Digital Planet: Big Data, Small World - Amity Insight Ecclesiastical Investment Management Limited
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Ecclesiastical Investment Management Limited
Amity Insight
Digital Planet:
Big Data, Small World
This is for professional advisers only. This material is not
suitable for retail investors who should not rely upon it.
Welcome to the world Digital data and
of Big Data Big Data defined
By Thomas Fitzgerald, Investment Analyst, In computing, the term data refers to information (i.e. text,
Ecclesiastical Investment Management Limited images and sounds) that has been translated into a form that
can be stored and processed by a digital device, for the purpose
The first of this two-part Amity Insight, examined of electronic transmission, presentation and analysis.
the rapid way in which digital technology has become
embedded within our everyday lives, transforming
the way in which we create, communicate, buy, share
and search for information. The piece highlighted how
the proliferation of digital devices and the convergence
of communication and information technologies have
re-shaped existing industries and established new Unstructured Data
ones in the process. In Part II, we address the main The body of an email
by-product of a digitally driven world; the vast amount Comments on social networks
of digital data that is being generated by individuals Untagged audio, video and images
and organisations.
Thanks to smartphones, the videos we stream on
our tablets, the smart meters within our home and
the networked sensors implemented in automobiles
and industrial machinery, digital data is now universal.
This Insight explores how digital data has evolved from
traditional datasets into what has become known
as ‘Big Data’. We also examine the implications for
companies, individuals and policymakers as data is
increasingly used commercially to analyse human
behaviours. As responsible investors, we also ask
what are the emerging ethical challenges in this
Brave New World?
Data
Semi-Structured Data
GPS tracking information
XML (Webpages)
Why is data important?
n Structured Data: Organised in a highly manageable and ersonal Data is the new oil
P
mechanised form, residing in fixed fields such as a relational
database e.g. data within an Excel spreadsheet or indexed
of the internet and the new
fields within an email such as date, time, sender, recipient currency of the digital world
and subject. M. Kuneva, European Consumer Commissioner
n Semi-Structured Data: A hybrid of structured and
unstructured data as it does not conform to the formal
Digital data has always been an amalgamation of
structure of data models associated with databases and
information and communication technology, but as the
other forms of data tables, but contains tags and other
digital revolution has unfolded, technological innovations
markers to enforce hierarchies of records and fields within
have generated new forms and greater volumes of data.
the data. Examples include tracking information from GPS
This in turn has led to data being promoted from an
systems and XML (a file extension format used to create
ancillary position in business operations and market
and share information over the web).
transactions, to become an economic resource and
n Unstructured Data: In contrast, unstructured data a tradable commodity in its own right. Increasingly,
is raw and unorganised, meaning that it does not reside enterprises and government organisations are viewing
in a traditional database, which makes it more difficult for data as a source of significant value in terns of providing
computer systems to interpret. Examples include free-form insights and predictive capabilities.
text such as the body of an email, comments on social
Companies are utilising Big Data to build a competitive
networks and text within e-books and online articles
advantage in their business models, in order to understand
as well as untagged audio, images and video data.
the needs of consumers, more effectively target them
Big Data refers to streams of digital data that encompass and deliver goods and services in a more efficient manner2.
all the domains detailed above. The emergence of this key In other areas, governments and research institutions
theme in recent years reflects the continually evolving nature are mining vast datasets in order to solve complex
of data management technology in capturing, aggregating, behavioural, societal and public policy problems3.
storing and analysing vast amounts of data, in conjunction
with the rising demand for analytical insight1.
Structured Data
Indexed fields (dates & times)
Data within spreadsheets
Enterprise systems (CRM)
The current Big Data market size of
$12.6 billion is forecast to grow to
$32 billion by 20174.
1. McKinsey Global Institute, Big Data: The Next Frontier for Innovation, Competition 3. Klobucher, Derek, 2013, Big Data Opens Governments And Fosters Innovation,
and Productivity, June 2011, p.1 Forbes, February 2013, http://www.forbes.com/sites/sap/2013/02/13/
2. Morgan Stanley, Monetizing Any Data, Morgan Stanley Research, September 2012 big-data-opens-governments-and-fosters-innovation/
4. International Data Corporation
Amity Insight January 2015 3
The explosion in data generation
The growth of structured and unstructured data is rapidly accelerating, with the International Data Corporation (IDC) estimating
that annual digital data generation will reach 44,000 exabytes (or 44 trillion gigabytes) by 2020. If we were to store this data on
iPads and stack these face down on top of one another, the queue would stretch from the Earth’s surface to the Moon 6.6 times5.
This surge in data generation is predominantly derived from the rapid increase in semi-structured and unstructured data that is
being created. At present, an estimated 90% of all data is either semi-structured or unstructured6.
Annual Digital Data Creation, Replication and Consumption
50,000 44,000
Replicated and Consumed
Digital Data Created,
(Exabytes Annually)
40,000
30,000
20,000
7,910
10,000
130 1,227
0
2005 2010 2015E 2020E
The drivers of digital data growth
Three key drivers at the centre of the massive growth in digital data being generated and stored:
1. Increasing digitalisation
This driver refers to the dramatic expansion of new technologies,
Global Connected Devices by Type sensors and physical objects with digital processing and
transmission capabilities. The growth of digital devices that are
connected to the internet, capable of collecting and transmitting
25 greater amounts of data, is forecast to grow at a compounded
annual rate of 11% from 2013 through to the end of 20187. One
Number of Devices (Billions)
20 of the fastest growing elements of the digital world is machine-
to-machine connectivity (or the Internet of Things – see our
15
January 2015 SRI Expert Brief), which refers to the rapid
10 expansion of physical objects that have been digitalised, with
internet connection capabilities that enable these objects to
5
feed additional data into the system. In the case of
0 smartphones, tablets and laptops, these digital technologies
2013 2014E 2015E 2016E 2017E 2018E have the propensity to connect to online networks and services
Machine to Machine Smartphones where the data generated is predominantly unstructured.
Non-Smartphones TV PCs
Tablets Other Portable Devices
4 Amity Insight January 2015
2. Ubiquitous connectivity
There is not only a greater number of avenues in which an
Global Internet Protocol Traffic individual or an object can create digital data, but through
(Petabytes per Month) technologies such as wi-fi, Bluetooth and GPS as well as
upgrades and greater penetration in mobile and broadband
networks, the velocity in which this data is generated has
140,000 dramatically increased. Enhanced and continuous connectivity
through these innovations has fuelled a rapid increase in data
Global IP Traffic (Petabytes per Month)
120,000 traffic, with a large proportion of digital technologies now capable
of transmitting data in real-time. As a result, annual data traffic
100,000
over both fixed and mobile network connections increased
80,000 fivefold between 2009 and 2013, and Cisco estimates that over
the next five years, data traffic will grow at a compound annual
60,000 growth rate of 21% and this is heavily skewed in favour
40,000
of the consumer8.
20,000
0
2009 2018E
Business Consumer
3. L
ower data storage costs and computing advancements
There has been a stark divergence in trends between data
Average Selling Price Declines, storage costs and computing capabilities over the course of the
CAGR (%) 2006-2012 digital era. In the past 50 years, the cost of digital data storage
has been reduced by approximately half every two years, while
storage density (the quantity of information that can be stored in
Storage IP Core Routers a given space) has increased 50 million fold9. The declining cost
Servers (per Terabyte) (per Port) of data management and storage infrastructure is a result of the
0% commoditisation of hardware and technological innovations such
-5% as cloud-based infrastructure, which removes the immediate
-10% requirement for physical hardware. Simultaneously we have seen
-15% dramatic advancements in compression technologies and
-20% analytical software, which enable companies to manage the
-25% rapid growth in data volume more efficiently without increasing
-30% spend on storage at the same rate, while using analytical tools
Average Selling Price CAGR (%) that are more suited to their aims.
5. EMC, The Digital Universe of Opportunities, April 2014. Comparison based on iPad 8. Cisco, Cisco Visual Networking Index: Forecast and Methodology, 2013-2018,
Air 128 GB model June 10th 2014 http://www.cisco.com/c/en/us/solutions/collateral/service-
6. Cisco, 2013, Big Data: Not Just Big, But Different – Part 2, Cisco IT Insights Series, provider/ip-ngn-ip-next-generation-network/white_paper_c11-481360.html
April 2014 http://www.cisco.com/web/about/ciscoitatwork/enterprise-networks/ 9. Mayer-Schönberger, Viktor, Delete: The Virtue of Forgetting in the Digital Age,
docs/i-bd-04212014-not-just-big-different.pdf Princeton University Press, July 2005, p.63
7. Cisco Visual Networking Index, 2014, Cisco VNI Forecast: It’s not just about big
numbers, Cisco, June 2014, https://blogs.cisco.com/news/cisco-visual-networking-
index-vni-global-ip-traffic-and-service-adoption-forecast-update-2013-2018/
Amity Insight January 2015 5
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6 Amity Insight January 2015
Big Data
in practice Finance
A variety of technologies and analytical techniques As global financial infrastructures become more complex
are being deployed by organisations in every sector and illegal activities such as money laundering grow more
in order to capture value from these vast new datasets. sophisticated, Big Data has become a strategic imperative
This has resulted in a rapidly expanding market for Big for financial institutions in detecting criminal activities and
Data technology and services – a market which the complying with an increasingly rigorous regulatory environment.
International Data Corporation (IDC) forecasts to grow Real-time geo-location technology paired with historic consumer
from its current level of $12.6 billion to $32.4 billion transactions allows a bank to detect anomalies in financial
by 201711. To demonstrate how Big Data practices activity which may point to credit card theft. Big Data can also
are already creating value across the global economy, be a source of incremental revenue opportunities for these
we highlight industries that have already experienced firms, as insurance providers have already shown, by using data
a material impact. on consumer behaviour to suitably price and target insurance
products at specific consumers.
Utilities Big Data example: Visa and MasterCard
The use of Big Data analytics is predicted to have a dramatic
shift within the utilities sector, with companies being able to
track, visualise and predict both supply and demand. GTM
Research estimates that the annual expenditure on data
analytics by global utility companies will grow from $700 million Credit card companies are harnessing Big Data analytics
in 2012 to $3.8 billion in 202012. to combat fraud and create new revenue opportunities.
n Fraud Detection: Traditional databases and analytical
Big Data example: Suez Environnement models studied as little as 2% of transaction data, while
Big Data in conjunction with powerful algorithms and
underlying hardware and software analyses all data,
with systems now studying more than 500 aspects
of a single transaction at once versus 40 in 200513
– V
isa estimates new analytical platforms have
identified $2 billion in potential annual fraud
Suez Environnement is a French-based utility company
detection and mitigation activities
which operates in the water treatment and waste
management sectors. n Revenue opportunities: MasterCard and Visa along
with other credit card companies are mining data for
n The company has made ‘smart water’ one of its
marketers, retailers and banks, selling anonymous
priorities for its long-term strategy
transaction data to aid with targeted advertising
n The company has installed 1.8 million smart meters – M
asterCard revenue from ‘other’, the area that
and is aiming for 2 million by the end of 2014 includes the sale of data, grew 37% in Q3 2014
n Generated €350 million in revenues from ‘smart water’ to $460 mn
services in 2013
n Targeting 10% annual growth in ‘smart water’
10. IBM, Mayer-Schonberger, Racicati, Google; Apple; Netflix
per year through to 2016 11. IDC, New IDC Worldwide Big Data Technology and Services Forecast Shows Market
Expected to Grow to $32.4 Billion in 2017, December 2013, http://www.idc.com/
getdoc.jsp?containerId=prUS24542113
12. http://www.greentechmedia.com/research/report/the-soft-grid-2013
13. Rosenbush, Steve, 2013, Visa Says Big Data Identifies Billions of Dollars in Fraud,
The Wall Street Journal, 11 March 2013, http://blogs.wsj.com/cio/2013/03/11/
visa-says-big-data-identifies-billions-of-dollars-in-fraud
Amity Insight January 2015 7
Healthcare
Data in the healthcare sector is complex and highly fragmented. By digitally storing
more patient information, opening data systems and increasing the use of connected
‘smart’ medical devices, which wirelessly transmit health information on a real-time
basis, the healthcare sector stands to benefit through increased operational
efficiencies, more timely emergency care and greater informational resource for
research and development. McKinsey estimates that Big Data can help to unlock
over $300 billion per annum in additional value for the US healthcare system14.
$165bn
Clinical
Transparency in clinical
data and clinical
decision support
$108bn $5bn
Business Model
R&D
Aggregation of patient
Personalised medicine,
records, online platforms
clinical trial design
and shared datasets
$300bn
in the potential annual
value to healthcare
$9bn $47bn
Public Health Accounts
Public health surveillance Advanced fraud detection
and response systems and performance-based
drug pricing
Source: McKinsey Global
14. McKinsey Global Institute, Big Data: The Next Frontier for Innovation, Competition and Productivity, June 2011, p.43
15. Horizon Discovery, 2014, Corporate Overview, http://www.horizondiscovery.com/media/item/206
16. McKinsey Global Institute, Big Data: The Next Frontier for Innovation, Competition and Productivity, June 2011, p.64
17. Tesco, 2014, Annual Report and Financial Statements 2014, Tesco PLC, May 2014
8 Amity Insight January 2015Retail
Big Data and related analytical processes could increase
sector-wide productivity and drive profitability higher, with the
McKinsey Global Institute estimating that US retailers could
increase operating margins by more than 60% by 202016.
The integration of information technology and vast data
resources presents the opportunity for retailers to create
value via more effective product promotion and greater
leverage of the supply chain.
Big Data example: Horizon Discovery Big Data example: Tesco
Established in 2007 and a publicly traded company Tesco is the world’s third largest supermarket group by
since March 2014, the Cambridge-based firm is revenue behind Wal-Mart and Carrefour and has long
engaged in genomics research and the development been recognised as a pioneer of using Big Data,
of personalised medicines15. introducing its own loyalty scheme (Clubcard) in 1995.
n Most diseases carry certain genetic variations, which n The Clubcard loyalty scheme has enabled Tesco
pre-dispose individuals to the onset and progression to amass a huge amount of data on shoppers
of certain diseases as well as the clinical response to
– T
esco Clubcard has more than 16.5 million
therapy. Rapid declines in the cost of DNA sequencing
registered users17
driven by innovations in technology and more cost-
– E
nables the company to target promotions such
efficient methods of information storage have led to
as money-off coupons at relevant customers
the generation of vast amounts of data on the genetic
drivers of disease – O
ffers those it deems less risky based on shopping
habits, discounts of up to 40% on insurance products
n Horizon’s proprietary gene-editing platform GENESIS™,
has enabled the company to develop an extensive n Energy management system connects all 2,700+ UK
inventory of genetically defined cell-lines, which model stores to data analysis facility in India
anomalies found in human DNA that can cause disease – A
nalyst team tracks real-time data, monitoring categories
n These can be used to predict the clinical outcomes of such as lighting, refrigeration, heating and cooling
medicines targeted at patient populations with a specific – H
alf-hourly reports on energy consumption allow
genetic profile, allowing drug developers to implement team to identify irregularities in consumption
shorter, less costly and more targeted clinical trials – H
elped the group save £3.9 million on its energy bill
n Personalised medicine offers the promise of early in 2012
detection and diagnosis, more effective therapies n Predictive analytics driving reductions in wasted stock
and minimised side effects
– C
ombining data from weather records with sales
data, broken down by store and products
– U
ses data to predict future demand for product lines
on a per store basis according to weather forecasts
– S
aving £100 m per year in supply chain costs since
analytical programme was deployed
Amity Insight January 2015 9Big Data: Entering the ethical void
In Digital Planet we highlighted what we see as a suite of Companies will need to confront some
emerging ethical challenges faced by companies participating fundamental behavioural questions:
in the digital economy including:
n Is offline existence now deemed to be identical to online?
n Digital poverty
n Who should control access to data?
n Environmental impacts (emissions, conflict minerals,
water, electronic waste) n Who owns data, can its rights be transferred (and sold)
and what are the obligations of users?
n Cyber security and crime
n What is the impact for reputation when it (inevitably)
n Human rights and freedom on the Net
goes wrong?
These are all visible challenges arising from the Big Data
At the heart of this ethical debate is the consumer. A lack
information revolution – with one overriding proviso; we are now
of regulation and possibly unscrupulous use weigh heavily
entering an ethical void. Kord Davis in his pioneering research
in the context of poor consumer awareness and low value placed
‘Ethics of Big Data: Balancing Risk and Innovation’ 18 makes
on personal data. For instance, most users of social media are
the point that “there isn’t yet an ethical framework or common
careless of their own privacy – and yet companies such as
vocabulary for having productive discussions around the ethical
Facebook have encountered reputational challenges when
use of Big Data”. Whilst the received wisdom is that Big Data
consumers withdraw consent over arbitrary changes to privacy
will put power in the hands of consumers in a transformative
settings. Big Data profiling may also lead to discrimination,
way, undoubtedly its use – or misuse – will skew outcomes
victimisation or ‘minority reporting’. Examples (that may attract
for some consumers and as personal data becomes increasingly
public consent – or not) include data mining to detect benefit
public, companies will face critical ‘ethical crunch points’.
fraud, insurance pricing based on health and lifestyle profiling,
Regulation has not yet begun to contend with this; many
security services using data to detect behavioural abnormalities
corporate-taken decisions will rely on in-house ethical Codes
in a controlled sample, or the targeting of consumers with highly
of Conduct. The Financial Times predicts that 25% of
personalised offers, effecting a skewing of consumer behaviour.
organisations will face corporate reputational challenges
At one extreme, social media analytics could be used to ‘identify’
by as early as 201619.
mass shootings profiling based on ‘crunching’ social media posts,
background profiling, and age, gender and location data19.
Without Kord’s ‘ethical framework’ customer segmentation
may lead to discriminatory outcomes based on age, gender
and lifestyle. Organisations will need to evaluate the value of
knowing something given the potential ethical pitfalls arising
18. Ethics of Big Data: Balancing Risk and Innovation (2012) Kord Davis O’Reilly Media from a consequential course of action. Intent therefore becomes
ISBN 978-1449311797
19. Financial Times: Confronting the privacy and ethical risks of Big Data 24 September
the precursor to data analytics – why do we need to know
2013 www.ft.com NOT what do we want to know? The jury is out as to whether
20. Various sources, but see ‘Mass murder, shooting sprees and rampage violence:
research roundup September 2013 www.journalistsresource.org commercial imperatives will outweigh ethical due diligence.
10 Amity Insight January 2015Big Data: Emerging ethical challenges
Municipality/Government Insurance Company Embed
Principles
Code
Administers Benefits Assesses & Writes Risk
Big Data Code of Conduct
Principles of
Appropriateness
Ethical Checks
and Balances
Legal Implications
Customer Profiling
Analyses Social Media Reputational Risk
Dieting, Smoking,
for Fraud
Health, Social Media Intended Use Vs. Actual Use
Valuing data
The key to the future use of Big Data is appropriately valuing it.
This is still at a relatively early stage. We have shown several
examples of how data is being amassed and analysed by
companies – monetising this, against a backdrop of significant
ethical challenge, will be a key ongoing test. The surveillance
of consumers via profiling of social media and purchasing
habits is now routinely carried out in a largely unregulated way.
Companies, using highly sophisticated algorithms, can predict
and influence consumer behaviour, and so data has a value in
building brand and market share – Amazon’s ‘you may also like
these’ is a good example. However, the competition for data
and its sheer volume are driving down the market price for
personal information. Basic datasets (age, gender and location)
sell for as little as $0.0005 per person, whilst income and
buying habits are more valuable – but only marginally – at about
$0.001. The more detailed and intimate the dataset, the greater
the market value. For $0.26 per person, subscribers to
leadsplease.com can access specific health data including
medical conditions. However, for most individuals, the value
of all data is seldom worth more than $1 per person20.
20. Financial Times: How much is your personal data worth? June 2013
Amity Insight January 2015 11The Big Data value chain
The digitalisation of the physical world and the growing Typically, these industries are very competitive and rife with
importance of Big Data practices across numerous end- technological disruption, therefore, we believe those companies
markets create a number of opportunities and challenges for with substantial scale will be best positioned to monetise
investors. With the proliferation of digital data it is important opportunities. This will allow for greater integration into the
that investors focus on which companies hold the potential business models of end-users.
to create significant value from the data, rather than simply
the generation of data itself.
Semiconductors Hardware Networking
n Computing n PCs n 3G/4G spectrum
n Connectivity n Tablets n Wi-fi
n Memory n Smartphones n GPS
n Servers n Data centres
Data Capture Software/Services End-Users
n Search engines n Structuring data n Healthcare
n Social media n Organising data n Retail
n Cloud systems n Cloud software n Insurance
n Utilities
12 Amity Insight January 2015Amity case study: Cisco Systems
Founded in 1984 by A strong sustainability champion
two members of Stanford
Cisco Systems has been reporting its material sustainability
University’s computer support
challenges for a decade. Its key focus has been access to
staff, Cisco Systems has
education and connected healthcare – both strong Amity
become one of the world’s
pillars for positive screening. Harnessing the power of
largest technology companies, with a market capitalisation
network technology via its pioneering schools partnerships,
of over $132 billion and annual revenues of more than
Cisco Systems has actively closed the skills gap in some
$47 billion, sourced from a well-diversified customer base
of the most disadvantaged areas of the world, thereby
on both a geographical and end-market basis.
improving career chances and changing the cycle of poverty
The company has a long-established leadership in Internet and low achievement. Similarly, its collaborative approach to
Protocol-based networking equipment for data, voice healthcare has seen the innovative pioneering of healthcare
and video and also provides related networking services. outreach into rural regions and those devastated by natural
However, in recent years the company has faced a number disasters. Cisco too, has strong environmental management
of considerable challenges, having lost 25% of its market systems, achieving a 30% absolute reduction in Scope
value since 2007 in the face of an increasingly competitive I and II GHG (greenhouse gas) emissions worldwide from
threat from Asian peers with lower cost structures, as well a 2007 base line. The company has invested heavily in
as the emergence of disruptive technologies that could put energy efficiency ($9.6 million in 2014) and renewable
pressure on future revenue growth and profitability. energy as part of its pioneering Energy Ops Program,
which is investing a total of $50 million over four years
Nevertheless, with substantial scale and a commanding market in order to meet very challenging GHG reduction goals.
position in core product areas, we believe the company stands The company is rolling out state-of-the-art low-energy
to be a key beneficiary of the rising network infrastructure data centres that economise water and energy use,
investment that is required to support future growth in data employ LED exterior lighting and Low-E-glass windowing.
and connectivity. This is augmented by a series of investments Solar technology is helping deliver an estate that is at the
the company has made in recent years, providing new product cutting edge of low-energy building design.
and service categories which help it defend its position against
disruptive technologies and broaden its portfolio offering to
customers, from infrastructure through to analytics.
Amity Insight January 2015 13View from the top Over two successive Insights we have outlined how our world is changing from analogue to digital. We observed that at the heart of the digital economy there will be corporate winners and losers – our job as responsible investors is to understand where opportunity lies, whilst being ever cognisant of the evolving ethical landscape. Data is at the heart of the digital economy – its amassing, analysis, sale and use. We have shown how the pace of technological innovation and the speed of data generation are transforming our ability to understand – as never before – predictive human behaviours. Much of this will be genuinely useful – examples we have seen in healthcare and access to education will transform the life chances of some of the world’s most vulnerable people. But much of this is taking place in an ethical void, where regulation and legislation struggle to keep up. This places huge responsibility on companies to make moral choices about the use and sale of data – choices which as the FT suggests will lead to more and more reputational issues. Whilst our own view is fundamentally positive, we will, as responsible investors, continue to ask companies demanding questions about the control, ownership and use of data, pointing out the rising risk to reputation and loss of consumer consent. Neville White Head of SRI Policy & Research 14 Amity Insight January 2015
Why Ecclesiastical?
n he backing of an
T n pride in our independent analysis.
A n voidance of companies materially
A
award-winning team We’re not afraid to adopt contrarian involved in alcohol production,
positions and are in favour of long- gambling operations, pornographic
n ver 20 years of experience of
O
term investment horizons and violent material, tobacco
socially responsible investing (SRI)
production, testing animals for
n consideration of the preservation
A
n unds that are both positively
F cosmetic or household products,
of capital as our primary responsibility,
and negatively screened supporting oppressive regimes
preferring absolute returns over
stable investment team with
A or strategic weapon production
n
relative performance
a wealth of experience spanning n ctively seeking out companies with
A
n und Managers at Ecclesiastical
F
many years a record of involvement and good
are unconstrained by rigid stock lists,
comprehensive in-house
A performance in terms of business
n
permitting more flexibility to take
SRI research function practices, community relations,
advantage of good-value opportunities
corporate governance, education,
n n independent panel that reviews
A as they present themselves
environmental management,
investment decisions n ecision-making for the long term,
D healthcare, human rights, labour
n robust socially responsible
A as frequent trading increases costs relations and urban regeneration
investment process and decreases returns
Amity Insight January 2015 15Meet the team
Sue Round Andrew Jackson
Director of Investments and UK Equity Growth Fund Manager
Amity UK Fund Manager Andrew joined Ecclesiastical in 2003
Sue is the UK’s longest-serving retail SRI and manages the UK Equity Growth Fund.
Fund Manager. With the benefit of extensive His wealth of experience includes roles
experience, she has made the Amity UK Fund at Canada Life and Lloyds Investment
one of the leaders in the increasingly important Managers. Andrew is AAA-rated by Citywire.
socially responsible investment sector.
Robin Hepworth Neville White
Chief Investment Officer, Amity International Head of SRI Policy & Research
Fund Manager and co-manager of the Amity Before joining Ecclesiastical in 2010, Neville
Sterling Bond Fund was responsible for developing and managing
Robin has been with Ecclesiastical global corporate governance proxy voting with
for 27 years. He is recognised as one of CCLA Investment Management. Prior to this,
Citywire’s top 10 Fund Managers of the past he worked for the Church Commissioners,
decade and is also a Trustnet Alpha Manager, latterly as Secretary to the Church of England’s
placing him in the top 10% of all UK unit trust Ethical Investment Advisory Group.
and OEIC managers.
Chris Hiorns, CFA Ketan Patel, CFA
Amity European Fund Manager and Senior Socially Responsible
co-manager of the Amity Sterling Investment Analyst
Bond Fund Ketan began his career at JP Morgan in
Chris started working for Ecclesiastical in 1998. He moved to Clerical Medical (now
1996 and has been a CFA Charterholder Insight Investment) as an Equity Analyst.
since 2004. Ketan has worked for Ecclesiastical for
ten years and is a CFA Charterholder.
Peter Cameron CFA Thomas Fitzgerald
Assistant Fund Manager Investment Analyst
Peter joined Ecclesiastical as an Assistant Fund Thomas joined Ecclesiastical in 2011
Manager in 2014. Previously, he worked as an after completing a BSc in Economics and
Equity Analyst within the Quant Solutions Team Business Management at Oxford Brookes
at Aviva Investors. He also held positions within University. He supports the fund management
SRI, performance and portfolio risk at Aviva. team by providing detailed company research
He is a CFA Charterholder and has a BSc and analysis. Thomas is studying for the CFA.
in Mathematics and an MSc in Corporate
Governance & Ethics.
Please note that past performance is not a reliable indicator of future results and that the value of investments can fall as well as rise and you may get back less
than the amount invested. Source & Copyright: CITYWIRE, for the three years to 30 September 2014 based on risk-adjusted performance.
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Ecclesiastical Investment Management Limited (EIM) Reg. No. 2519319. This company is registered in England at Beaufort House, Brunswick Road, Gloucester, GL1 1JZ, UK. EIM is
authorised and regulated by the Financial Conduct Authority and is a member of the Financial Ombudsman Service and the Investment Management Association.You can also read
