The document summarizes discussions from an Instech Advisory Board Dinner on the topics of real-time data and insurance, ethics and artificial intelligence, and data collection and GDPR regulations. Key points from each topic included a need for more skilled data analysts, changing customer demands requiring new data sources, concerns about job losses from automation, and a lack of clarity around GDPR's impacts. Throughout, participants debated challenges and potential solutions, with the goal of capturing insights to share more broadly.

1. Hosted By: Sponsored By: Published By:
INSTECH ADVISORY BOARD DINNER
DISCUSSION PAPER
12TH
OCTOBER 2017
www.instech.club, December 11th, 2017, Hilton Canary Wharf, London
Innovation, Future Technologies & AI for Insurance

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The Meeting Place for Top Insurance, Broker and Instech Executives in
Europe
Instech.club is designed to give insurers, brokers, re-insurers and instech companies new
ideas, strategies and networking they need to win the innovation and disruption game.
Chief Operating Officers, Chief Innovation Officers, Chief Marketing Officers, Chief Data
Officers and Chief Technologists from the top 250 insurance and broker companies form the
advisory board and the panel of speakers and participants. Dozens of innovators will be
joining the panels and debates, with some of the most senior C-level executives from the
world’s largest insurance giants, as well as medium size underwriters, brokers and small
companies, to explore the future impact of this technology on your business. In short, all of
your competitors, partners and future employers will be at this event! instech serves as a
source of new ideas, proven strategies and meeting place for both top established insurance
companies, instech innovators as well as investors.
A New Approach
Informal discussion formats such as dinners or networking drinks often bring together a wide
range of experiences and deeply knowledgeable attendees, however there is rarely any
formal outcome that captures the knowledge being discussed. Conversely, formal
engagements such as conferences tend to only provide a superficial level of information due
to the constraints of time and the need to adapt to a lower level of general knowledge on the
topics discussed.
Wzard Innovation use an innovative approach to address the key problems faced by other
formats by combining industry expertise in facilitating interactive problem-solving workshops
with an informal dinner discussion. The goal is to allow a depth of discussion and capture
more detail on real problems and real solutions that can be provided as a take-away to
participants and share with a wider audience.

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Introducing the InsTech Advisory Board Dinner
…We’ve followed the same format for many years, this is the first time we
have applied more structure, capturing insight and opinions to share with a
wider audience. I hope you find this discussion paper helpful and informative.
Katia Wyatt, Club2020 Founder and Host
The InsTech Advisory Board Dinner involved two separate tables, for each topic table hosts
navigated the discussion through three phases as outlined in Figure 1, leading the discussion
from problems/challenges, through solutions/opportunities and finally identifying any actions
that should be taken.
Figure 1 - Discussion Stages
Discussion Topics
Three topics were selected for discussion:
• Real Time Data and Insurance
• Ethics and the Machine
• Tiny Data Collection Forms vs GDPR

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Topic 1 – Real Time Data and Insurance
The first topic originates from the
challenges of increased data volumes
being generated by various mobile and IOT
devices.
“Insurers are not ready for”
real-time data
In the first phase of discussion participants
are encouraged to discuss their insights
and problems. The differences of opinion
were immediate with voices split between
the feeling that companies do not yet have
enough real-time data compared to the
reality of insurers simply not yet being
ready to ingest and utilise real-time data
even if they had it. The consensus was
there is a skills shortage for turning the
increasing amount of data into valuable
insight.
“a shortage of skills”
The debate on the types skills necessary
demonstrated wide variation of opinion
which ranged from feelings that current
data scientists are not delivering enough
insight, through to there being increasing
needs for more data analytics.
The volume of data is increasing and the
paradoxical situation that on one hand
companies are missing out on large
volumes of data because they are ill
prepared to capture it, compared to the
broad acceptance that legislation such as
GDPR will limit what can be collected in the
future.
Specific scenarios were discussed, the
changes in car manufacturing for example
has rendered much of the historical data
gathered much less relevant. Meanwhile
smart home devices are providing
immediate benefits to customers but there
is little real understanding regarding which
of the devices give real value.
“more bad data is better”
than having less good data
On the theme of Data Quality there was
the surprising conclusion that more bad
data is still better than less good data. A
point that was counter to the general
concern that the data being provided by
current mobile devices could not be
sufficiently relied upon.
Figure 2 - Visibly sharing key points
Inevitably the discussion returned to
customer needs and everyone agreed that
customers generally do not wish to talk
directly to insurers and usage based
insurance makes more sense to the next

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generation of customer. Two facts which
lead directly to the need for real time
pricing that differentiates based on actual
customer behaviours. However, this is an
approach that is more difficult than
inferred pricing, but it is also expected to
be the future approach. As this scenario
becomes realistic customer lifestyle
changes would need to be tracked
automatically and produce micro-
adjustments to the pricing.
In concluding the discussion, the view was
taken that the customer journey is
changing and the touchpoints will no
longer be directly with the insurers
themselves. Action is needed to find out
who is now closer to the customer and
ensure these channels are open to us.
“Usage based insurance”
makes more sense
If there is an unexpected opportunity then
it will be moving insurance from a grudge
purchase to a convenience service for
which the customer is positive about.
In bringing the topic to a close, the advisory board concluded:
• There is a need for more skilled people able to deliver insight from data
• The ability to record more data, irrespective of quality right now, is important
• Customer demands are changing the touchpoints for insurance, identification of
these new touchpoints is high priority
• Real time data will be critical for delivering future value
Throughout this session a Trello board was displayed for everyone to see, prompting a
cross-fertilisation of ideas between the different tables.
Figure 3- The Trello Board used for sharing key points on Real Time Data

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The Value Proposition Canvas was used to summarise in real-time the discussions which
focused on the customer, driving out potential products and services that meet changing
customer demands:
Figure 4- Initial Value Proposition Canvas
Further Thoughts – Real Time Data and Insurance
The discussion on real time data could have taken many routes, a few other areas to
consider on this topic might be:
• Using Real Time Risk Models for Fraud Detection
• Real Time Data for Cyber Security
• Machine Learning evaluating real-time behaviours and identified pay-as-you-go
needs (insurance because you’re looking for a new car, mortgage if you’re looking at
houses, etc.)
• The advance of Smart Cities, when everything is connected real-time, will there even
be an option to opt-out?
• There are already third-party insurance companies beginning to disrupt by using
real-time lifestyle products

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Topic 2 – Ethics and the Machine
Ethics are the code of conduct that
distinguishes between good and evil,
between right and wrong, and between
virtuous and non-virtuous characteristics.
The rapid advances in technological
change are leaving many to debate the
ethics of the changes we face. A debate
largely driven by the advances in
automation and artificial intelligence.
Figure 5- Insight and Debate
The discussion generated some passionate
debate from the advisory board, with the
opening gambit of “You can approve my
claim with AI, but you cannot deny it,”
being a general view. Others were
unhappy with the term “AI,” pointing out
that it was an over-used term and it should
be redefined as the ability for self-learning.
“You can approve my claim”
with AI, but you cannot deny it!
Several discussions were heard about the
many fears regarding the risk of self-
learning machines generating unconscious
bias and thereby poisoning the underlying
data. Several prominent examples of AI’s
being closed down because they began to
deliver racist and sexist responses were
cited.
Some took the view AI was just data
analytics and good data analytics would
generate the same results. This led to the
question of the data being analysed, what
types of data is it permissible – or ethical -
to be collected on individuals in the first
place? Here many members of the board
had strong feelings that we cannot trust
financial services organisations to behave
ethically with the data if they were given a
complete free reign, and legislation such as
GDPR is essential to ensure only necessary
data is collected.
“Rules and Regulations”
cannot keep pace
Most members felt that rules and
regulations cannot currently keep pace
with the changes, so regulation is only part
of the answer. The debate on regulation
was particularly focused around the
growth of AI solutions, without full
traceability the “computer says no (and we
don’t know why)” scenario is unacceptable.
“An uninsurable sub-class”
Bringing the discussion to insurtech, the
question was raised whether the adoption
of AI to track behaviours would create an

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uninsurable sub-class whose behaviour
would be considered an unnecessary or
excessive risk.
Inevitably the powerful language
recognition of Alexa (and others) was
recognised, leading to the debate of
whether bots could ever achieve a
sufficient level of empathy.
On a more pragmatic level the fear of job
losses was a big concern irrespective of
industry (the use of drones for A to B
transport in the future for example).
Similar to the previous discussion topic, the
potential need for insurance companies to
repackage their offering to meet customer
needs was discussed. The need to break
down traditional lines of business to meet
future customer needs was highlighted a
number of times.
“Fear of Job Losses”
a concern
Bringing the discussion to a close there was
agreement that customers would be happy
to use AI to triage and advise, presenting
better quality of information to staff, but
would be unhappy if the result was a
decline.
Participants also agreed that Live Chat is an
important stepping stone, it will lead to a
chatbot and eventually provide the
stepping stone needed to adopt AI.
The “trolly problem” (a thought
experiment where you are given a disaster
scenario and have to decide how to
respond when presented with the choice
of killing a child or a doctor) is actually
irrelevant, if the choice is made to simply
protect the customer / driver.
Using data to recognise the customer
situation, or context, would open new
opportunities to move from reactive
insurance to proactive insurance,
automatically determining the next course
of action without the need for manual
(human) involvement.
Finally, and despite the slow pace of
regulatory change, there was still the
general view that regulation is needed to
ensure ethical behaviour by corporations.
Figure 6- Customer (Proposition Canvas)

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In bringing the topic to a close, the advisory board concluded:
• There are mixed views on the ethics of Financial Services companies, therefore
regulation remains a cornerstone.
• Customers are unlikely to be accepting of an AI denying claims.
• The fear of job losses throughout multiple industries is a genuine concern
Further Thoughts – Ethics and The Machine
The discussion on ethics could have taken may routes, a few other areas to consider on this
topic might be:
• The Virtual Me - Who owns the Virtual you? Company ownership if employee leaves?
Or After death? If your knowledge is stored in a Neural Network, what does that
mean?
• Surveillance - fraud detection, suicide watch, compliance breach are all possible but
we don’t / can’t do this at the moment because of our ethics. What happens when a
country doesn’t apply the same principles?
• Impact on Taxation of earnings if automations begin to cap the upper earnings,
changing the nature of the economy and delivery of public services
• Increasing use of AI for Elder Care, or use of Humanitarian Drones
• Automated Armed Robots
• UK Government indicating the decision not to regulate AI

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Topic 3 – Tiny Data Collection Forms vs GDPR
The final topic was perhaps the most challenging for our participants, discussions focused on
the current situation and challenges rarely moving into opportunities, solutions or potential
action.
The conversation began with a sharing of
the background to data analysis, a
discipline that has seen a lot of change over
the last 3 years. Historically data required
simplification to analyse in any realistic
timeframe, whereas now it is possible to
analyse greater volumes of data in real-
time.
While some felt that there was a lot of
scaremongering by legal and compliance
teams, creating unnecessary panic about
GDPR within organisations, others felt that
GDPR was actually great news for
consumers as it provided them with
necessary protection. A more challenging
concern was that the introduction of GDPR
will inhibit opportunities for innovation.
“GDPR will inhibit innovation”
Relatively few discussions focused on the
“tiny data collection forms” beyond the
broad agreement that customers would
prefer a lower data collection burden.
While a small form of data entry using
publicly available data is possible –
generally as a result of people openly
sharing data through social media – there
is a feeling that GDPR will also make this
more difficult to achieve in the future.
“personalised services require”
more data
Millennials are considered to be distrustful
of companies, yet are also demanding
more personalised services, which in turn
requires more data to achieve. The
challenges facing insurance companies
broadly breaks down into what do you
store, what do you hold on to, and being
clear about what value the data is giving
you.
Questions on the practicalities of GDPR
regularly raised to the surface, such as
whether GDPR would be enforceable?
What can we do with historical data? What
happens to marketing data for which
explicit consent has not been given? Or
what is necessary to make legacy systems
compliant?
Figure 7 - Desert and Discussion in action

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The topic of data quality also resurfaced
when considering the use of IOT data in
relation to GDPR; IOT can be ambiguous as
to which person the data has been
collected for.
“IOT can be ambiguous”
In conclusion the final topic was perhaps
more interesting from the view of how
participants addressed the topic rather
than the specifics of the topic being
discussed. Participants openly stated that
their energy for GDRP discussion was
lacking, a scenario that is likely reflected in
many organisations across the UK who are
struggling forward with GDPR. It also
generated the most polarising views,
which cited a doomsday scenario at one
extreme, through to comparisons with Y2K
(a lot of fuss about nothing) at the other.
In bringing the final topic to a close, the advisory board concluded:
• Customers prefer lower data collection burden
• There is a lack of education across insuretech on the real impact of GDPR
• More data is needed to provide personalised services for customers
Further Thoughts – Tiny Data Collection Forms vs GDPR
The discussion on GDPR could have taken may routes, a few other areas to consider on this
topic might be:
• Surveillance has a need for data that is a challenge for GDPR (Fraud Detection, Suicide
watch, compliance Breach)
• People are ignorant, they don't care that they give data away for free, regulation and
education is therefore needed.
• We are not obliged to use social media (Facebook, LinkedIn, etc) yet we have signed
up to give everything away for free, we don't read the T&C!
• Could you develop a proposition that uses deep data about customers to understand
their needs and deploying e-health technologies to build relationships and guide
customers’ behaviour?

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Feedback and Lessons Learned
• Traditionally discussions tend to focus towards insight and
problems, the new approach generated more information on
solutions and actions.
• The shared Trello Board allowed discussion points to be shared
between tables and participants to reflect on key points.
• Participants were reallocated to different seating
arrangements for each topic / dinner course, an approach
generally frowned upon, but near unanimously agreed as an
effective approach for this format.
• Three topics were selected for the first event, our view is fewer
topics would provide increased opportunity for greater depth.
• Information that may have been missed during the event (it took place at the other
table for example) is available for review and sharing with members who were unable to
attend.
• The output is a resource for sharing more widely, to customers or internal staff,
promoting insights gathered.
• Additional research, value-added insights or promotional materials can also be
incorporated into the final report.
Contact Wzard Innovation for more information
Wzard Innovation combines industry expertise in facilitating interactive problem-solving
workshops with informal discussion formats such as dinner events or networking. Our first
experiment for the InsTech Advisory Board Dinner was deemed a terrific success, facilitating
deeper discussion and documented insights for sharing with a wider audience.
If you would like to find out more about this innovative new format then email
info@wzard.co.uk or contact us directly, details on the following page.
Figure 8- Capturing Feedback

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Hosted By:
Katia Wyatt
Co-Founder & Director
katia.wyatt@club2020.co.uk
07847617977
Gabi Cogorno
Co-Founder & Director
gabi.cogorno@club2020.co.uk
078135 13701
Sponsored By:
Simon Laird
Partner
simon.laird@rpc.co.uk
Mark Crichard
Partner
mark.crichard@rpc.co.uk
James Phythian-Adams
Legal Director
James.Phythian-
Adams@rpc.co.uk
Prepared By:
Rod Willmott
CEO, Chief Wzard
rod@wzard.co.uk
07450 273103
@rwbdjr
Rob King
COO, Chief Operating Wzard
rob.king@wzard.co.uk
07711 250545
@Rob_King_
Thank You
Thank you to Club2020 and the InsTech Advisory Board for their support, participation and
insight in the production of this paper.
Next Event
www.instech.club, December 11th, 2017, Hilton Canary Wharf, London
Innovation, Future Technologies & AI for Insurance