T F O C U S - B U S I N E S S A R E A S I N V E S T M E N T F O C U S - T Y P E S O F A I

0% 20% 40% 60% 80% 100%

Front Office

Sales & Marketing

Client Servicing

Risk & Compliance

Middle Office

Back Office

Product

Other

2019

2018

2019

2018

• Front office continues to be the priority for AI, attracting the lion share of investment and rising - up 55% from 2018.

• Sales & Marketing is a secondary priority receiving roughly half the attention of Front Office, but up 80% from 2018

• Risk & Compliance investment has doubled (off of a small base) and usage in Product has fallen off the priority list

• All users are planning additional AI investment predominantly directed to the Front Office`

• Investment in Machine Learning remains a priority, with a slight increase from 2018

• Application of Predictive Analytics has doubled since 2018, making it the new top priority over Machine Learning

• Natural Language Processing has seen the biggest drop, halving in priority from 2018

• Investment in RPA remains strong, but has dropped off slightly from 2018 (10% drop)

A few potential reasons for this:• Many new, freely available data sources and increased use of cloud

platforms with strong data visualisation capabilities• Cloud tools have automated ML capabilities making it easier to build

algorithms


A p p l i c a t i o n o f A I i n t h e F r o n t O f f i c e

Front office use cases for AI cover a broad range but fall into two main categories – investment decision support and investment process automation

U S E C A S E S I N F R O N T O F F I C E

47%

42%

37%

32%

32%

26%

21%

11%

0% 5% 10% 15% 20% 25% 30% 35% 40% 45% 50%

Stock Screening

Generation of unbiased views/second opinion

Risk Management

Forecasting of economic data

Forecast future returns of asset classes

Predicting Market Trends/Sentiment

Fund Manager Selection Support

Other

• This years results are broadly consistent with last years. The top three applications remain unchanged although all lost some ground in favourof Forecasting of Economic Data and Asset Class Future Returns.

• This ties into the doubling of Predictive Analytics from last year (see previous page).

• Risk Management, a top three use case, refers to investment risk management. This is in stark contract to operational risk management, which is not a benefit being realised by AI users (see the next page).


B e n e f i t s R e a l i s a t i o n

The majority of firms are realising benefits, mainly through enhanced investment outcomes and operational efficiencies, while a third are not yet sure of the benefits

67%

58%

42%

17%

8%

0%

Enhanced investment insights

Operational efficiency gains

Improved investment performance

Improved client servicing

Reduced errors

Risk reduction

0% 25% 50% 75%

B E N E F I T S D E R I V E D

1 firm using AI is not getting value

36% say its too earlyto quantify benefits

D O W N F R O M 7 0 % I N 2 0 1 8

W H Y V A L U E I S N O T R E A L I S E D

• Did not apply AI to the correct type of problem

• Did not appropriately integrate the solution into workflows

57% are realising benefits

U P F R O M 3 0 % I N 2 0 1 8

• Enhanced insights and efficiency gains remain the top two benefits, while the number of firms claiming improved investment performance has doubled from 2018.

• Risk and Error reduction are not being realised as primary benefits. Those planning AI use may need to adjust expectations as they are expecting to realise benefits in these areas.

• Given all the hype over ‘robots stealing our jobs’, none of the participants expect to realise FTE reductions from the use of AI.


INTELLIGENT CONVERSATION AUTOMATION / CHAT BOTS is an AI which conducts a conversation via auditory or textual methods. Chat bots use Natural Language Processing to ‘understand’ a request and respond conversationally as a human would.

SENTIMENT ANALYSIS use of Natural Language Processing and other techniques identify, extract, quantify, and study affective states and subjective information, for example to assess sentiment towards a company based on social media channels.

NATURAL LANGUAGE PROCESSING, EG. VOICE RECOGNITION use of artificial intelligence to effectively and efficiently process large amounts of human (natural) language data.

DEEP LEARNING a class of machine learning whose algorithms mimic the human brain, learning multiple levels of representations that correspond to different levels of abstraction.

A p p e n d i x - W h a t i s A I ?We categorised AI into the most common types / applications:

MACHINE LEARNING is a technique to give computer systems the ability to "learn" (e.g., progressively improve performance on a specific task) based on data, without being explicitly programmed.

PREDICTIVE ANALYTICS encompasses a variety of statistical and Machine Learning techniques including predictive modelling and data mining that analyse current and historical facts to make predictions about future or otherwise unknown events.

INTELLIGENT / ROBOTIC PROCESS AUTOMATION combines fundamental process redesign with robotic process automation and machine learning.

© Copyright Shoreline Consulting Pty Ltd

A b o u t S h o r e l i n e


A b o u t S h o r e l i n e

INDEPENDENCEWe have no affiliation with vendors or service providers and make decisions based only on what is best for our clients.

INVESTMENT INDUSTRY EXPERTISEOur expert consultants are specialised advisors and practitioners with extensive first-hand knowledge and experience in the asset and wealth management industry.

DESIGN-PLAN-DELIVEROur focus is on achieving tangible outcomes for our clients, providing strategic advice and design, program planning and mobilisation, and hands-on implementation to solve business problems from start to finish.

PROVEN APPROACHOur proven industry-specific methodologies and frameworks, honed over a decade of successful client engagements, accelerate and de-risk delivery of client outcomes.

Our purpose is to help asset and wealth managers make the most of their opportunities in a rapidly changing industry

We have successfully delivered outcomes for over 60 asset and wealth managers across the Asia-Pacific region.

Our team of specialists based in Sydney, Melbourne, and Singapore cover Asia, Australia and NZ.

Independently owned and operated, we are not influenced by vendor affiliations – only what’s best for our clients.

Long standing client relationships and strong client advocacy are the key to our 10 years in operation.

SOLUTION & SERVICE PROVIDER SELECTION

OPERATIONS & OUTSOURCING

DATA & ANALYTICS

PRODUCT & DISTRIBUTION

DIGITAL & TECHNOLOGY

IMPLEMENTATION

Shoreline provides market, operations, and technology expertise to some of the world’s leading asset and wealth managers across Asia-Pacific

R E A L E X P E R T I S E , R E A L R E S U LT SO U R C A P A B I L I T I E S

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W H O W E A R EO U R V A L U E P R O P O S I T I O N


H o w S h o r e l i n e c a n h e l p

Our cross section of knowledge in Investment Management Front to Back Office, AI & Analytics and Data Management provides the necessary experience required to work with asset managers and owners to identify and define suitable problems / usecases and operationalise AI solutions.

• Interested in AI but don’t know where to start or how it could benefit your firm?

• Successfully executed an AI experiment and now want to operationalise?

• Attempted AI but your data is not fit-for-purpose?

• So you have poor data quality, hampering AI intentions and more broadly impacting investment decision making and operations?

• Not yet ready for AI but want to improve fundamental investment analytics and reporting capabilities?

Y O U R C H A L L E N G EAI Strategy and Roadmap Development

AI Proof of Concept Development

AI Solution Operationalisation

Data Management & Governance Capability Assessment

Investment Data Management Operating Model Design

Data Management Tool Selection

Advanced Analytics & Data IntegrationSolution Design

Data Governance Design and Operationalisation

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C o n t a c t I n f o r m a t i o n

Should you have any questions on information contained within this document, please contact:

J O H N D I B I A S EManaging Director

[email protected]

A N G E L O C A L L E J AAssociate Director

[email protected]

SingaporeLevel 11 Marina Bay Tower 1 8 Marina Boulevard Singapore 018981+65 6653 4470

China JapanSouth Korea

Australia

Singapore

New Zealand

Taiwan

Malaysia

Shoreline team

Market coverage

Indonesia

Hong Kong

SydneySuite 801b, Level 884 Pitt StreetSydney, NSW, 2000Australia+61 2 9235 0245

MelbourneLevel 3035 Collins StreetMelbourne, VIC, 3000Australia+61 3 9900 6402

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The Use of Artificial Intelligence...AUTOMATION / CHAT BOTS is an AI which conducts a conversation...

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