Artificial Intelligence for Financial and Insurance Services in New Zealand - Ahumoni me te Inihua i te Atamai Iahiko
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Artificial Intelligence for
Financial and Insurance
Services in New Zealand
Ahumoni me te Inihua i te Atamai Iahiko
Financial and Insurance Services Partners
Other AI Forum of New Zealand Research Reports:
ARTIFICIAL INTELLIGENCE ARTIFICIAL INTELLIGENCE
Shaping a Future FOR HEALTH IN
New Zealand NEW ZEALAND
(May 2018) Hauora i te Atamai Iahiko
This report examines the New (October 2019)
Zealand and international AI The AI Forum’s latest research
industry landscapes, investigating report describes how AI promises
AI’s potential impacts on to bring significant clinical,
New Zealand’s economy and workforce and cost benefits
society. The report identifies to the health sector, as well as
key AI opportunities, in the personalise medical care. It can
public, private and education help with predicting disease and
sectors, that New Zealand can injury; and mine vast quantities of
invest in to actively shape the literature for research insights.
effects on our collective future.
TOWARDS OUR ARTIFICIAL INTELLIGENCE
INTELLIGENT FUTURE FOR AGRICULTURE IN
An AI Roadmap for NEW ZEALAND
New Zealand Ahuwhenua i te
Atamai Iahiko
TE ARA MŌ TĀTOU
(October 2019)
ATAMAI O ĀPŌPŌ
Te Huarahi Atamai This report examines the New
Iahiko ō Aotearoa Zealand and international AI
industry landscapes for agriculture
(September 2019)
and investigates AI’s potential
This report identifies that New impacts for New Zealand’s place
Zealand urgently needs to increase in the global food value chain.
its focus on the core foundations
needed to operate in an AI enabled
future – particularly investment,
skills and talent, research, trusted
data, ethics and regulation.
The report also shows how AI
enabled solutions can be used to
improve New Zealand's wellbeing,
productivity and sustainability.
Download our reports at
https://aiforum.org.nz/our-work/publications/
AI for Financial and Insurance Services in New Zealand 01
About the AI Forum of New Zealand
_INTRODUCTION
THE ARTIFICIAL INTELLIGENCE FORUM OF NEW ZEALAND IS A NON-
GOVERNMENT ASSOCIATION WITH A MISSION TO HARNESS THE
POTENTIAL OF ARTIFICIAL INTELLIGENCE (AI) TO HELP BRING ABOUT
A PROSPEROUS AND INCLUSIVE FUTURE NEW ZEALAND.
The rapid development of AI technologies presents major opportunities and challenges for our country:
from creating world leading AI businesses, nurturing a pool of talented AI engineers and applying AI
technologies to our agriculture, government, manufacturing and service industries to holding a meaningful
national debate on the broader implications for society, New Zealand needs to actively engage with
AI now in order to secure our future prosperity.
The Forum brings together citizens, business, academia and the government to connect, promote and
advance the AI ecosystem to help ensure a prosperous New Zealand.
Acknowledgments Partners
The AI Forum of New Zealand would like to The staff from our project partners and those who
acknowledge the following contributors: took time to provide reviews and feedback throughout
Monica Collier (IDC), Anna and Kelly Pendergrast the process.
(ANTISTATIC) for carrying out the research
Thank you to the many organisations that supported
Ratneesh Suri, Chris Dolman and Eric Yamashita (IAG) the research financially and by providing case studies.
for supporting the research and review
Please download a free digital copy of the e-report
Craig Bunyan, Megan Tapsell, and the whole team at
from the AI Forum website, www.aiforum.org.nz
ANZ for supporting the research and review.
Koren O’Brien for providing extensive knowledge of
the financial services sector and review.
Ben Reid, Emma Naji (AI Forum NZ) for editing
and review.
02 TOWARDS OUR INTELLIGENT FUTURE
Contents
About the AI Forum
of New Zealand................................... 01 Section 3 19
Acknowledgements..............................................01 Current State of AI Adoption
Partners....................................................................01
in the New Zealand Financial
AI Forum 2019 Research Project.....04
Services Industry
Foreword: IAG......................................05
Foreword: ANZ.....................................06 New Zealand Case Studies...................19
Executive Summary...........................07 Harmoney: fast, accurate risk assessment..................19
Key Highlights..................................... 10 ANZ: personalised, life-like customer service
at scale................................................................................ 20
BNZ: detecting fraud in real time................................... 21
Kiwi Wealth: robo-advice to help with savings goals..... 21
PART A 11 ANZ: voice-driven biometrics......................................... 22
AI for Financial Services
Section 4 23
Section 1 12
Challenges and Barriers
to AI Adoption
Financial Services and Banking
Regulatory Challenges......................... 23
Skills and Talent................................... 23
Context..................................................12
The New Zealand Financial Services Sector............... 12 Industry Investment............................. 24
What Makes New Zealand’s Financial Organisational Challenges.................. 25
Services Sector Unique?.................................................. 12
Existing Workforce Fears..................... 25
Recent Changes in the Sector: Social Licence and Trust...................... 25
The FinTech Boom.................................12
Section 2 15 Section 5 26
Future Trends and Opportunities
Use Cases – How AI Can
Enhance the Financial
Services Sector
Section 6 28
Accelerating AI Adoption
A Sector Primed for AI..........................15 in Financial Services
AI Benefits for the Sector.....................16
AI for Financial and Insurance Services in New Zealand 03
_INTRODUCTION
Recommendations for New Zealand Tower Insurance and Ambit............................................ 37
Financial Services Organisations to Cove..................................................................................... 37
Accelerate AI Uptake........................... 28
Accuro and Intelligent Life.............................................. 37
Government-supported Industry Strategy.................. 28
Increasing Export of AI-Driven Services..................... 28
Working Together............................................................. 28
Conclusion............................................ 28
Section 2 38
Transformational Use
Cases for Insurance
PART B 29
Section 3 40
AI for Insurance Services
Nature and Scale of Impact
Section 1 30 – Insurers of the Future
Current State of AI in Insurance
Future Trends....................................... 40
AI Adoption in New Zealand................ 30
Trends in the Insurance Sector
Driving AI Adoption.............................. 31 Section 4 42
How AI is Helping................................. 32 Accelerating AI Adoption in
State of AI Adoption in the Insurance the NZ Insurance Sector
Industry................................................. 33
Insurance and AI Globally............................................... 33 Challenges and Barriers to AI Adoption
International Case Studies.............................................. 33 in Insurance.......................................... 42
Anthem Inc...............................................................................33
Overcoming the Challenges................ 44
AXA and Expert System – Document Analysis.........33
Nationwide and Lytx, DriveCam solution, Recommendations for New Zealand Organisations
commercial insurance..........................................................33 to Accelerate AI Uptake.................................................. 44
Cigna and Amazon, "Answers by Cigna".....................33 Strategy.....................................................................................44
AllState ABIe...........................................................................34 People and Culture...............................................................45
Flamingo Ai..............................................................................34 Process / Partners.................................................................45
Zurich and Spixii....................................................................34 Data............................................................................................45
Riskgenius................................................................................34
Conclusion............................................ 45
Insurance and AI In New Zealand........ 34 The Research Team.............................. 46
Insurtech............................................................................. 36
References.............................................47
New Zealand Case Studies.................. 36
Southern Cross and UneeQ........................................... 36
JRNY.................................................................................... 36
04 TOWARDS OUR INTELLIGENT FUTURE AI Forum 2019 Research Programme AI FOR FINANCIAL AND INSURANCE SERVICES IN NEW ZEALAND AHUMONI ME TE INIHUA I TE ATAMAI IAHIKO Ō AOTEAROA The AI Forum of New Zealand would like to extend our sincere gratitude for the generosity of all the Programme Partners and Supporters who have made this report possible. Principal Partners Banking Sector Partner Insurance Sector Partner Financial Services Research Partner Insurance Services Research Partner
AI for Financial and Insurance Services in New Zealand 05
_INTRODUCTION
06 TOWARDS OUR INTELLIGENT FUTURE Foreword ANZ ANZ IS PROUD TO BE ASSOCIATED WITH THE NZAI FORUM AND THE INTELLIGENT FUTURES RESEARCH REPORT TO RAISE AWARENESS OF THE OPPORTUNITIES AND CHALLENGES FOR INDUSTRY ADOPTION. We increasingly see the evolution of technology playing a critical part in helping us be successful in achieving our purpose at ANZ – helping shape a world where people and communities thrive. New Zealand and specifically the financial sector has a proud history of innovation and adoption of new technologies and the speed at which they are becoming available Craig Bunyan, to us emphasises the importance of focusing on GM Technology New Zealand the practical adoption of AI implementation. ANZ If we are to compete in a global market it is essential to accelerate our implementation of AI solutions and take ownership of growing New Zealand’s AI capability, investing in AI training to grow our talent pool and further strengthen our innovative abilities. Advanced data capabilities are in hot demand as is the ability to invent new business models to take advantage of such capabilities. There are foundational capabilities like Cloud already on the market to assist a more rapid adoption and whilst financial disruptors, such as the Fintech revolution, have had little impact on the New Zealand financial sector to date, with open banking on the horizon Fintech’s and new AI technologies will change the way we not only provide services but significantly change our service model. We have a real opportunity to embrace AI technologies for the benefit of all and this requires a high-level understanding of AI technology and AI expertise. The report that the AI Forum New Zealand has produced is a cornerstone for New Zealand in helping guide us to AI future we are trying to build. Ngā Mihi
AI for Financial and Insurance Services in New Zealand 07
Executive Summary
_INTRODUCTION
Financial and Insurance Services Blockchain and Distributed Ledger Technology
(DLT), Cryptocurrencies, Application Programming
– Sectors Primed for AI Interfaces (APIs), and Peer-to-Peer (P2P) digital
The New Zealand financial services and insurance platforms.1 AI will often be used alongside these
sectors are undergoing a period of significant other technologies to enable the transformation
change. Customer and partner expectations are of banking services. Change is happening in both
changing. There are technology innovations, in the front and back offices of incumbents as
regulatory demands, and sociopolitical and well as through an increase of new services by
economic disruptions. It is a challenging time start-ups and emerging players in the market.
for the sector and digitisation is a key trend
banks and insurers must address. Challengers, AI FOR FINANCIAL SERVICES
offering new business models, are pushing on
AI for financial services is a major opportunity
to the financial and insurance services scene.
area for New Zealand, driven by the country’s
The AI Forum NZ’s 2019 report Towards Our relative openness to new technology and digital
Intelligent Future: An AI Roadmap For New Zealand innovation. Despite regulatory hurdles and
identified that increasing computing power, challenges around hiring and industry maturity,
increased accessibility to mass data, and growing AI-enabled improvements at legacy banks and
interest in conversational based digital interfaces FinTech startups alike are already proving valuable
mean there is growing interest in AI as a business and creating relatively rapid returns on investment.
solution. AI promises to provide those businesses The future of AI in the financial services
that have embraced digitisation with a new tool to sector is tied up with wider trends. The
leverage data and drive productivity, efficiency and industry is already undergoing major changes
innovation. Economic modeling in the AI Forum’s and disruption, with some commentators
2018 report Artificial Intelligence: Shaping a Future believing that this is just the beginning of
New Zealand singled out Financial and Insurance significant changes to the way we bank.
Services as having the largest potential economic
benefits from AI-driven labour efficiencies of There are many opportunities for AI to change
any sector, delivering up to $6.4Bn in 2035. the face of financial services in the future. Many
companies are already experimenting with the
AI is a catch-all term for a range of automation possibilities all across banking operations:
technologies that most often use “machine
• Automated customer service agents that aid
learning” to make predictions and automate
in understanding customers' needs, reducing
decisions using data. We include within our
time and resources spent in resolution.
definition a range of computational techniques
which can be applied to problems in healthcare • Robo-advisors that provide automated,
including: robotic process automation, often AI-driven financial planning services
computer vision, natural language processing, and individualised investment plans for
reinforcement learning and generalised deep customers with little to no human interaction.
learning. For a fuller explanation of AI and • AI fraud detection that uses deep
machine learning, see the AI Forum's recent learning techniques to more quickly
report Towards Our Intelligent Future. and accurately detect fraud.
It is important to note that AI, and more specifically • AI market abuse detection to spot
machine learning, is just one of the sets of abnormal behaviour to detect market
emerging technologies that are enabling the abuse and rogue trading.
growing Kiwi FinTech and InsurTech ecosystem. • Robotic process automation for automating
Other key technologies and advances include ledger reconciliations and other processes.
08 TOWARDS OUR INTELLIGENT FUTURE
• IT automation that links systems to become more customer centric to remain competitive
self-acting and self-regulating, automating and relevant. The industry must transform from
mundane software maintenance activities. a product-centric mindset to a customer-centric
• Advice and recommendation systems mindset. Companies should look to deliver
to match a consumer's needs with the contextual and personalised sales and service
correct banking or finance product. through customers' channels of choice.
• Automated threat intelligence and The digital mission in the insurance industry
prevention systems to identify threat to is to create simple, transparent, and unique
databases, websites and other systems. experiences. Digital technologies and the power
• Intelligent processing automation of data and analytics enable this transformation.
that automates processes previously
AI can enable change and disruption across
carried out by knowledge workers.
the insurer's enterprise. It can deliver product
• Robo-regulators that use machine-readable recommendations and automate the application
and machine-executable rule handbooks process. AI solutions can improve risk assessment
to interpret and implement regulation. accuracy and automate underwriting. AI can
Corporate investment in AI is beginning to pay automate the claims process. This same
off for some large Australian and New Zealand technology can assist insurers to identify
banks who are early adopters. For example, claims fraud. Cross-industry use cases play
ANZ New Zealand’s parent announced its well into the insurance sector. For example,
half year results and told shareholders that AI for customer service, process automation,
a highlight was improvements it made in IT automation and threat intelligence.
automation in its institutional business, through AI assists customers to research, buy, manage,
robotics and machine learning. ANZ said it renew and claim on their policies at a time
has reduced turnaround times by up to 40 and place that suits them. This is increasingly
percent in trade, credit and customer service. important as the digital native generation reach
However, growing adoption is facing challenges an age where insurance becomes a priority.
with a limited pool of local machine learning and AI By leveraging machine learning, insurers are
talent to design and implement the technologies. finding they can gain a competitive edge over
their competitors by developing real time actions
AI FOR INSURANCE SERVICES based on behavioural and demographic data.
AI is one of the most disruptive forces for the In New Zealand insurers are focussing on their
insurance trade today. The recent intense interest digital experience. There is growing interest in how
in AI is a result of factors such as increasing AI can solve business problems. Some incumbents
computing power, increased accessibility to mass are identifying use cases and experimenting with
data, and burgeoning interest in conversational small scale AI pilots and proofs-of-concepts. These
based digital interfaces.The manual, transactional are siloed, tactical deployments, solving a discrete
nature of insurance means high potential business problem. The deployments are usually
for benefits of automation and precision. not yet part of the overall enterprise strategy.
There is an evolution towards autonomous Some New Zealand insurers are already
vehicles, connected vehicles and homes, sharing deploying scaled AI solutions. Tower Insurance
and on-demand economies, and peer-to-peer has a conversational AI chatbot that answers car
insurance models. These changes are adding a insurance claims queries. Southern Cross has
new dimension to the competitive landscape. recently launched a digital assistant called Aimee,
to help consumers understand health insurance.
Insurers need to reinvent and redefine their
business to respond to the changing marketplace. A recent report by EY New Zealand and
Insurers face pressure to cut costs and become InsurTechNZ illustrates the rapid growth in theAI for Financial and Insurance Services in New Zealand 09
_INTRODUCTION
number of InsurTech companies in New Zealand. 2 To increase the rate of AI adoption insurers need
These startups deliver technology solutions for an executable single strategy that incorporates
insurers or offer tech-based insurance products AI. Culture shifts need to come from the top down
themselves. For example, Cove Insurance offers as well as the bottom up. Insurers must foster
chatbot style policy applications for car and a culture of experimentation and innovation,
phone insurance. JRNY and Ambit offer insurance that is comfortable with failure. Engagement
focused conversational AI. IntelligentLife provides needs a multipronged approach as employees
an AI powered underwriting solution. Cove is a attitudes towards AI will differ depending on
potential alternative and challenger proposition to their role and experiences. Insurers should
incumbents. JRNY, Ambit and IntelligentLife offer seek to partner and collaborate with the vendor
AI based solutions to the insurance industry. community. The industry needs a connected
ecosystem with diverse stakeholders including
New Zealand organisations say the biggest InsurTechs. These parties must collaborate to
AI adoption barriers are cost and concerns bring innovative new solutions into the industry.
about governance and regulatory implications.
As we explain in the Towards Our Intelligent
Future report, data is the core foundation Call to action
of AI solutions. For financial institutions,
This report recommends that:
governance, regulatory matters and compliance
lead to challenges deploying AI. Enabling • Government accelerate its industry
AI data to be secure by design but usable transformation plans and consider a
at scale can be a barrier to adoption. specific government-supported focus on
the future of the financial services sector,
Within the insurance industry, conservatism including the role that AI has to play.
can be a barrier to engaging key stakeholders.
There is industry concern that implementing • New Zealand FinTech companies focus on
new AI based solutions could lead to a loss of developing and exporting AI-driven financial
consumer trust. Anecdotally, there is a lack of services products to large markets like the
willingness to experiment, or be comfortable UK where there is larger sales potential.
with failure. Insurers may fall back into known • Large banks and insurers should seek to
patterns they believe are secure and compliant partner with the local Fintech and Insurtech
and will bring returns. There's a lack of leadership vendor community to foster AI innovation.
roles in AI. A single team may own AI and will
• Financial sector organisations seize the
struggle to gain enterprise-wide engagement.
opportunity to work together across the ecosystem
A lack of industry collaboration is another (including regulators) on collective solutions
barrier. Incumbents and InsurTechs need closer to shared problems – for example anti-money
collaboration to produce appropriate innovative laundering controls and fraud prevention.
AI solutions. This is a challenge for a sector that
• There is an increase in New Zealand investment in
is in the early stages of learning how to operate
AI research for financial and insurance use cases.
in a collaborative ecosystem environment.
• Financial organisations focus on talent
Despite the barriers, research firm IDC expects development, including technical and AI
global spending on all AI systems to increase savvy management.
by over 30% (CAGR) by 2022 to US$75
billion. AI adoption is increasing across all With increased levels of investment and
sectors. Banking and retail sectors lead. effective regulation, AI-driven innovation can
help make the New Zealand financial and
Within the global insurance sector, AI- insurance services sectors become more
penetration is at early stages and
nimble, customer driven, and effective.
increasing. IDC estimates spending within
the insurance sector to triple by 2023.10 TOWARDS OUR INTELLIGENT FUTURE
Key Highlights
FINANCIAL AND INSURANCE SERVICES SECTOR HAS THE
LARGEST PREDICTED ECONOMIC BENEFITS FROM AI-DRIVEN LABOUR
EFFICIENCIES. UP TO $6.4B IN 2035.
Trends within the Insurance
Sector Driving AI Adoption:
AI WILL BE CRITICAL FOR
COMPETITIVE ADVANTAGE: Agree 52.5%
• Shared Economy
• Cybersecurity The ability DESPITE REGULATORY
• On-Demand Economy for financial HURDLES AND
• Automation institutions in CHALLENGES, AI-ENABLED
IMPROVEMENTS AT
• Autonomous / New Zealand to
LEGACY BANKS AND
Semi-Autonomous Vehicles quickly adopt AI FINTECH STARTUPS ALIKE
is limited in part ARE ALREADY PROVING
by the shortage VALUABLE AND CREATING
New Zealand of skilled workers. RETURNS ON INVESTMENT.
FinTech
companies must focus on Reccomendations to accelerate AI adoption:
developing and exporting • Create a government-supported industry AI strategy
AI-driven • Increasing export of ai-driven services
• More collaboration
financial services • Enabling experimentation friendly culture
products to large markets with
larger sales opportunities.
AI should be an organisational AI NEEDS GOOD
capability, rather than DATA. BANKS
With a strong history of analytics, HAVE HUGE
something the "AI
the financial sector is better REPOSITORIES
department" comes up with.
prepared to incorporate and reap OF GOOD DATA,
rewards from AI implementation. BUT MOST
INCUMBENT
Great potential exists for BANKS TEND TO
Spending on AI in insurance is set businesses to leverage AI HAVE SILOED
to triple by 2023. New Zealand to respond to the changing DATA ASSETS
businesses can increase their rate marketplace and become more THAT ARE
of AI adoption by formulating an customer centric to remain NOT EASILY
executable AI strategy. competitive and relevant. ACCESSIBLE.
BANKS AND INSURERS SHOULD PARTNER WITH LOCAL FINTECH AND INSURTECH
CREATORS TO FOSTER AI INNOVATION IN NEW ZEALAND.AI for Financial and Insurance Services in New Zealand 11
_PART A: AI FOR FINANCIAL SERVICES
PART A:
AI for Financial Services12 TOWARDS OUR INTELLIGENT FUTURE
Section 1: Financial Services and Banking
Context employed in the finance and insurance sector in
2017, with an expected increase to 76,000 in 2020.6
This is an exciting and uncertain moment for the As of April 2018 there were 26 registered banks in
financial services sector, with technological shifts New Zealand, 15 of which are incorporated in New
creating new opportunities and new challenges, Zealand, the remaining 11 are international banks
especially for incumbent banks. Gartner has with branches in New Zealand.7 The overall financial
predicted that at the current rate of change, up to services sector (including insurance) contributed
80 percent of traditional banks risk going out of $13.4 billion to GDP in the year ending March 2017.8
business or becoming uncompetitive by 2030. 3
From AI to cryptocurrency, new financial WHAT MAKES NEW ZEALAND’S FINANCIAL
technology is driving change in the pursuit of SERVICES SECTOR UNIQUE?
simplicity, efficiency, better services, competition, As a geographically isolated, developed nation
and social wellbeing. Banks and other financial with a small population and internationally high
institutions that understand the current landscape levels of technological uptake, New Zealand is
and the opportunities that AI presents will be often seen as a perfect testing ground for new
best equipped to capitalise on this new wave. technologies. New Zealand’s early-adopter status
is frequently illustrated with the early success and
Given these changes, it is clear that financial
wide uptake of EFTPOS, which was introduced
institutions will need to continue to adapt and
in the mid-1980s.9 Since then, many major
change if they are to thrive in an increasingly digital
companies including Facebook and Google have
world and a changing marketplace. We expect to
used New Zealand to test out products before
see banks apply an increasingly diverse range of
launching more widely in order to minimise risk
AI-enabled tools to a broader array of services,
and indicate the product’s chance of success.10
unleashing efficiency gains4 and customer-focused
improvements. The New Zealand context provides New Zealand has relatively high uptake of
a specific set of challenges regarding scale, digital banking, with the World Bank reporting
regulation, and social context, but with appropriate in 2015 that 83 percent of New Zealand adults
investment and a focus on increasing the AI- were using electronic payment methods (e.g.
readiness of the sector, New Zealand financial electronic cards and internet banking). This
services legacy institutions and startups alike will made New Zealand the fourth most intensive
be poised to take advantage of the benefits of AI. electronic payment user out of 164 countries.11
THE NEW ZEALAND FINANCIAL SERVICES SECTOR Recent Changes in the
In New Zealand, the meaning of financial services is Sector: the FinTech Boom
set out in section 5 of the Financial Service Providers
Traditionally it has been difficult for new businesses
(Registration and Dispute Resolution) Act 2008.5
to break into the financial services industry. Large,
The sector is broad, and covers a range of services
established institutions had advantages of size,
including: banks, financial advisory services, credit card
large client bases, and the ability to manage ever-
issuers, money exchangers, investment brokers, and
increasing regulation.12 However, there has been
insurance companies. In Part B of this report we will
considerable innovation in the financial services
cover applications of AI specific to the insurance sector.
sector over the past two decades, coming in the
The financial services industry is a major employer form of fast-moving companies — often startups
and economic driver in New Zealand. To give an idea – focused on a single and specific technology or
of the size of the sector, the Ministry of Business, process, be it mobile payments or insurance.13
Innovation and Employment’s 2018 short-term Examples include Alipay, the world’s largest
labour market estimates showed 70,900 people mobile payments platform which offers a range ofAI for Financial and Insurance Services in New Zealand 13
_FINANCIAL SERVICES AND BANKING
functionality from bus pass purchasing to peer- a growing push towards personalised, contextual,
to-peer payments; TransferWise, which offers and customer-centric products and services.
low-fees transfers of payments internationally; and FinTech, which includes big data solutions and AI,
others such as Ant Financial and WeChat Pay. is part of the solution to these changing needs.
These new companies are part of a wider boom Trending changes in the financial services
in FinTech. FinTech is defined as “technology- landscape include:
enabled innovation in financial services that could • Cryptocurrencies: digital or virtual currencies
result in new business models, applications, that operate independently of a central bank or
processes or products with associated material authority, where every transaction is encrypted
effect on provision of financial services.” 14 The and verifiable. This independence is usually
FinTech industry is broad, and includes established
enabled by blockchain, which provides a sense
banks offering technology-enabled solutions
of “digital trust” between parties. Bitcoin is
for their customers as well as a large number of
perhaps the most ‘famous’ cryptocurrency, with
startups and global technology companies.
others including Ripple, Ethereum and Tether.
In a 2016 environmental scan, McKinsey found • In June 2019, Facebook announced a new
over 2000 FinTech startups in the space, up from cryptocurrency protocol called Libra, which is
800 in 2015.15 Global FinTech investments reached slated for likely launch in 2020.19 In addition
US$12 billion in 2014.16 These new companies to Facebook, a range of other companies and
are eroding traditional services and creating new venture capital firms are investing in Libra, and
marketplaces, thriving on new technologies and will be members of the currency’s governing
innovative approaches to traditional products body, the Libra Association. 20 Libra differs from
and services.17 In its report Financial Services other cryptocurrencies in that it was designed
Technology 2020 and Beyond: Embracing to be global and scalable. Unlike Bitcoin,
disruption, PwC noted that “successful disruptors Libra is a centralised protocol. It is also asset-
typically offer a better customer experience and backed, so will likely stay relatively stable to
greater convenience at a much lower price.” 18 local currencies. 21 Fees are likely to be low
However, startups and digital native companies for users, and founding members of the Libra
aren’t the only groups making the most of the Association will make a profit through the interest
FinTech boom. FinTech has been incorporated by earned on the balance of users’ accounts.
financial service providers for decades in ways • Blockchain: a digital record keeping system for
most people may take for granted. Examples of trades and transactions, in which an ever-growing
adoption are plentiful – credit cards, Automatic list of records is stored simultaneously on lots
Teller Machines (ATMs), the Society for Worldwide of computers in a network — it is not controlled
Financial Telecommunication (SWIFT), electronic by any one person or company. Every record is
trading, mainframes, online banking, applications connected to the one before it and the one after
and mobile wallets. Adoption of FinTech has it, so once an entry is added it can’t be altered.
seen banks — including the Big Four in New It’s often discussed in the same breath as Bitcoin
Zealand (ANZ, BNZ, ASB, Westpac) — not just or other cryptocurrencies, but there are many
remain relevant, but thrive. However, new digital- more applications in the finance sector, including
native startups that incorporate AI and other enabling financial transactions to automate
innovations from the ground up do threaten to contractual agreements. In 2015, 13 blockchain
eclipse incumbent banks in some areas, with companies obtained over $365 million in funding. 22
user-focused interfaces and new services that
• Social Payments: banking through social media,
are attracting customers at an increasing rate.
peer-to-peer (P2P) lending or the development
As older models of differentiation — like speed and of online financial communities. The trend
cost — for financial institutions are eroding, there is was first popularized by PayPal, and other14 TOWARDS OUR INTELLIGENT FUTURE
• companies have since developed their own of new startups, companies, and incubators
versions, including Venmo, Snapcash, Google have emerged, supporting and accelerating the
Wallet, Apple Pay and Twitter Buy. These types diffusion of AI and other FinTech applications.
of banking are often seen as part of a growing
democratisation of finance, with startups and
FinTech companies helping solve problems that DIGITAL INCLUSION FOR BANKING SERVICES
the traditional banking system are less willing
or able to deal with. Facebook Calibra, a digital As more New Zealanders go online to do
wallet for using the (yet to be launched) Libra their banking, there has been an increase in
digital currency that will likely be integrated with physical bank branch closures, especially in the
its products such as Messenger and WhatsApp. regions. Stephen Parry, national finance sector
organiser for First Union told the NZ Herald
• Open Banking: involves making internal bank
in August 2018 that "Over the last two years
data and processes available to external parties
alone we have seen nearly 50 branch closures
via digital channels, such as APIs. Open Banking
across ANZ, BNZ and Westpac. There has also
operates on the premise that customers, rather
been a trend towards reducing staffing levels
than banks, own their data, and should be free
and opening hours, most recently at BNZ."27
to share it with external parties as they wish. 23
• In early 2018, the UK introduced the Second Despite overall high levels of digital capability,
not all New Zealanders have the skills, or access
Payment Services Directive (PSD2), which
to technology needed to do their banking online.
requires the UK’s largest nine banks to release
The Government’s Digital Inclusion Blueprint, Te
data in a secure, standardised fashion (with the
Mahere mō te Whakaurunga Matihiko, released
customer’s consent). In Australia, banking is
in May 2019, noted that there are a range of
the first sector to be covered by the Consumer
groups who are at increased risk of digital
Data Right, which aims to make it easier
exclusion including seniors and people living
for customers to share their data between
in rural areas. 28 As banks become increasingly
organisations. The first phase of open banking
digital and continue to incorporate AI, it will be
was launched on 1 July 2019, with customer
important to ramp up education and inclusion
banking information required to be made available
efforts to ensure all New Zealanders are equipped
by the “big four banks” from February 2020. 24
to engage with new banking technologies.
• New Zealand is currently taking an industry-
led approach to open banking. Hon Kris Faafoi,
Minister of Commerce and Consumer Affairs has
indicated that while regulation for open banking is
not off the table in the long-term he is “genuinely
focused on giving industry-led open banking a real
chance to succeed.”25 In May 2019, Payments NZ
— the industry-owned organisation that governs
New Zealand’s payment system — opened its
API Centre, which will lead the development and
agreement of common API standards across the
banking sector. This will mean that third parties
do not need to make a bespoke solution for
each API provider it wants to connect with. 26
Many of these trends and changes are being
incorporated into the operations of legacy
finance institutions. In addition, a broad rangeAI for Financial and Insurance Services in New Zealand 15
Section 2: Use Cases – How AI Can
Enhance the Financial Services Sector
_USE CASES - HOW AI CAN ENHANCE THE FINANCIAL SERVICES SECTOR
A Sector Primed for AI to match products and services. Chatbots, such
as Bank of America’s Erica, use AI to optimize
The finance sector is already primed for AI. the user’s experience. This tool helps customers
Creating and maintaining accurate data is check balances, offers bill reminders, and
mission critical for financial service providers, answers banking-related questions. IDC expects
so the large digital data sets and robust data investment companies to increasingly use
management systems required by many AI machine learning for real-time trading decisions.
applications tend to be an existing asset at banks,
going back many tens of years in some cases. However, AI is just one set of technologies that
make up the wider FinTech trend, and it can’t
Banks and other financial organisations have been be extracted from the wider shift to digitisation
using complex analytics and predictive models for and explosion of FinTech. The elements that
decades to predict risk, assess credit, and make AI is dependent on — from well-managed big
investment decisions. These attributes mean that, data to massive computing capacity — are
compared with many other industries, the financial already integral to the shifts currently happening
sector is likely better prepared to incorporate in finance, both at large banks and smaller
and reap rewards from AI implementation. providers. So, while this section covers the way
Unsurprisingly, financial institutions have been that AI can benefit the finance sector, it can be
quick to capitalise on the promise of AI. Outside hard to parse out the effects of AI from the rest
the tech industry, the financial services sector is a of the changes in the finance ecosystem. As a
leading early adopter of AI in terms of spending. 29 recent report from the World Economic Forum
Financial services and retail were among the first and Deloitte states, “focus on AI alone is not
industries worldwide to adopt AI systems. Industry sufficient to understand the myriad ways in which
analyst IDC expects these industries to continue it could be used within financial institutions”. 30
representing more than a quarter of AI spending. In the AI Forum’s 2018 report Artificial Intelligence:
Within financial services, banks are using AI to Shaping a Future New Zealand, economic
enable next-generation client experience. These modeling singled out the Financial and Insurance
systems’ ability to extract information and insight Services sector as having the largest potential
from enterprise documents is maturing. Banks economic benefits from AI-driven labour
pair this insight with recommendation systems efficiencies, delivering up to $6.4Bn in 2035.16 TOWARDS OUR INTELLIGENT FUTURE
FIGURE 1: Estimated Ranges of Economic Benefits of Labour Efficiencies from AI in New Zealand
Industries in 2035
2015 $b
Financial and insurance services 2.6 6.4
Manufacturing 2.6 6.3
Construction 2.4 5.8
Professional, scientific and technical services 2.2 5.0
Health care and social assistance 1.6 3.6
Retail trade 1.5 3.7
Wholesale trade 1.4 3.4
Transport, postal, and warehousing 1.4 3.3
Administrative and support services 1.0 2.3
Rental, hiring and real estate services 1.0 2.2
Education and training 0.9 2.0
Accommodation and food services 0.8 2.0
Arts and recreation services 0.8 2.0
Information media and telecommunications 0.6 1.5
Electricity, gas, water and waste fishing 0.6 1.5
Agriculture, forestry and fishing 0.5 1.2
Other services 0.4 0.9
Mining 0.1 0.3
0 2 4 6 8
SOURCE: Sapere and Schiff Analysis, 2018
AI Benefits for the Sector Intelligent Future report. In the financial services
context, The US Federal Reserve notes that there
The financial services sector needs to continue is particular interest in at least five AI capabilities in
creating customer-centric services that anticipate the banking sector. 31 Citigroup notes six capability
user needs, allow customers to bank in a way areas, and identifies three areas of the sector in
that suits them — including on the go with mobile which AI can provide value: customer engagement,
devices and touchless payment — and reduces operations, and risk and compliance. 32
risk and fraud. Digital transformation, FinTech,
• In customer engagement, AI can help banks
and data analysis play a big part of this necessary
better serve customers by providing data-driven
evolution. To achieve continued growth and
insights into user behavior, allowing them to
align to the changing expectations of customers,
provide custom recommendations. Chatbots
partners, and markets, the industry needs to
and other AI-enabled customer service tools
continue to invest in technology solutions.
can help banks to answer customer queries
AI has already been revealed as a critical part more effectively and efficiently, while potentially
of this improvement and transformation. AI is a cutting costs by automating some elements
catch-all term for a range of technologies that of customer service. 33 AI allows banks to offer
most often use “machine learning” to make robo-advisers for investment accounts, which
predictions using data. For a fuller explanation can provide tailored investment advice that is
of AI and machine learning, see the Towards Our more cost-effective for both banks and users.AI for Financial and Insurance Services in New Zealand 17
_USE CASES - HOW AI CAN ENHANCE THE FINANCIAL SERVICES SECTOR
FIGURE 2: Value from AI to Banking
ENHANCE SCALE ACCELERATE AND
EFFICIENCY NON-LINEARLY ENHANCE DECISION
INSIGHTS
CUSTOMER Simplify and automate Augment and enhance Increase speed and
ENGAGEMENT user engagement human effort in quality of insights to
interactions target and personalise
OPERATIONS Automate and Augment capacity Reduce time to
standardise process to address variable predictions and
flows demand and complexity information retrievals
RISK AND Reduce costs by Track risks in real Reduce time to
COMPLIANCE automating manual time, at scale; while detection and
tracking and reviews improving effectiveness mitigation
SOURCE: Citi analysis, 2018.
In New Zealand, the Financial Advisers Act AI image recognition can be used to digitise
2008 required that financial advisers be natural compliance documents and extract key figures,
persons, however in 2018 the Financial Markets anti-money laundering transaction monitoring
Authority began issuing exemptions for a number software can monitor transactions for risk in real
of firms from the Financial Advisers Act, allowing time, and automated reporting can source, sort,
the use of robo-advice for financial advice. 34 generate and store reporting requirements to
• In operations, AI provides opportunities for maintain audit trails, risk logs and reports. 38
improving back-office operations, including
advanced models for capital optimisation, As of 2018, Citigroup notes that most current bank
model risk management, stress testing, and investments in AI focus on risk management,
market impact analysis. 35 Robotic process fraud prevention, and compliance activities. 39
automation help automate ledger reconciliations However, general operations and customer service
and streamline IT support, potentially resulting improvement also offer major opportunity areas for
in cost savings of up to 40 percent. 36 AI. Within New Zealand, AI is anticipated to have
• In the realm of risk and compliance, AI can help significant impact in each of these three areas. “AI
automate processes and reduce costs of regulatory in the back office will dramatically impact banking
compliance. AI solutions are already being used and insurance operations, from credit decisions
by some firms in areas like fraud detection, to investment advice,” says Deloitte New Zealand
capital optimisation, and portfolio management. 37 Partner and Banking Sector Lead Marco Ciobo.4018 TOWARDS OUR INTELLIGENT FUTURE
According to recent reports from Citigroup, • IT automation that links systems to become
IDC, and the World Economic Forum, top self-acting and self-regulating, automating
use cases for the finance sector include: mundane software maintenance activities.
• Automated customer service agents that aid • Advice and recommendation systems
in understanding customers’ needs, reducing to match a consumer’s needs with the
time and resources spent in resolution. correct banking or finance product.
• Robo-advisors that provide automated, often • Automated threat intelligence and
AI-driven financial planning services and prevention systems to identify threat to
individualised investment plans for customers databases, websites and other systems.
with little to no human interaction. • Intelligent processing automation
• AI fraud detection that uses deep that automates processes previously
learning techniques to more quickly carried out by knowledge workers.
and accurately detect fraud. • Robo-regulators that use machine-readable
• AI market abuse detection to spot and machine-executable rule handbooks
abnormal behaviour to detect market to interpret and implement regulation.
abuse and rogue trading.
• Robotic process automation for automating
ledger reconciliations and other processes.
FIGURE 3: Artificial Intelligence Use Cases and Adoption in Banking
IMPROVED CUSTOMER EXPERIENCE
• Improved offer targeting and personalisation
• Automated customer service agents - chatbots / digital Humans for
customer service and support
• Secure identity using using facial, voice recognition biometrics
• Robo-advisors - automated recommendation systems and financial advice.
BETTER RISK AND COMPLIANCE MANAGEMENT
• Improved cybersecurity
• Market abuse detection
• Fraud detection
• Automated threat intelligence.
AUTOMATE OPERATIONS
• Robotic process automation
• IT process automation
• Intelligent data processing automation.
REGULATION
• Robo-regulators.AI for Financial and Insurance Services in New Zealand 19
Section 3:
Current State of AI Adoption in the
New Zealand Financial Services Industry
_CURRENT STATE OF AI ADOPTION IN THE NEW ZEALAND FINANCIAL SERVICES INDUSTRY
IN NEW ZEALAND, A NUMBER OF FINANCIAL INSTITUTIONS ARE
ALREADY USING AI TO PROVIDE SERVICES AND IMPROVE OPERATIONS.
THE “BIG FOUR” INCUMBENT BANKS IN NEW ZEALAND HAVE STARTED
TO ADOPT AI SOLUTIONS TO IMPROVE SERVICES TO CUSTOMERS,
NOTABLY THROUGH CHATBOTS AND DIGITAL ASSISTANTS.
Corporate investment in AI is beginning to pay off $70,000 and are assigned an interest rate based
for some large Australian and New Zealand banks on an individualised credit risk assessment.
who are early adopters. For example, ANZ New
Harmoney uses artificial intelligence to accurately
Zealand’s parent announced its half year results and assess the credit risk of borrowers. Information
told shareholders that a highlight was improvements from over 300,000 loan applications are used in
it made in automation in its institutional business, training Harmoney’s models. This use of machine
through robotics and machine learning. ANZ learning has led to fewer questions on loan
said it has reduced turnaround times by up to 40 application forms, reduced costs for borrowers
percent in trade, credit and customer service.41 and increased profitability for investors.43
However, adoption is complicated and New Zealand Harmoney’s machine learning services are
financial services institutions must face both provided by DataRobot, an automated machine
regulatory demands and a limited talent pool when learning platform, which streamlines the process of
it comes to implementing AI technologies in their deploying accurate models. Taking this approach
organisation. Many of New Zealand’s bigger banks has resulted in a reduction in the time it takes to
have “innovation units” or funds, tasked with incubating deploy a model from 12 to 16 weeks to minutes.44
or accelerating FinTech solutions and startups. For
instance, Kiwibank’s Kiwi FinTech Accelerator gives
startup companies access to mentors, experts,
regulators, and potential partners, and has incubated
successful new companies like Sharesies. One
startup in the latest intake is Stream RLP, which is
developing a digital platform that leverages AI and
machine learning “to enable lenders to provide
an end-to-end, responsible lending experience to
their customers”.42 This and other programs have
had modest impact, but the field is still nascent.
The case studies section below provides expanded
examples about key New Zealand financial
organisations that are capitalising on AI opportunities.
New Zealand Case Studies
HARMONEY: FAST, ACCURATE RISK ASSESSMENT
Harmoney is a digital marketplace that facilitates
digital peer-to-peer (P2) lending, acting as an
intermediary between lenders and borrowers.
Potential borrowers apply online for a loan up to20 TOWARDS OUR INTELLIGENT FUTURE
SOURCE: https://bluenotes.anz.com/posts/2018/07/her
ANZ: PERSONALISED, LIFE-LIKE CUSTOMER To avoid robotic responses to standard banking
SERVICE AT SCALE questions, considerable effort was made to
optimise Jamie’s friendly persona. This included
In July 2018, ANZ New Zealand launched their new
digital assistant pilot, called Jamie. spending time observing the ANZ contact
centre team. In addition, Jamie’s creators
The AI technology was developed with New developed a backstory and personality.
Zealand company Soul Machines. Jamie was initially
programmed to answer questions based on the 30 Currently, Jamie is only able to assist with general
most frequently searched online topics. The pilot banking queries. However, it is expected that Jamie
has since been extended and is increasing Jamie’s will soon be able to carry out personal banking tasks.
workload as it learns to answer a broader range
“When you’re driving in the car you might go: ‘Hey,
of customer enquiries and increase its Te Reo
Māori vocabulary. Jamie, I really need to pay the babysitter $50.’ And
Jamie would do that for you,” says Maguire.46
In its first 100 days Jamie had more than 12,000
conversations with people visiting the site. The most ANZ is not alone in using AI-enabled customer
common question was how to open a bank account, service. Other banks also have chatbots or digital
which Jamie was asked nearly 1200 times. Liz Maguire, assistants, including:
ANZ’s Head of Digital and Transformation, reports that
Jamie was able to answer approximately 60 percent of • Josie, ASB’s digital assistant developed in
customer queries.45 partnership with New Zealand company UneeQ.AI for Financial and Insurance Services in New Zealand 21
_CURRENT STATE OF AI ADOPTION IN THE NEW ZEALAND FINANCIAL SERVICES INDUSTRY
Josie is designed to help with questions Mike Smith, Managing Director of IBM New
about starting a small business, and Zealand says “With financial crime becoming
is available by appointment to meet increasingly sophisticated, BNZ partnered with
customers at the ASB Auckland offices. IBM to address the rising threat of crime and fraud
• Wes, Westpac’s (text-based chatbot, available while still enabling top quality experiences for
to assist customers on the Westpac website. customers and allowing for future growth.”50
• BNZ has created two chatbots – one Safer Payments is one of a number of AI-enabled
for their internal helpdesk, and another solutions that BNZ has announced. As another
built in Microsoft Azure which is being example, in 2017, BNZ was an early adopter of
trialled for KiwiSaver customers.47 Intel’s Saffron Anti-Money Laundering advisor.51
BNZ: DETECTING FRAUD IN REAL TIME KIWI WEALTH: ROBO-ADVICE TO HELP WITH
In late 2018, BNZ announced it was deploying SAVINGS GOALS
IBM’s Safer Payments, a transaction monitoring
In late 2018, Kiwisaver provider Kiwi Wealth
system that uses machine learning and artificial
introduced a robo-adviser service for its
intelligence to identify fraudulent activity before
customers. The robo-advisor, which is
it happens, without accidentally stopping
accessed through Kiwi Wealth’s Future You
customers’ genuine transactions.48 The Safer
Payments system uses a combination of a online tool can provide information and
customer’s transaction history with other advice about the most appropriate Kiwisaver
financial and non-financial data to profile and account for a customer based on their savings
authenticate every transaction as it happens. goals, circumstances and preferences.
While many banks’ legacy systems were designed Ramesh Naran, Kiwi Wealth’s head of digital
to identify and stop repetitive fraud patterns, the strategy told Stuff.co.nz that “Robo-advice is
move to “anytime, anywhere” mobile banking allowing us to reinvent the way Kiwis manage
has made fraud detection more challenging.49 their finances, giving many access to personalised
SOURCE: https://www.kiwiwealth.co.nz/kiwisaver22 TOWARDS OUR INTELLIGENT FUTURE
financial advice that’s previously been out of devices for higher value transactions. Voice
reach.”52 Kiwi Wealth was the first financial biometrics allow ANZ customers to use their voice
services provider in New Zealand to get to automatically authorise payments of more
Financial Markets Authority (FMA) approval to than $1000 through the bank’s mobile apps.
deliver personalised digital financial advice.53
The addition of voice identification technology
Other financial services are also planning simplifies the payment process at ANZ, allowing
robo-advice services. The Warehouse founder customers to omit the usual security measures
and philanthropist Sir Stephen Tindall’s K1W1 when making payments, by using their voice.
investment arm has signed a deal to fund the Although this change makes transactions faster,
growth of Simplicity Kiwisaver.54 Part of Simplicity’s security is not compromised. This is because a
plans for growth include developing an AI ‘robo- person’s voice has five to 10 times as many security
advice’ platform that would be available to all Kiwis. points than other methods such as fingerprints.
“Our customers expect digital options for their
ANZ: VOICE-DRIVEN BIOMETRICS banking and for it to be seamless and easy. A key
challenge for banking today is to help customers
In 2017, ANZ bank partnered with Nuance, a do what they want to do safely and securely” says
speech software company to launch AI driven Craig Bunyan, ANZ General Manager, Technology.
voice biometrics. The system identifies a person
by using the characteristics of their speech
and is designed to improve security on mobileYou can also read
