AWS re:Invent 2023 - Catalyzing success: Max Life’s digital insurance revolution with PwC (AIM249)

Summary

マックス・ライフ保険のデジタル変革の旅を、AWSとPWCとの協力を通じて実現した戦略と成果について紹介されました。インドの保険業界において、新しいビジネス販売、顧客サービス、エンタープライズシステムの強化、データ駆動企業、デジタルファースト文化の構築という5つの主要なビジネス目標を達成する9つの戦略的柱を立てました。これにより、クラウドネイティブのソリューションを構築し、データのリアルタイム利用、AI/MLモデルの活用、デジタル技術と人材の育成を通じて競争力を高めました。

Takeaways

• 🎉 Max Life Insuranceはインドで活動しており、Max Financial ServicesとAxis Bankとのjoint ventureです。
• 📈 公司拥有約4.2百万の顧客と約5百万の有効保険ポリシーを保有し、総資産運用額は130億米ドルに達します。
• 🥇 Max Lifeは、保険金の支払い率という重要な指標で、4年連続で1位を維持しています。
• 🤝 Max LifeはAWSとPWCとの協力を通じて、デジタル化の変革の道を模索しています。
• 🌐 デジタル化戦略は9つの柱に分かれており、5つの垂直柱と4つの水平柱から成り立っています。
• 🛒 EコマースビジネスはMax Lifeの主要なビジネスオブジェクトの一つであり、インドで最も成功しているとされています。
• 🚀 クラウドの採用により、Max Lifeは新しいブランチの迅速な展開とデータのリアルタイム利用が可能となりました。
• 🔄 Legacyシステムの変革は、多様なアプリケーションやミドルウェアを再構築、再ホスト、再プラットフォーム化することで達成されています。
• 💡 AIとMLのモデルを活用し、カスタマーサービスを向上させることで、ポリシーの継続や顧客の獲得を目指しています。
• 🌟 デジタルファーストの文化を醸し出すために、適切な人材の確保と既存人材のスキルアップ、プロセスの整備が重要です。
• 📊 データの取り扱いと分析は、クラウドから最大限の価値を引き出すことができるかの鍵となります。

Q & A

マックス・ライフ・インシュアランスのビジネス環境の特徴は何ですか？

マックス・ライフ・インシュアランスはインドに展開し、マックス・フィナンシャル・サービスとアクシス・バンクとのjoint ventureです。約420万の顧客と500万の有効ポリシーを持っており、総保証額は1300億米ドル、資産管理額は1600万米ドルです。また、398の支店を有し、約22,000人の従業員と80,000人の代理店アドバイザーによってサポートされています。

マックス・ライフのデジタル変革の目的は何ですか？

マックス・ライフのデジタル変革の目的は、変化する消費者行動、厳しい競争環境、そして製品の迅速なローンチに対応し、クラウドを利用してビジネス成果を遂げることにあります。

マックス・ライフが選んだクラウドサービスプロバイダーは哪家ですか？

マックス・ライフが選んだクラウドサービスプロバイダーはAWSです。

マックス・ライフのデータ管理のアプローチは何ですか？

マックス・ライフのデータ管理のアプローチは、データ湖の設定、データの現代化、そしてAPIの現代化を含みます。

マックス・ライフのデジタル変革の9つの柱は何ですか？

マックス・ライフのデジタル変革の9つの柱は、eコマースビジネス、オンボーディングと発行、デジタル販売、顧客サービス、エンタープライズシステム、AI/ML分析、エンタープライズデータハブ、デジタルスキルと文化の育成です。

マックス・ライフのオンラインサービスの目標は何ですか？

マックス・ライフのオンラインサービスの目標は、有機的なトラフィックの100％の成長、オンボーディングと発行の改善、そして電子商取引でのポリシー発行の向上です。

マックス・ライフのデジタル変革のビジネス成果は何ですか？

マックス・ライフのデジタル変革のビジネス成果には、クラウドへのフロントエンドシステムの移行、ポリシー発行とアンダーライティングシステムのクラウドへの移行、データ湖アーキテクチャの構築、AI/MLモデルによるリスク管理の改善、デジタルファーストの文化の醸成が含まれます。

マックス・ライフのデジタル変革の過程で遭遇した課題は何ですか？

マックス・ライフのデジタル変革の過程で遭遇した課題は、管理層との期待値の設定、データ管理の重要性、クラウドでの運用コスト管理（FinOps）、セキュリティの継続的な焦点付け、そして既存システムの複雑性に対する正確な評価が含まれます。

マックス・ライフのデジタル変革の経験から得られた教訓は何ですか？

マックス・ライフのデジタル変革の経験から得られた教訓は、管理層の支援を確保し、データ管理を早期に取り入れ、運用コスト管理（FinOps）に注意を払い、セキュリティを継続的に強化し、適切な期待値を設定することが重要であることです。

マックス・ライフの今後のクラウド戦略は何ですか？

マックス・ライフの今後のクラウド戦略は、データのjourneyを終えた後、85-90％のワークロードがクラウド上に移動することを計画しています。これは継続的なjourneyであり、クラウド変革の重要なマイルストーンとなります。

マックス・ライフのデジタル変革の成功を評価する指標は何ですか？

マックス・ライフのデジタル変革の成功を評価する指標には、eコマースでのポリシーボリュームの増加、クラウドへのコアシステムの移行、そしてビジネスプロセスの改善が含まれます。

Outlines

00:00

📌 会議の開始とVamsiとManishの紹介

ビデオスクリプトの最初の段落では、Vamsiが参加者たちに挨拶し、会議の目的を説明しています。Vamsiは、戦略と成果の重要性を強調し、AWSとMaxのパートナーシップを評価しています。次に、クライアントのManishを紹介し、Max Life Insuranceのデジタル変革の道を話す予定です。Manishは、Max Lifeのビジネスモデル、市場規模、そして彼らのビジョンについて説明します。

05:03

🚀 Max Lifeの戦略とクラウドの役割

Manishは、Max Lifeの戦略の概念化と、クラウドが戦略的目標を達成する上でどのように役立つかについて説明しています。インドの消費者行動の変化、競争の激化、保険製品のリリースプロセスの加速化など、彼らが直面していた課題についても触れています。また、戦略の9つの柱（5つの垂直柱と4つの水平柱）についても詳細に説明しています。

10:05

🛠️ デジタル変革の具体的な取り組み

この段落では、ManishがMax Lifeのデジタル変革の具体的な取り組みについて説明しています。新しいビジネスの販売、顧客サービス、エンタープライズシステムの強化、AI/MLの活用、データハブの構築など、戦略の各柱について個別に取り組む方法を詳細に説明しています。また、クラウド技術を利用して、これらの取り組みをどのように進めてきたかについても語っています。

15:06

📈 成果と学び - Max Lifeのクラウド変革の旅

最後の段落では、ManishがMax Lifeのクラウド変革の旅の成果と学びについて話しています。彼らが達成した具体的な成果、例えばインドで電子商取引の保険ポリシーの販売量の増加、コアシステムのクラウドへの移行などについて触れています。また、同じような道を進んでいる他のCXOたちに向けて、重要な教訓をいくつか共有しています。それは、マネジメントの理解と支持、データの重要性、FinOpsの重要性、セキュリティへの継続的な焦点、そして期待値の設定などです。

Keywords

💡digital transformation

デジタル変革は、企業がデジタル技術を導入することでビジネスプロセス、文化、顧客体験を根本的に改善することを指します。このビデオでは、Max LifeがAWSとPWCとの協力を通じてデジタル変革の道を模索し、クラウド技術を活用してビジネス成果を出す様子が紹介されています。

💡strategy

戦略とは、組織が目標を達成するために長い見通しで計画し、決定を行うプロセスのことを指します。このビデオでは、Max Lifeが変革を成功させるために、戦略をどのように立て、実行に移したかが説明されています。

💡outcomes

成果とは、プロジェクトや取り組みが目標を達成することに対する具体的な結果を指します。このビデオでは、Max Lifeが期待する成果をどのように定義し、それを実現するためにどのような戦略を展開したかが示されています。

💡tech solution

技術解決策とは、特定の問題を解決するために使用される技術的な手段やシステムのことです。このビデオでは、Max Lifeがどのようにして技術解決策を選び、実装し、ビジネス成果につなげたかが語られています。

💡AWS

AWS（Amazon Web Services）は、クラウドコンピューティングサービスを提供するAmazonのサブブランドです。このビデオでは、Max LifeがAWSと提携し、クラウド技術を活用してデジタル変革を実現したことを強調しています。

💡Max Life Insurance

Max Life Insuranceは、インドで運営される生命保険会社で、Max Financial ServicesとAxis Bankのjoint ventureです。このビデオでは、Max Lifeがデジタル変革を進め、その成果について説明しています。

💡customer engagement

顧客エンゲージメントとは、企業が顧客と関係を築き、維持し、強化することに焦点を当てた戦略的取り組みです。このビデオでは、Max Lifeがデジタル技術を活用して顧客エンゲージメントを向上させた方法が紹介されています。

💡data modernization

データモダンIZATIONは、企業がデータを最新のフォーマットやプラットフォームに移行し、効率化することで、より価値ある洞察を得るプロセスです。このビデオでは、Max LifeがデータモダンIZATIONを通じてビジネス成果を出す方法が説明されています。

💡API modernization

API現代化は、アプリケーションプログラミングインターフェース（API）を最新の技術に合わせて更新することで、システムの統合性と柔軟性を高めるプロセスです。このビデオでは、Max LifeがAPI現代化を行い、その成果について説明しています。

💡digital first culture

デジタルファースト文化とは、デジタル技術を最優先して活用し、それを通じてビジネスプロセスや顧客体験を改善しようとする組織文化です。このビデオでは、Max Lifeがデジタルファースト文化を醸成し、その影響について説明しています。

💡FinOps

FinOpsは、クラウドベースのサービスにおいて費用管理と最適化を担当する機能です。このビデオでは、Max Lifeがクラウドサービスを利用する際にFinOpsの重要性を認識し、費用管理に注力したことが示されています。

Highlights

Max Life Insurance's digital transformation journey in collaboration with AWS and PWC.

Max Life Insurance operates in India with a joint venture between Max Financial Services and Axis Bank.

Max Life has 4.2 million customers and 5 million active policies.

The company has written 130 billion US dollars of assured business and manages $16 million in assets.

Max Life operates across 398 branches in India with a network of 22,000 employees and 80,000 agent advisors.

Max Life's solvency ratio is 1.27, and it leads in claim paid percentage for four years in a row.

The company's strategy includes a focus on e-commerce business, customer servicing, and enterprise systems.

Max Life's e-commerce business protection is ranked number one in India.

The company aims to digitize its distribution, scaling up from 200 to 400 branches in three years.

Max Life's strategy includes five vertical pillars aligned with top business objectives and four horizontal pillars for delivery.

The company has embraced cloud technology, with a focus on security and data modernization.

Max Life has moved its core policy admin system to the cloud, becoming the first live insurer in India and the second in the world.

The company has refactored its front-end systems for customer engagement at scale.

Max Life has implemented AI and ML models to enhance decision-making and customer servicing.

The company has transitioned to a data lake architecture for real-time data availability and analytics.

Max Life has focused on building a digital-first culture within the organization.

The company's cloud transformation journey has seen 70% of workloads moved to the cloud, with a target of 85-90% in the near future.

Max Life's key takeaways include keeping management engaged, prioritizing data, focusing on FinOps and security, and setting realistic expectations for core system migrations.

Transcripts

- [Vamsi] Hi everyone.

Warm welcome. Very pleased to be here.

Hopefully you're all having a good conference.

You have got your extra steps in over the last three days.

In this session, what we wanted to do was highlight outcomes

and how outcomes, and having the right strategy

led to the right tech solution.

While you will see a lot of tech solutions around.

For us, we are extremely pleased to partner with AWS

and Max,

and drive sustainable outcomes.

So it is great pleasure to share the stage

with our client, Manish.

What we will briefly talk about is, you know, who's Max Life

and followed by the digital transformation roadmap.

Starting with strategy and how the strategy

has been realized with the proper tech solution,

and what were the business impact outcomes.

So with that, Manish, over to you, yeah.

And introduce Max Life. Yeah, here you go.

- Good morning. I'm extremely excited to be here

and talking about Max Life digital transformation journey

in collaboration with AWS and PWC.

Quickly to talk about Max Life Insurance.

Max Life Insurance operates in India.

It's a joint venture between Max Financial Services

and Axis Bank.

Axis is a leading private bank in India.

We have about 4.2 million customers

and about 5 million policies, active policies.

Max Life has already written 130 billion US dollars of

some assured, and it has about $16 million

of asset under management.

Max Life operates in 398 branches across India.

About 22,000 employees supported by another

80,000 agent advisors who sell policies

for Max Life Insurance on a commission basis.

We are a financial healthy organization.

Our solvency ratio is 1.27.

And one important

metric on this is our claim paid percentage.

This number is total number of claims logged

versus total number of claims paid

by an insurance organization within a given year.

We are number one on this metric four years in a row now.

And it's a very, very important metric.

India tracks it very closely

and important for our business.

On this slide, it just talks about

what sets us apart in the journey so far.

Max Life began in 2001.

We have been in operation for 23 years now.

Some of the key milestones at the bottom

I'll just touch upon are tie up with important banks.

Bank insurance is very important for us.

About 65% of our business revenue comes from banks.

In 2005, tie up happened with YES Bank.

In 2010, with Axis bank, which who is now our JV partner.

About 55% of our revenue comes from Axis bank.

It talks about how steadily the asset under management

is increasing and

how the claims paid percentage has been

increasing year on year.

Two important data points on this slide is that

despite the socioeconomic challenges,

including COVID in last five years,

while the entire insurance industry in India grew

by a lower single digit percentage,

Max Life reported a healthy 15 year

CAGR growth over past five years.

And for this year, our target is to garner about $1 billion

of premium income, new business premium income,

and about $2 million of renewal income.

So that's Max Life, Vamsi.

- [Vamsi] Thank you.

Thank you Manish. So we've been fortunate enough as PWC

to partner with Max at a very pivotal point,

just when some of the background challenges

and industry forces that Max was dealing with.

You know, we've partnered with them initially

for cloud transformation.

The first tranche of work that we have helped them with,

was moving their workloads

to cloud securely, followed by modernizing some

of their core applications.

And now over the last 12 plus months,

we have been involved in modernizing their data estate.

First, initially by setting up a data lake,

followed by data modernization initiatives

and also API modernization initiatives.

So, very pleased to be part of this journey, very privileged

to be associated with a brand like Max Life.

But I think it's important to understand

how did this journey start?

And as I said at the beginning, for us,

driving outcomes

and helping achieve sustainable,

you know, outcomes is critical.

And for us, tech comes closely next to

how do you solve some of these business problems.

So Manish, if I can request you to walk us through

the conceptualization of strategy

and then how did cloud

help achieve those strategic measures?

That'll be great.

- Sure. So this is the comprehensive

strategy, which we laid out

three-three and a half years back.

It's a pretty heavy slide,

but I'll just dissect it for all of you.

But before we get into the slide, it is important to note

that what was the context when we created this slide?

There were three important things which we had in our

mind when we were creating it.

One, the consumer behavior in India was changing a lot.

The millennials, the Gen Z, they were dealing

with the platforms like e-comms, OLAS

and Ubers, instant gratification one and done.

All these things were table stakes.

And even banks,

all the transactions, nobody has to walk

to bank branch, everything is online.

And therefore for insurance company also,

it had become very, very important that that we

you know, provide all of our services

on a DIY portal, rather than asking consumers

or customers to walk in or interact with agents.

The other two things which are important was, one,

because of regulation changes,

the competition in India was becoming very fierce.

For example, in banks earlier, there was only one insurer

who was allowed to sell policy for that bank.

But with the regulation changes,

there are about nine insurance companies

who can sell on the same counter.

And therefore, the competition between the insurers

on a bank counter becomes so fierce that winning

in that competition became very important.

The third important thing which happened was

that at one point of time, the process

of launching an insurance product in India

was about two to three months process.

But some regulation changes happened

and the process was relaxed.

And from there, what has happened is what we used to do

about three years back, say five to six interventions

of products in a year, that changed to about 40,

which we are doing as of now.

So five to 40, that is the kind

of change which was broadened

because of these regulation changes.

And it is reasonable to understand

that setting all those changes up

and rolling it out to field on a legacy infrastructure

wouldn't have been possible.

So that is why we, you know, kind of drafted this

strategy and it has nine pillars in it.

And if you will notice there are five vertical pillars.

And then there are four horizontal pillars.

Okay? The five vertical pillars are aligned

with our top business objectives.

And then these four verticals are not business

objectives, but they're required to, you know,

deliver these five objectives.

That's how it is thought through.

So number one, the first three are

about new business sales.

So number one is our e-commerce business.

While I told you that we are the fourth largest

life insurance company in India.

But when it comes to e-comm business protection,

we are number one in India consistently.

And it was very important for us to, you know, kind

of continue that lead.

And therefore, that was one key thing,

which is on this slide,

a growth of organic traffic, about 100%.

That's the target we took. Onboarding and issuance,

about one in five policies come from onboarding

from our e-commerce platform.

The rest of the policies are sourced by our

offline feet on street, our sellers.

It was important to create a very comprehensive solution

for them so that they're able to, you know,

kind of sell policies, create very good experience.

And we should be able

to issue those policies without any human intervention.

And therefore, insta issuance,

which essentially means over the counter issuance

and humanless underwriting

because we underwrite the risk, was key KPIs,

which we took over there. Digital sales, all

of our distribution was manual

at that point of time,

when we created the strategy.

We had about 200 branches at that point of time.

In three years, we have scaled up to 400.

I just shared that on the previous slide.

This kind of ramp up wouldn't have been possible unless

or until there's digitization, so that you're able to,

you know, kind of copy paste

that frame in every subsequent branch, centrally monitor it,

and then make them productive as quickly as possible.

So that was the third vertical.

The fourth one, like I said, is customer servicing,

enabling self-service to about 85%

of transactions was one of our aspiration at that time.

And then enterprise, some of the enterprise systems,

while they're backend, but they're important

for enforcing policies.

Say our treasury system releases the NAV, which is used

for enforcement of policy.

If that gets delayed, policies won't get issued.

Similarly, the anti-money laundering checks,

Indian regulations necessitates that the regulation,

the checks are done before you issue the policy.

So those systems were supposed to be, you know, kind

of spruced up so that

they support issuance, along with security.

We knew that we are going to embrace cloud

and security is going to become key focus for us.

So that became the fifth vertical.

Now talking about horizontals, our AI ML

work analysis, which can be embedded so that the systems

of engagement can create the vow

and we are able to give the right kind of nudges.

The next best actions for our sellers, customers

and employees was one horizontal.

Our enterprise data hub from

the siloed data sources

to one comprehensive

data lake architecture, one enterprise data hub,

along with the modernization of legacy systems,

because that wouldn't have been possible without

was another horizontal layer.

And last eight and ninth enough has been spoken about it in

last three days on this,

the digital talent and digital culture.

How do we bring in, how do we attract new talent?

Who will be able to do this, execute it,

and at the same time, how do we build this culture across

the organization so that everybody starts

seeing it the same way, start moving in the same direction

and helps us deliver this.

So what we did was

that we worked on four dimensions.

And out of these four dimensions, if you look at

the bottom left corner, which is the digital first culture,

that is a dimension which is about people and processes.

Remaining three dimensions are what, you know,

where we leverage cloud.

But I have mentioned this fourth one also over here

because it is important to understand that unless

or until we work on this dimension, we will not be able

to achieve anything because, after all, we need people

and processes through, who you know, kind of

deliver what we aimed for.

So the first one is customer engagement at scale.

Like I said, all of our front-end assets,

wherever the customer's interactions are happening,

we refactored all of them.

So typically three, our e-comm platform,

our onboarding journey, which was being used

by our offline sellers to sell policies

and our customer service portal

through which the customers were coming for servicing.

The way the reality emerged in India

is that for our onboarding journey,

the business is set up in such a way now that

out of 30 days of business,

there are definitely three, four days out

of those 30 days when the business volume's about four,

five times of the usual volume of the other days.

This kind of variability in the business

wouldn't have been possible

on a traditional architecture.

So therefore we built a complete cloud native solution

for our onboarding journey.

Similarly, being on top

of Google search was extremely important for our e-comm.

The delivery of sub-second page load time

having best of the best content, creating the

best of best in class experience was important for us

to remain number one in e-comm channel.

And that's what we did through this.

And eventually we reached to about 89%

of self servicing

through our digital corporate portal.

The second is legacy transformation.

Again, we picked up a multi-model strategy here.

There were plethora of applications, middleware, as well

as our core policy admin system.

We refactored, re-hosted, and re-platformed,

depending on what kind of application was there.

To talk about one of the example,

our policy issuance and underwriting system,

it had workflow. What we did was we changed

and we reconfigured it in such a way

that rather than coding our business rules now,

we were configuring them.

It integrated with all the publicly

available APIs, bank APIs,

so that rather than asking information from customers,

it, you know, takes that information

automatically from those sources,

eliminating humans from, you know,

validating the information which is coming in and, you know,

therefore enabling insta issuance.

The other thing is our poor policy admin system, no matter

how good we do in our front-end applications,

it's extremely important that we are able

to process everything within the same day

and then pass on that information to our data stores so

that from there the analytics can be passed on

to the front-end assets to engage with the customers.

So we have two months back, re-hosted

our core policy admin system also.

And we are the first live insurer in India to do that,

to put our core policy admin system on cloud.

And we are also the second live insurer

in the world to do that.

So that's what we did.

Data driven enterprise enough has been spoken about

data also in past three days.

What we needed was to move from data silos

to a data lake architecture,

which will enable realtime availability of data

for reports, analytics, data.

And the other thing is all of our AI ML models,

because now that we had our front-end assets,

the velocity volume

and the variety of data had changed dramatically.

We needed a common place where we could,

store all this data

and then run AI ML models on top of it to, you know, kind

of enable decisioning at the time of customer engagement.

To give you a couple of examples in order to, you know, kind

of issue policies on the fly, we had to raise

our limits of underwriting rules

and therefore, so that more policies can pass through.

But that would've brought in a lot

of risk in order to carry that.

We wrote a lot of AI ML models,

which depending on the demography, geography,

and the age, education,

the income of the customer,

it was pointed.

It was actually surgically taking out

some of the customers, not all.

And, you know, raising them as high risk customers so

that more due diligence can be done on that.

And, so that we don't take any undue risk on our books.

The other examples are some

of the AI ML models we have written

to enable our customer servicing so that,

we are able to anticipate who are the policy,

who are the customers, who are likely

to lapse their policies, who are the customers

who are likely to surrender their policies so

that we can upfront go out, engage and retain them.

Last but not the least is digital first culture.

I must share two things.

One, getting in the right kind of resources,

setting them in our environment

and at the same time, you know,

upskilling our existing resources

so that people can work in harmony with each other.

They can empathize with each other's point of view.

Truly setting up a structure

so that not only digital technology

but people in business also are, you know,

educated and upskilled,

so that they are able to together work

was one key thing, which we picked up over there.

The other thing is right kind

of processes, right from top to bottom.

Say setting up processes like DevSecOps,

setting up rituals with management so that they understand

what is being done, what is our cloud journey

and how we are, you know, so

that we get right kind of sponsorship, right

kind of resource commitment from the overall organization.

And we move forward together is something

which we did in this vertical.

So all in all put together,

after doing this, we have been able to move off

all of our front-end systems, all of our front-end systems

of engagement on cloud.

About 70% of our workloads at this point of time running

on clouds,

and within about say next two quarters.

And that is our data journey, which we are working

with PWC on is gonna get completed next quarters

and then about 85, 90% of workloads pretty much are going

to be on cloud.

And that, you know, while it's a continuous journey,

but that's a landmark in our cloud transformation journey.

- So thank you so much Manish.

I don't know if you picked up on these three points.

Number one, in terms of e-commerce

policy volumes in India.

The first in India to move the core system to cloud.

The second in the world

to move to cloud the core system.

So those are some really impressive numbers

and also other things on the slide, I'm not going to drain.

So Manish, with this kind of success,

I'm sure the journey would have had its

own set of experiences and learning.

So, you know, just as a last point, if you were

to share in this impressive journey, some fantastic outcomes

for the business, what is your single largest takeaway

that you can share with fellow CXOs who are

on a similar journey or planning a similar journey?

- Okay, so I have a couple

and I'll just, you know, divide it into two buckets.

One is when you are on the journey,

when you're beginning the journey.

I think two, three things which are very important is, one,

keeping your management in your camp.

It's very important to reach out, engage,

let them know it's a very long-term commitment.

There're gonna be highs and lows.

You will make mistakes, tons of mistakes,

but it's very important that everybody sees it the same way

and be with you and understand the benefits of it.

The other thing is that data cannot be an afterthought.

We also, you know, kind of made that mistake.

We started our data journey a little late with PWC

but we also wish that

we could have started a little

sooner, but the point is you'll be able

to extract best value out of the cloud only

and only when you're able to juice out, when you're able

to monetize the data, which you're getting

generated from there.

The other side is once you have done significant part of

that journey on cloud, I think

FinOps becomes very, very important.

If you just take your eyes off it,

it can really burn a very big hole in your pocket

and that can, you know, raise a lot of questions on

what you guys have done and what you guys have achieved.

So therefore, very, very important,

FinOps. Continuous, continuous focus on security is

another very, very important matter.

And I'll just add one more,

last but not the least, set the expectations right,

specifically on your core systems.

It's very easy to say that you'll be able to migrate

and say maybe three months, six months,

but when it comes to complexity of your legacy applications,

what our experience tells us

that there is always a long tail setting up

right expectation with your management,

with your business stakeholders is always important.

That while you will be able to move a large chunk,

but then there is a long tail

and all of us will, you know, continuously work

on it and move forward together. That's what we do.

- Thank you so much. Thank you, Monish.

- Thank you. - Thanks everyone.