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Artificial intelligenceApril LaRusse

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Investment Managers are appointed by BNY Mellon Investment Management EMEA Limited (BNYMIM EMEA) or affiliated fund operating companies to undertake portfolio management activities in relation to

contracts for products and services entered into by clients with BNYMIM EMEA or the BNY Mellon funds.

Any views and opinions are those of the investment manager, unless otherwise noted.

2

What are the experts saying?

Technology that existed when we were born

seems normal, anything that is developed

before we turn 35 is exciting, and whatever

comes after that is treated with suspicion.

Douglas Adams

…there should be some regulatory oversight,

maybe at the national and international level,

just to make sure that we don’t do something

very foolish. …with artificial intelligence we’re

summoning the demon.

Elon Musk

The development of full artificial intelligence could spell the end of the

human race... It would take off on its own, and re-design itself at an ever

increasing rate. Humans, who are limited by slow biological evolution,

couldn't compete, and would be superseded.

Stephen Hawking

“ ““ ““ “

3

Fear of technology is normal

1564 Swiss scientist, Conrad Gessner: people are overwhelmed with data …overabundance was both ‘confusing and

harmful’ to the mind. 1564 (printing press)

1936 Gramophone magazine ‘children had developed the habit of dividing attention their school assignments and the

compelling excitement of the program’ and they were disturbing the balance of their excitable minds. 1936 (radio)

1947 Media historian Ellen Wartella has noted how ‘opponents voiced concerns about how television might hurt

conversation, reading, and the patterns of family living and result in the further vulgarization of American

culture’. 1947 (television)

2005CNN reported that ‘Email hurts IQ more than pot’. 2005 (internet/email)

2009The Telegraph reported that ‘Twitter and Facebook could harm moral values’. 2009 (social media)

2009Daily Mail ran a piece on ‘How using Facebook could raise your risk of cancer’. 2009 (social media)

Luddite – English workers who destroyed machinery, especially in cotton and woollen mills,

which they believed was threatening their jobs

4

Learning to use ‘tools’

Source: Google, Citi Group and Economist January 2017. For illustrative purposes only.

Google estimates that robots

will reach levels of human

intelligence by 2029.

AI robots will replace 1/3 of

jobs by 2025 but be the

largest source of new jobs.

Citi Research

PWC says UK GDP will be

10.3% higher by 2020

because of AI: productivity

(1.9%), new firm entry which

will stimulate demand

(Economist magazine

January 2017)

5

We have all experienced AI first hand

Microsoft Office assistant ‘Clippy’

Financial fraud prevention

Email spam filter

Autopilot Transport – traffic prediction pricing

6

• Why use AI?

– 55% grow market share

– 45% reduce costs

• Best companies for effective AI usage are:

– digitally mature

– larger companies

– adopt AI in core activity

– focus on growth over savings

– customer support for AI

At a corporate level:

Reinvention or adaptation?

Making the most of AI

Where in the value chain can AI help?

Project

Production

Promote

Source: McKinsey &Company, Artificial Intelligence, June 2017. For illustrative purposes only.

Provide

7

Source: McKinsey Global Institute 'AI the next Digital Frontier‘, June 2017. For illustrative purposes only.

Not all sectors are enthusiastic adopters of AI

In 2016 tech companies spent US$30bn on AI

development

Travel companies have good algorithms for booking

travel but they cannot get rid of the human reservation

agents

Media sector faces a challenge trying to make virtual

reality and augmented reality content cost effective

High adopters

• High tech ($30bn 2016)/telecoms

• Auto/assembly

• Fin services

Medium adopters

• Retail

• Media

• Entertainment

Low adopters:

• Education

• Healthcare

• Travel

• Tourism

8

Ginger.io recommends the

best time to take

medication

Bespoke drugs (and

when to take them)

Drug reactions

Prediction Prevention

TreatmentSharing info clinical trials

Diagnosis Surgery

Medical sector

How to use AI to improve medical treatment

Estimates will save UK

NHS £3.3bn per annum

Second diagnosis,

misdiagnosis can be

reduced by 85%

Sedasys system

automatically delivers

anaesthesia

US causes of death:

• 614,000 cancer

• 591,000 heart disease

• 250,000 medical errors

• 150,000 respiratory disease

Source: Johns Hopkins University Study, May 2016. For illustrative purposes only.

9

Transport sector

For illustrative purposes only.

Source: Electrek, April 2016; Association for Safe International Road Travel, April 2018; ThoughtCo.

Why does public transport need to be on rails? A fleet of electric self-driving cars is cheaper than building mass

transit systems

Tesla Austin study:• Goal 10% market share of all journeys in a

100 mile square grid

• Need 31,859 cars and 1,517 charging stations

• Cost per mile US$0.66 vs Private vehicle

US$0.40-0.90 or Lyft/Uber at US$1.50-3.18

Cost:• Morgan Stanley predicts driverless cars will

save the US US$1.3trn a year by 2030− car ownership costs US$5,500 per year− money saved in less time wasted in traffic

jams

Change:• Car manufactures are asking “are we a car

company or a transport company?”− Tesla: Rideshare− GM: Lyft− BMW: Reachnow− VW: Gett

Safety:• Google’s self-driving cars have completed 1.8

million miles. Only 13 accidents (ALL caused by the other car)− 1.3 million die globally in car accidents

10

• Get consumers to buy more by knowing what they need and when they need it

• Less risk of loss of sale due to product unavailability

• Arrange the store or online platform differently: places together the items you buy

together

• Intelligent price: depends on the day of the week, seasons, time of day, weather,

channel and device

• Successful adoption:

− Otto – forecasts demand and automates sourcing. Sales forecast are 90%

accurate (what will company sell in the next 30 days)

− Netflix – personalised recommendations. >90 seconds to find a movie = they give

up. Avoiding cancellation will save revenue of US$1bn annually

− Amazon bought KIVA robotics automated collecting and packing. Time human 60-

75 minutes, vs robot 15 minutes. Inventory capacity increases by 50%. Operating

costs down 20%

Source: eCommerce News, April 2017 and Forbes Magazine, December 2017. For illustrative purposes only.

Retail sector

When you want it

What you want

At a 'good price'

Efficiently

11

Industry/manufacturing

Source: Metro: For Transit and Metrocoach Business, April 2017. For illustrative purposes only.

Productivity improvements can come from all directions

Subway implemented predictive

maintenance when a machine broke

the machine next to it would also

break down. Why?

Was it:

• Installed at the same time?

• Data counted twice?

• Disease contagious?

12

Communications: translation software

Mental Floss February 2016

The importance of good and accurate translation:

In 1956, the Cold War, Nikita Khrushchev said:

We will bury you.“

“We will be present when you are buried.“

“A better literal translation is:

Which means we will outlast you.

13

Source: MIT Technology Review Deep Learning.

Communications: translation software

Microsoft speech recognition software translated spoken English into Chinese with a 7% error rate

14

Ethics

• Unemployment. What happens after the end of jobs? ...

• Inequality. How do we distribute the wealth created by machines? ...

• Humanity. How do machines affect our behaviour and interaction? ... machines can trigger

the reward centres in the human brain…

• Artificial stupidity. How can we guard against mistakes? ...

• Racist robots. How do we eliminate AI bias? ...

– Amazon Prime excluding certain post codes from the service

– Criminal Justice System is full of judicial biases

» racial discrimination by algorithm prediction of re-offending

» Black defendants are 2X more likely to be misclassified

• Security. How do we keep AI safe from adversaries? ...

• Evil genies... AI that can fulfil wishes, but with terrible unforeseen consequences

• Singularity… How do we stay in control of a complex intelligent system?

Source: H.V. Jagadish, Propublica, World Economic Forum October 2016, Isaac Asimov 1942. For illustrative purposes only.

Who polices the algorithms?

Three laws of robotics:• A robot may not injure a human

(including through inaction)

• A robot must obey orders given by

humans except where it conflicts

with first law

• A robot must protect its own

existence as long as no conflict

with 1st and 2nd law.

15

Source: Sloan Review: Boundary Setting Strategies April 2025. For illustrative purposes only.

AI is relevant for picking the winners

Peaked 2004, 60k employees,

9,000 storesPeaked in 1988, 145k

employees, 1996 US$80 per

share

Xerox now trading at 1/6 of the

market cap in 1999

• In bonds there is no upside. Focus is on survival (default avoidance)

• Not necessarily interested in how much profit that can be made from a new product. Focused on changes in the

competitive landscape and increase risk of obsolescence.

• Historic examples of companies caught off guard by technological change.

• Physical trap (invest in old systems), physiological trap (focus on what worked historically), strategic trap (attention on

market today not tomorrow)

https://www.google.co.uk/url?sa=i&rct=j&q=&esrc=s&source=images&cd=&cad=rja&uact=8&ved=2ahUKEwi5l6jknZHaAhVKGhQKHdjoDIkQjRx6BAgAEAU&url=https://www.technobuffalo.com/2013/01/18/flashback-friday-blockbuster-video/&psig=AOvVaw3smJG-JPr8CJFKoSvoMl-P&ust=1522402435950323

16

Credit fundamentals

Source: Bloomberg, Insight calculations. LTM = Last twelve months. Earnings are before depreciation, interest costs, taxation and amortisation (EBITDA). Data as at 31 December 2017. For illustrative purposes only.

Leverage (Net debt/earnings)

Earnings growth is improving fundamentals, lowering leverage and raising interest coverage

Interest cover (EBITDA interest cover)

6.0x

7.0x

8.0x

9.0x

10.0x

11.0x

12.0x

13.0x

14.0x

2003 2005 2007 2009 2011 2013 2015 LTM0.5x

0.7x

0.9x

1.1x

1.3x

1.5x

1.7x

1.9x

2.1x

2.3x

2.5x

2003 2005 2007 2009 2011 2013 2015 LTM

US

EuropeUS

Europe

Average

Average

17

Investment process Security selection: landmine checklist

Aims to identify the risks that can lead to a sharp deterioration in an issuer’s credit quality

Each factor scored 1 (good) to 5 (bad)

ExampleFactor

• Assuming no access to capital markets in the next 24 months, what is the impact on the

issuer’s liquidity?

• What is the magnitude of the issuer’s off balance sheet liabilities such as pension deficits,

operating leases etc.?

• To what extent is the issuer’s industry subject to regulation and changes in regulation?

• Does the management have an appetite for debt financed M&A? Is the company’s share price

underperforming?

• Is the business likely to be subject to an approach from or a bid by private equity?

• Is the issuer properly managing environmental, social and governance risks?

Liquidity

Contingent liabilities

Regulatory risk

Event risk

LBO risk

Environmental, social,

governance (ESG)

18

Increased rating activity

Source: Moodys Investor Services, February 2018.

12 month rating drift

-30%

-25%

-20%

-15%

-10%

-5%

0%

5%

10%

15%

2013 2014 2015 2016

Global US Europe

More

upgrades

More

downgrades

0%

10%

20%

30%

40%

50%

60%

2008 2009 2010 2011 2012 2013 2014 2015 2016 2017

Global_Vol US_Vol Europe_Vol

12 month credit rating volatility

19

Idiosyncratic risks

Source: Bloomberg, February 2018.

M&A activity rising

3.08

1.92

2.54 2.71 2.44

2.67

4.46

5.60

4.91

5.44

20

25

30

35

40

45

50

0.00

1.00

2.00

3.00

4.00

5.00

6.00

2008 2009 2010 2011 2012 2013 2014 2015 2016 2017

ThousandsU

S$ T

rilli

ons

Global M&A volumes (LHS) Deal Count (RHS)

20

Not a beta game anymore

Source: Spreads are Bank of America Merrill Lynch, from Bloomberg. Data as at 30 March 2018.

Investment grade credit spreads

0

100

200

300

400

500

600

700

800

2003 2004 2005 2006 2007 2008 2009 2010 2011 2012 2013 2014 2015 2016 2017 2018

Euro corporate spreads Sterling corporate spreads US dollar corporate spreads

Spre

ad

over

govern

ment (b

p)

21

What does 2018 look like?

Source: Insight as at 16 January 2018.

Growth, inflation and risks to base case:

• UK slows to 1.2%

• EU and US close to 3%

• 2.6% in UK

• 1.4% in EU

• 2.0% in the US

• US fiscal stimulus with

limited domestic capacity?

• Global politics and

protectionism?

• Brexit negotiations?

GROWTH INFLATION RISKS

22

A tale of two economies

Source: Thomson Reuters Datastream as at 30 September 2017. For illustrative purposes only.

UK exports

Exporters benefiting from the global economic upswing, higher inflation impacting consumers

UK consumption

-4

-2

0

2

4

6

8

10

Q1 2

013

Q3 2

013

Q1 2

014

Q3 2

014

Q1 2

015

Q3 2

015

Q1 2

016

Q3 2

016

Q1 2

017

Q3 2

017

%

% change yoy

-0.40

-0.20

0.00

0.20

0.40

0.60

0.80

1.00

1.20

1.40

Q1 2

013

Q3 2

013

Q1 2

014

Q3 2

014

Q1 2

015

Q3 2

015

Q1 2

016

Q3 2

016

Q1 2

017

Q3 2

017

%

% change q.o.q.

23

UK: BoE – between inflation ‘rock’ and Brexit ‘hard place’

Source: Insight and Bloomberg as at 30 December 2017. For illustrative purposes only.

CBI business confidence survey Sterling TWI versus core goods CPI

-60

-50

-40

-30

-20

-10

0

10

20

30

40

Q114 Q314 Q115 Q315 Q116 Q316 Q117 Q317

Surv

ey

result

Post EU vote

result

Future outlook

uncertain

-0.5

0.0

0.5

1.0

1.5

2.0

2.5

3.0

3.5

4.0

70

75

80

85

90

95

100

105

110

Jan-0

0

Ma

r-0

1

Ma

y-0

2

Jul-0

3

Sep-0

4

No

v-0

5

Jan-0

7

Ma

r-0

8

Ma

y-0

9

Jul-1

0

Sep-1

1

No

v-1

2

Jan-1

4

Ma

r-1

5

Ma

y-1

6

Jul-1

7

Core

infla

tion %

UK

tra

ded w

eig

hte

d s

terlin

g

Trade-

weighted

sterling

UK core

inflation

24

Global fixed income capabilities

1 Benchmark: 3 Month GBP Libid. Inception: 30 November 2009. 2 Benchmark: Barclays Capital Global Aggregate Credit (GBP-hedged). Inception date: 30 September 2011

Source: Insight as at 31 March 2018. Performance calculated as total return, income reinvested, gross of fees, in GBP. Fees and charges apply and can have a material effect on the performance of your investment.

Insight claims compliance with the Global Investment Performance Standards (GIPS). Please see appendix for GIPS compliant presentation.

Insight Short-Dated High Yield Bond strategy1 Insight Global Credit strategy2

-1.46

2.21 2.23

3.90

5.35

-1.59

1.55 1.91

3.03

4.17

-2

-1

0

1

2

3

4

5

6

3 months 1 year 3 years(pa)

5 years(pa)

Sinceinception

(pa)

%

Composite Benchmark

0.24

4.21

5.254.89

6.00

0.11 0.28 0.35 0.37 0.48

0

1

2

3

4

5

6

7


5 years(pa)

Sinceinception

(pa)

%

Composite Benchmark

25

Global fixed income capabilities continued

1The representative portfolio adheres to the same investment approach as Insight’s Absolute Insight Credit strategy. Performance calculated as total return, income reinvested, gross of fees in GBP. Fees and

charges apply and can have a material effect on the performance of your investment. Benchmark: 3 Month GBP Libid. Inception: 2 June 2009.2The representative portfolio adheres to the same investment approach as Insight’s Inflation-Linked Corporate Bond strategy. Performance calculated as total return, income reinvested, gross of fees in GBP. Fees

and charges apply and can have a material effect on the performance of your investment. Inception: 9 February 2013.

Source: Insight as at 31 March 2018

Absolute Insight Credit strategy1 Insight Inflation-Linked Corporate Bond strategy2

-0.92

2.99

4.794.41

4.85

-2.0

-1.0

0.0

1.0

2.0

3.0

4.0

5.0

6.0


5 years(pa)

Sinceinception

(pa)

%

Representative portfolio

0.23

5.37

1.95

3.90

11.16

0.11 0.28 0.35 0.37 0.49

0

2

4

6

8

10

12

3 months 1 year 3 years (pa) 5 years (pa) Sinceinception

(pa)

%

Representative portfolio 3 month GBP Libid

26

Representative portfolio performance

1 Benchmark is the iBoxx Sterling Collateralised and Corporate Index. 2 Peer group ranks are shown versus the IA £ Corporate Bond Sector as at February 2018. 3 Inception 1 October 2014

Source: Lipper as at 31 March 2018. The representative portfolio adheres to the same investment approach as Insight’s corporate bond strategy. Performance calculated as total return, income reinvested, net of

annual charges (including AMC of 0.5%), in GBP.

Insight corporate bond strategy

2.23%

7.27%

4.00%

5.46%

1.37%

5.88%

3.95%

5.64%

0

10

20

30

40

50

60

70

80

90

1000%

1%

2%

3%

4%

5%

6%

7%

8%

1 year 2 years(pa)

3 years(pa)

Sinceinception³

Representative portfolio Benchmark Percentile rank vs peer group (RHS)

Aims to outperform its benchmark1 by 1.5%

pa (gross of fees and expenses) over rolling

three-year periods

Core focus on UK is enhanced by global

opportunity set

Actively managed, high conviction portfolio.

Avoids the flaws inherent in a passive

approach

Outperformed its benchmark1, top quartile

performance since inception2

Appendix

28

April LaRusse

Head of Fixed Income Investment Specialists at Insight Investment, a BNY Mellon Company

April joined Insight in September 2008 and leads the Fixed Income Investment Specialist Team.

April joined Insight from F&C Investments where she was a portfolio manager responsible for

managing UK, US and global government bond portfolios. Prior to this, she was in government

bond and derivative sales at Lehman Brothers.

April began her career as a government bond portfolio manager at Newton Investment

Management. April graduated with a BA in Economics from Mount Holyoke College,

Massachusetts, United States and an MBA from City University Business School in London. She

is also an Associate of the CFA Society of the UK.

29

GIPS® firm-wide disclosures

30

GIPS® compliant presentationFixed Income, Short-Dated High Yield Bonds as at 31 December 2017

31

GIPS® compliant presentationFixed Income, Global Credit as at 31 December 2017

32

Source: Lipper and Insight. The representative portfolio adheres to the same investment approach as Insight’s Absolute Insight Credit strategy. Performance calculated as total return, income reinvested, net of annual

charges (including AMC of 1.0% and a performance fee of 10%), in GBP.

Absolute Insight Credit strategyRepresentative portfolio performance as at 31 March 2018

5-year cumulative performance (%)

13.82%

1.76%

0

4

8

12

16

Mar-13 Mar-14 Mar-15 Mar-16 Mar-17 Mar-18

Absolute Insight Credit RP LIBID GBP 3 Months

Calendar year performance (%)

2013 2014 2015 2016 2017

Absolute Insight Credit RP 8.70 2.63 0.34 -3.65 7.32

LIBID GBP 3 Months 0.37 0.38 0.41 0.38 0.23

Performance summary (%)

3 months YTD 1 year 3 years 5 years 3 years ann. 5 years ann.

Absolute Insight Credit RP -0.02 -0.02 4.17 2.74 13.82 0.90 2.62

LIBID GBP 3 Months 0.07 0.07 0.25 1.00 1.76 0.33 0.35

33

Source: Lipper. The representative portfolio adheres to the same investment approach as Insight’s Inflation-Linked Corporate Bond strategy. Performance calculated as total return, income reinvested, net of annual

charges (including AMC of 0.5%), in GBP.

Insight Inflation-Linked Corporate Bond strategyRepresentative portfolio performance as at 31 March 2018


17.61%

-8

-4

0

4

8

12

16

20

Mar-13 Mar-14 Mar-15 Mar-16 Mar-17 Mar-18

Insight Inflation-Linked Corporate Bond RP


2013 2014 2015 2016 2017

Insight Inflation-Linked Corporate Bond RP - 4.24 -1.20 9.00 6.07



Insight Inflation-Linked Corporate Bond RP -1.27 -1.27 2.19 11.58 17.61 3.72 3.29

34

Source: Lipper. The representative portfolio adheres to the same investment approach as Insight’s Corporate Bond strategy. Performance calculated as total return, income reinvested, net of annual charges

(including AMC of 0.5%), in GBP.

Insight Corporate Bond strategyRepresentative portfolio performance as at 31 March 2018


12.51%

12.33%

-8

-4

0

4

8

12

16

Mar-15 Mar-16 Mar-17 Mar-18

Insight Corporate Bond RP Markit iBoxx Sterling Collateralized & Corp TR GBP


2013 2014 2015 2016 2017

Insight Corporate Bond RP - - -0.45 11.63 6.75

Markit iBoxx Sterling Collateralized & Corp TR GBP 1.59 12.46 0.45 11.73 4.91



Insight Corporate Bond RP -1.86 -1.86 2.23 12.51 - 4.00 -

Markit iBoxx Sterling Collateralized & Corp TR GBP -1.40 -1.40 1.37 12.33 30.14 3.95 5.41

35

Source: BNY Mellon Investment Management EMEA Ltd

Insight Short-Dated High Yield Bond strategyTarget market

Investor type:

Retail Y Professional Y Eligible counterparty Y

Knowledge and/or experience:

Basic investor Neutral Informed investor Y Advanced investor Y

Ability to bear losses:

No capital loss N Limited capital loss N No capital guarantee Y Loss beyond capital Neutral

Client objectives and needs:

Preservation Neutral Growth Neutral Income Y Hedging Neutral

Leveraged return profile Neutral Other Neutral

Time horizon:

Recommended holding period

(in years)- Very short-term (<1 year) - Short-term (<3 years) - Medium-term (<5 years)

Long-term (>5 years) - Neutral -

Distribution strategy:

Execution only BExecution with appropriateness

test or non-advised servicesB Investment advice B Portfolio management B

36


Insight Global Credit strategyTarget market

Investor type:



Basic investor Neutral Informed investor Y Advanced investor Y


No capital loss N Limited capital loss N No capital guarantee Y Loss beyond capital Neutral


Preservation Neutral Growth Neutral Income Y Hedging Neutral


Time horizon:







37


Absolute Insight Credit strategyTarget market

Investor type:



Basic investor Y Informed investor Y Advanced investor Y


No capital loss N Limited capital loss Null No capital guarantee Y Loss beyond capital Y


Preservation Null Growth Y Income Y Hedging Null

Leveraged return profile Null Other Null

Time horizon:







38


Insight Inflation-Linked Corporate Bond strategyTarget market

Investor type:





No capital loss N Limited capital loss Neutral No capital guarantee Y Loss beyond capital Neutral


Preservation Neutral Growth Y Income Y Hedging Neutral


Time horizon:







39


Insight Corporate Bond strategyTarget market

Investor type:





No capital loss N Limited capital loss Neutral No capital guarantee Y Loss beyond capital Neutral


Preservation Neutral Growth Y Income Y Hedging Neutral


Time horizon:







40

Important information

Important informationFor Professional Clients and, in Switzerland, for Qualified Investors only. This is a financial

promotion and is not investment advice.

Portfolio holdings are subject to change, for information only and are not investment recommendations.

BNY Mellon is the corporate brand of The Bank of New York Mellon Corporation and its subsidiaries.

BNY Mellon Investment Management EMEA Limited and any other BNY Mellon entity mentioned are all

ultimately owned by The Bank of New York Mellon Corporation.

Issued in the UK and Europe (excluding Switzerland) by BNY Mellon Investment Management EMEA

Limited, BNY Mellon Centre, 160 Queen Victoria Street, London EC4V 4LA. Registered in England No.

1118580. Authorised and regulated by the Financial Conduct Authority. Issued in Switzerland by BNY

Mellon Investments Switzerland GmbH, Talacker 29, CH-8001 Zürich, Switzerland. Authorised and

regulated by the FINMA.

PRE01603-014. Exp. 19 July 2018.

Past performance is not a guide to future performance.

The value of investments can fall. Investors may not get back the amount invested. Income from investments may

vary and is not guaranteed.

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