The Future of GenAI and Insurtech: LIVE from AWS re:Invent
Summary
TLDRAWSのAry GuptaとAnorのFaruk Shayが、保険業界における生成的AIの影響について議論。Guptaは、AIが技術と人間の関係を変革し、保険業界では創造性、ドメイン探求、専門的な意思決定支援、新入社員のオンボーディングに影響を与えていると述べた。Farukは、保険会社がAIを積極的に採用し、操作効率化とデータのスケールでの活用を目指していると補足。両者は、AWSとAnorが提供するコードレスプラットフォームを活用し、保険業界のデジタル化を加速する可能性について語った。
Takeaways
- 🌟 AWSのAry Guptaが保険業界のビジネス発展をリードし、北米に焦点を当てています。
- 🔍 Ary GuptaはAWSで6年以上働いており、保険業界におけるAIと機械学習の進化に貢献しています。
- 📈 保険業界では、創造的なアウトプット、新しいドメインの探求、専門的な意思決定支援、新しいチームメンバーのオンボーディングなど、AIの活用が進んでいます。
- 🚀 保険会社は、AIを通じて運用効率を向上させるために積極的に実験を行っています。
- 🛠️ 従来のチャットボットとは異なり、AIは対話形式でQ&Aを可能にし、保険業界におけるカスタマーサービスの向上に役立ちます。
- 💡 AIは、保険業界の顧客サービスを向上させるために、リアルタイムでのサポートやカスタマイズ情報を提供することができます。
- 🌐 保険会社は、AIを活用して、データのスケールと効果を高め、遺伝子データや外部データの統合を迅速に行うことができます。
- 🔄 保険会社は、AIの力を最大化するために、AWSとNoCodeの能力を組み合わせることを積極的に検討しています。
- 🔧 従来のレガシーシステムからの移行において、AWSのBedrockを使用することで、プロセスの加速と効率化が期待できます。
- 📊 保険業界のCIOは、AIを活用して実験を行い、プロトタイピングから生産までをスケーラブルな方法で進めるべきです。
Q & A
AWS reinventでAry Guptaが参加したイベントの主題は何ですか?
-Ary Guptaが参加したAWS reinventのイベントでは、保険業界におけるAWSの役割とAI(特に生成的AI)が保険業界にどのように影響を与えているかについて議論されました。
Ary Guptaの現在の役職は何ですか?
-Ary Guptaは、AWSの保険業界向けのNorth America地域のMarket focused on Goto Marketをリードしています。
Ary Guptaは保険業界でどのくらいの経験がありますか?
-Ary Guptaは保険業界でほぼ25年もの経験があります。
AWSが保険業界で注目している4つの主要なイノベーションの分野は何ですか?
-AWSが保険業界で注目している4つの主要なイノベーションの分野は、クリエイティブなアウトプット、新しいドメインの探求、専門的な意思決定支援、そして新入社員のオンボーディングです。
生成的AIが保険業界にどのように影響を与えているか?
-生成的AIは、保険業界に多くの影響を与えています。例えば、コードの作成やデザイン、検索や要約化、パーソナライズテーションの改善、Q&A形式の対話、専門的な意思決定支援、複雑なタスクの自動化、ニューハイヤーのオンボーディングなどです。
保険会社が直面している主な課題は何ですか?
-保険会社は、コストの上昇、有機成長の難しさ、災害露出の増加、ビジネスコストの高コスト、データシステムの分断など、多くの課題に直面しています。
AWSとAnorが提唱するコードレスフレームワークの利点は何ですか?
-AWSとAnorが提唱するコードレスフレームワークの利点は、迅速な開発、低コスト、ビジネスユーザーの早期参加、自動化されたプロセス、そしてよりスケーラブルなプロトタイピングから生産へとの移行が容易であることです。
保険会社がAIを採用する際のアドバイスは何ですか?
-保険会社がAIを採用する際のアドバイスは、まず低リスクな内部運用からの実験を始め、コードレスのアプローチを検討し、プロトタイピングから生産へとの移行に向けた戦略を立てることです。
AWSのBedrockサービスとは何ですか?
-AWSのBedrockサービスは、事前訓練されたファウンデーションモデルへのアクセスを提供し、APIフレームワークを通じて複数のモデルにアクセスできるフルマネージドサービスです。
保険会社がAI技術を採用する際のセキュリティや規制上の考慮事項はどのように対処されていますか?
-保険会社はAI技術を採用する際に、セキュリティや規制上の考慮事項を重視しています。特に、データプライバシーや顧客情報の保護は重要であり、AIの実装にはこれらの要素が適切に取り入れられています。
Ary Guptaが保険業界で見ている最も興味深いトレンドは何ですか?
-Ary Guptaは、保険業界で最も興味深いトレンドとして、生成的AIの認知的自動化機能の到來を指摘しています。これはスケールで実施可能であり、技術の進化が非常に迅速であると感じていると述べています。
Outlines
🌟 導入とゲスト紹介
この段落では、イベントのライブ配信が開始され、ゲストであるAry GuptaがAWSから加入したことが歓迎されています。Faruk Shayが保険ビジネスをリードしているAnorで、Ary GuptaがAWSの保険業界の市場に焦点を当てた北アメリカ地域をリードしていることが紹介されています。Ary GuptaはAWSに6年以上勤務しており、保険会社や再保険会社、大型ブローカー、ISV、システムインテグレーターと協力してAWSの保険顧客へのビジネス変革を促進しています。Aryは保険業界で約25年働いており、AWS re:Invent会議に出席していることを楽しみにしています。
🤖 ジェネラティブAIが保険業界に与える影響
この段落では、AIと特にジェネラティブAIが保険業界にどのように影響を与えているかについて議論されています。Ary Guptaは、ジェネラティブAIが強力なツールであり、そのような強力なツールがユーザーの手中にあることを指摘しています。保険業界においては、これまでに不可能だった様々なアプリケーションが可能となりました。また、AIがもたらした技術革新の歴史を振り返り、ジェネラティブAIがAIと機械学習の進歩の節目をもたらしたと感じていると述べています。Aryは、AWSの保険顧客が見ているイノベーションの主要な分野について4つのカテゴリに分け、それぞれについて説明しています。
🚀 保険業界の課題とジェネラティブAIの機会
この段落では、保険業界が日々直面する課題と、ジェネラティブAIがどのように役立つかについて説明されています。Ary Guptaは、COVID-19の流行以来、保険業界に起きた変化や課題について話し、マクロ経済の立場からのコストの上昇や保険会社の有机的な成長の難しさについて触れています。また、AIがデータをより効果的に利用できるようにし、保険業界の複雑なデータシステムやレガシー環境から解放される方法についても議論しています。
🛠️ 保険会社のデジタル化とAWSの役割
この段落では、保険会社がAWSの機能をどのように活用してデジタル化を進めているかについて説明されています。Ary Guptaは、AWSの顧客が特に審査機能と請求機能で活発に実験をしていることを指摘しています。AIによる支援機能や詐欺検知、カスタマーサービスの改善など、保険業界におけるAIの活用方法について詳細に説明しています。また、AWSとAnorが協力してBedrockを通じて保険会社がどのように支援されているかについても触れています。
🤝 保険CIOへのアドバイスと未来の展望
最後の段落では、保険会社のCIOや業界の他の関係者にとって、ジェネラティブAIの今後の進展に向けてどのようなアプローチを取っていくべきかについてのアドバイスが提供されています。Ary Guptaは、組織内で実験を始めることを勧め、特にAWSのBedrockを使用して事前訓練された基盤モデルにアクセスする方法について説明しています。また、AnorとAWSが協力してBedrockを活用し、保険会社がレガシーシステムの移行を加速する方法についても言及しています。保険業界の技術採用の速度と、AIの可能性を最大限に活用するための期待が表現されています。
Mindmap
Keywords
💡AWS
💡保険業界
💡生成的AI(Generative AI)
💡ビジネス変革
💡カスタマーサービス
💡意思決定のサポート
💡データ分析
💡デジタル化
💡NoCode
💡レガシーシステム
Highlights
Ary Gupta, who leads AWS's insurance industry go-to-market focused on North America, discusses the impact of generative AI on the insurance industry.
Generative AI has brought an inflection point in AI and machine learning, making significant advancements in a short period.
Generative AI empowers users to create images, videos, and write code, offering new possibilities for the insurance industry.
The potential for foundation models within generative AI is incredibly exciting, though it's still early days.
In the insurance space, generative AI is being used for creative output, domain exploration, expert decision-making support, and onboarding new team members.
The importance of choice in generative AI models and the platforms provided by AWS is highlighted, allowing for tailored solutions.
AWS's launch of Amazon Q demonstrates the game-changing potential of generative AI in technology and DevOps.
The rapid pace of generative AI development means that insurers should maintain a flexible mindset and not be tied to one model.
Insurers face challenges such as increased cost of doing business and the need for innovation to stay relevant.
Generative AI can help insurers with operational efficiencies, especially in underwriting and claims functions.
Fraud detection in claims is an area where generative AI shows promise, with the ability to flag patterns of fraud more effectively.
Improving customer experience through real-time assisted functionality is another application of generative AI in insurance.
Insurers are embracing generative AI more actively than other industries, with a thoughtful and secure approach.
Legacy migration and the use of AWS Bedrock are central to the conversation for streamlining business processes in insurance.
Ary Gupta advises insurers to start experimenting with generative AI and consider no-code solutions to accelerate the innovation process.
The combination of AWS's technology, no-code capabilities, and industry collaboration is seen as a powerful approach for insurers.
Ary Gupta and Faruk Shay encourage insurers to reach out and engage in conversations about adopting and leveraging generative AI.
Transcripts
we're live uh
Daniel hello and welcome everyone from
AWS
reinvent uh Anor is proud to have Ary
Gupta from AWS joining us today my name
is Faruk Shay I lead the insurance
business at Anor welcome everyone Ary
would love to start with a quick intro
from your side uh tell the viewers about
your background what you do at AWS and
it's a pleasure to have you here yeah
thank you Faruk uh and thank you to the
uncork team for having me so my name is
arti Gupta and I lead aws's insurance
industry goto Market focused on North
America region and I've been with um
with AWS for over six years now what I
do in my current role is I really uh
lead the business development and go to
market working with both BNC and life
insurance companies re reinsurance
companies large Brokers so really
anything in the insurance space along
with our isvs and system integrators and
really just helping them effectively
position the benefits of AWS to
Insurance customers to really drive that
business transformation um with the line
of various lines of business so I've
been working in the insurance industry
for almost 25 years um and really happy
and excited to be
here it's a pleasure having you I'm
super excited about the conversation I
was saying this to somebody earlier the
AWS 3 invent conference like always it's
such a magnificent event and this year
yeah with all the kind of activity
around gener like generative AI it's
been exceptional to be here I guess to
kick off the discussion maybe we can
start there right it's a Hot Topic AWS
is doing a lot of work in gen would love
to get your perspective on how gen is
influencing the insurance
industry yeah absolutely you know I was
actually it's funny you say that I was
thinking about the last year's reinvent
and the reinvent this year right I think
geni was not as you know probably not
even mentioned at last year's reinvent
so how so much has changed in a way like
so much advancement has been made when
it comes to AI more broadly but
specifically gen and I feel like you
know gen has really brought an
inflection point in our kind of Journey
of overall Ai and machine learning and
if you really look at the history it has
really always been about change and lot
of that change has been driven by
technology um I feel what's really
different with Gen and I think the hype
is real and obviously a lot of our
customers are super excited about it we
are very excited about it but there are
a couple things um in my opinion that I
feel are very different right so first
thing is I think if you just like purely
look at gen I think it's a very very
powerful tool but the beauty is that
something so powerful is now directly in
the hands of users so users can go
around and play around with it and do
things like creating images videos
writing code and all that stuff right so
even in terms of insurance there's lot
of different applications that you know
traditionally were not quite possible um
but now with geni that um business users
can just jump in and start playing with
it and then the second thing I think
with Gen more broadly speaking is
historically has just been about you
know writing technology writing software
and then humans had to kind of learn how
to really um derive value from that
software and Technology gen again has
really just reversed that it has just
made the whole process so much easier by
giving those tools in the hands of the
users and I think the potential for
foundation models within you know gen in
particular is incredibly exciting um and
having said that that I would say it's
still very early days because as you
kind of think about the the key areas of
innovation that at least we see from an
AWS standpoint with our insurance
customers I would say more broadly
they're kind of falling in the four key
buckets number one would be creative
output whether that's just you know U
writing code or designing or modeling
really being used behind the scene and
improving that search and summarization
and personalization so I think that
really gaining a lot of traction um in
in the insurance space second thing I
would say would also be new domain
exploration where it's very much in a
Q&A very conversational type of format
that historically we have not seen um
kind of play out with the traditional
chat Bots and then um the expert
decision making support um I think for
Rook you probably see a lot more use
cases on that front too where it's the
human in the loop almost as an assistive
functionality where um whether it's in
underwriting or claims you can have an
assistant so to speak powered by gen to
really kind of automate the complex task
that really save that human cognitive
power for those things that require
human intelligence but reducing the
consideration set of things that they
may need to consider and then of course
we also see that in onboarding new team
members into potentially complex subject
area so I think the use case is a really
really uh powerful and very diverse set
of use cases that we are seeing in the
insurance space curious about your
thoughts as well it's been
fascinating looking at the uh keynote
yesterday uh at aw3 invent and they were
talking about the importance of choice
right the ability for you as these
models get developed in generational AI
to or generative AI to be able to
leverage the right model for the right
capabilities and the kind of platform
and choice that AWS provides through
bedrock that was fascinating to see it
was also very interesting with the
launch of um AWS or Amazon Q right which
all so we were we were spending some
time with a number of our clients who
have uh technology and devops
capabilities uh and and folks who spend
all their time looking to automate those
functionality but the ization of gen in
that context really is a game changer
right like it's you need to SP
environments and ec2 instances and so
forth and you can you can actually just
have a conversation with some like a
technology capability that helps you do
that right so the learning curve the
adoption the speed and automation that
you would expect like it's like
fantastic to see and in fact like the
one of the biggest observations uh
client made today was it's moving so
fast we just just don't know what it in
six months right like it's only been to
your point less than a year since we all
like become familiar with the technology
and the word of geni but it's moved so
fast and across so many kind of areas
right like
marketing engagement customer engagement
servicing
technology Amazon whisper automation
productivity there there's so many
fronts here right so the confusing a
little bit to say what it might be six
months from
now oh yeah I mean new models I feel
like are just coming out every day and
new features and functionalities so
right so and I I always tell our
customers as we are working with Gen um
use cases or proof of concept to really
maintain like a mindset a flexible
mindset and not not necessarily being
tied to just one model because the
models just are you know coming out
every day more and better and faster um
and that's the beauty of Technology
there it's fascinating the the the way I
think about gen is that this is there's
been many Technologies like cloud and
rpas and like you know uh blockchain and
but this is the first time you're seeing
really the cognitive automation
capability oh absolutely right at scale
which is very very exciting I I wanted
to check with you right like in that
context how do you see there's this
world of cognitive automation gen
capabilities models and and services
coming out but at the same time as you
look at insurers and the industry
broadly what are some of the challenges
that you see on a day-to-day
basis yeah you know um it's funny you
ask so I think few things I would say
within the last two years because it's
interesting right so in the spectrum of
um Insurance in particular but even more
broadly I I think covid brought in some
Behavior changes and um you know just
different challenges that came with
covid but now coming out of covid right
so this postco
era so it kind of put these pressures
more kind of an economic standpoint and
you know we all hear about inflation we
all hear about just you know the higher
cost of doing business so I I think both
in the personal General Insurance space
as well as life Insurance base what we
are first of all seeing is just in terms
of an overall macroeconomic standpoint
is just the cost of doing business is
higher plus I think that organic growth
for insurance companies is has been
challenging right like the PNC insurance
companies are really struggling more I
would say from a profitability
standpoint the catastrophic exposures
are at kind of at an all-time high and
like I said the cost of doing business
is you know higher so
and insurance as you know there's always
like a lag in terms of being able to
catch up to the right rate for the right
risk so I think that's going on on the
life insurance side what I'm seeing
talking to our customers is I think
they're just looking for that Innovation
um in terms of making those um you know
whether it's the term life an nudies
those you know typical products in the
Life Insurance space making them really
more relevant um for their and customers
being able to appeal to the younger
Generations being able to make that ease
of doing business direct to Consumer
channels uh elevating the customer
experience right like so all those
challenges are really even more
highlighted I feel in today's world and
I'm I'm really hoping as as we you and I
are kind of just discussing about the um
promise of Genna I think these all these
areas really can you know be good
candidates for that experimentation and
really bringing first of all those
operational efficiencies to kind of take
take out the cost uh but also being able
to leverage data um at scale and more
effectively because again you know I
think insurance has been kind of really
notorious for having this disparate Data
Systems and Legacy environment um and
being able to really kind of break free
from that and get into use cases where
you can really liberate not just your
internal data but uh you know attack on
your external third party data and being
able to do it with really um speed
velocity and at scale so I think those
those are kind of my things like I think
they the customers are facing but I
think there's definitely a lot of
potential in addressing those risks this
is such an exciting time I always think
about it when we when we talk about the
challenges that the industry has faced
right but if I if I put together all the
Innovation and capabilities that
AWS has provided over over the years
right all the way from like just the
cloud capabilities and the serverless
capabilities and and kind of how we had
uncor think about codess and then you
add then to the mix right I would love
to get your perspective on how are you
seeing opportunity for insurers to
leverage some of these capabilities
together to exrate their
Journey yeah I think the key areas that
I'm kind of seeing a lot of um interest
and experimentation number one you know
that operational efficiency that I was
talking about so I think the two key
business units that pop up over and over
again is in underwriting uh functions
and claims functions right because again
there are um I mean if you think about
from a traditional standpoint I would
say for example our AWS customers are
using what we call intelligent document
processing but I think what happens
traditionally with those models is you
still have to train a lot of your
documents um and the data to to be able
to you know get the outputs that you're
Desiring um but the hope with now gen
and the experimentation that we are
seeing is that these models are
generalized and trained upfront so
they're much more immediately Deployable
and being able to kind of get the
results and also with better accuracy so
I think that assisted functionality
again I'm not saying that there are
going to be decisions kind of you know
automated decision making happening in
underwriting in claims but definitely
being able to enhance those processes
and really kind of cut down on those
manual tasks um are some of the areas we
are seeing same thing with on the claim
side you can have all your adjuster
notes and stuff like that being able to
um automate and summarize so you know
you can extract the relevant information
much more timely and really speed up the
claims resolution process and then also
I'm seeing um on the fraud detection
standpoint uh from a claims again claims
functionality where I think gen is
showing a lot of Promise being able to
kind of look at the data holistically
and being able to flag those patterns of
fraud again you know fraud is a big area
of interest uh within the insurance
industry and then last but not the least
overall from a customer experience
standpoint U I think that's again that
real time assisted functionality for
your call center Representatives being
able to guide them and when you have an
angry customer on the line or being able
to kind of Coach them through it in real
time with Gen being able to summarize
and present that personaliz information
the next best action I think those um
all areas I think show a lot of promise
and this is this is such an interesting
space right like uh as I think about
today all of our customers are very
actively experimenting with Gen right
and what we have seen generally and I'm
I'm sure like as we work together on so
many clients we're seeing the same thing
that the insurers are actually embracing
Genai much more actively than they've
ever embraced any technology yes faster
than most Industries have right like so
it's very fascinating for insurers just
kind of engage with technology this
quickly but they're also very thoughtful
about it right like there's always the
security conversation and I think people
beyond that already there's also a lot
more of the experimentation for on
internal use cases like underwriting
claims marketing devops and so forth and
then there is also to your point they're
very thoughtful about not trying to
automate the decision making but rather
digitize the process of decision making
right human in the loop whether it's
underwriting whether it's claims
adjudication fraud and so forth but
getting the you know the the difficult
manual pieces of the process out of the
way in a more digitized process manner
right like so that that's very exciting
I did I I also wanted to you know the
more we work together there's a lot of
work that we are seeing from a legacy
migration perspective right like and
Bedrock is the central theme in this
conversation right so whether it's goal
migrations and there's very early
emerging successes in this area right we
we're seeing this where insurers are
actively looking to address the biggest
problem that we have had in the industry
right for a long time which is all about
Legacy migrations desperate systems like
the whole plora of of systems and
infrastructure that you can you can
think about and I'm I'm very excited
about the potential for using llms using
jna for legacy migration bedrock and the
functionality it provides to
accelerating the journey for the
industry to streamline their business
right like uh from your perspective like
what would your advice be to insurers as
they're thinking about ni as you're
thinking about the amount of innovation
aw is bringing how would you think about
what an insurance CIO should be looking
to do over the next few months over the
next year what what does success look
like for
insurers yeah no great question I think
number one I would say that you know
experimentation is the key I think as
the you know as in your organization
you're kind of finding like these use
cases that again could be internal could
be low risk more from a regulatory
standpoint so not really automating the
decision- making but more from an
operational standpoint I would say start
um you know kind of experimenting there
um but you know even even I I do want to
kind of bring to a point um you know
about the partnership that we have Faruk
you know AWS and uncor as we have worked
together through several different um
customers I think what your organization
is able to bring in is that code L
aspect and that kind of becomes the glue
in this conversation too what I really
like about that is as you're
experimenting and you're working with
Partners such as your organization I
think not only you are gaining the
agility so three times faster but also
that reduced cost in terms of 70 almost
70% you know reduced maintenance cost
and again as the name suggests no code
generated no code needed and being able
to bring your business users into the
process early on on I think that's
really huge because historically the way
things have worked and I've grown up in
the insurance spaces you know business
rules you know are defined and then
they're kind of thrown over to the
developer side and then they kind of
build something and then you go back to
the user
testing I think with with a partner like
yours I think what we are seeing jointly
and I would love to hear your thoughts
too where you know you can just go in
with a codeless framework and being able
to kind of Build That Joint Le with the
business users being part of the process
faster and better at a reduced cost so
first of all yeah I mean so I think as
the cios or any Persona in the
organization is thinking about and you
know bedrocks in particular you know
that's really the easiest way um from an
AWS standpoint to access pre-trained
Foundation models with a single API
framework that can really provide access
to multiple models because it's a fully
managed service with API access is um
and by default it's not trained on
customer data and prompts but it really
kind of achieve that domain adaptation
mainly by providing custom data through
through the prompt and really new
features are coming out so we have now
agents for Bedrock which really gives
you the enable generative AI apps to
complete the task in just a few clicks I
mean that's really nice and also being
able to connect your own data to bedrock
um and I know some of the work uh a s
and uncor is doing jointly leveraging
Bedrock um in that in that framework is
something we can also talk about
especially you know around Cobalt
migration and whatnot but I think those
are all the uh you know tips I would
give that just start experimenting and
consider codess as part of the process
this is this is great right and this is
what we are seeing across the industry
right like there's a method of bringing
the power power of three right like the
the right AWS as the biggest kind of
Provider of technology and innovation in
this space and the codeless capability
to accelerate the journey I know
everyone's thinking actively about
prototyping but very quickly you to
consider how do we go from prototyping
to production in a scalable manner
similar to how you know everything
everything in technology and Innovation
needs to have that mindset of how do you
go from prototyping to production and
how do you Leverage The Power of of AWS
Oncor and the
kind of industry together to streamline
so it's as I said again very exciting
times um I'll close with the like please
reach out AWS onor reach out to either
Ary or myself would love to engage in
this conversation with the industry
there's a lot of work underway and I'm
very impressed by the amount of
excitement within the insurance industry
on adopting technology faster than I've
ever seen before and would love to be
part of the journey and and build this
together together so thank you Ary for
joining us today and really appreciate
your always a pleasure uh to be at ews
reinvent and super exciting times for
the industry ahead yeah thank you for
having me great conversation and yeah
anybody looking to jump into this and
start experimenting please reach out to
Faruk reach out to me we' love to help
you take care thank you
浏览更多相关视频
#440 保険不要論が浸透する現代の保険業界と淘汰される保険営業【保険不要論】
【AI×水産養殖】AIで持続可能な水産養殖を地球に実装する【産学連携】
Pie Insurance is revolutionizing insurance for small businesses with AI-driven solutions
NO RULES 第一生命が、アバターと営業やるらしい
ここまで進化したAIを活用しないのはもったいない!企業のChatGPT活用法とは
【セレブリックス】営業×生成AI/営業は商談以外の時間が多すぎる/正しいセールスプロセスを設計/最短5分で商談準備/生成AIと対話しながら模擬商談/AIを優秀な営業パーソンに
5.0 / 5 (0 votes)