OLM Insurance Summit 2020: Claim Settlement and Best Practices
Panelists will discuss the pandemic’s impact on the claim settlement ratio. Challenges insurers are facing in maintaining healthy claims settlement ratio. Digital fraud detection mechanisms and steps insurers are taking behind the curtain to train their team for digitally handling a spurt in claims
Bhargav Dasgupta, MD & CEO, Aditya Birla Gen Insurance
Mayank Bathawal, MD & CEO, Aditya Birla General Insurance
Asish Kumar Srivastava, MD & CEO, PNB Met Life
Dr. S Prakash, MD, Star Health & Allied Insurance
Moderator: N Mahalakshmi, Editor, Outlook Business
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Bhargav Dasgupta, MD & CEO, Aditya Birla Gen Insurance
Mayank Bathawal, MD & CEO, Aditya Birla General Insurance
Asish Kumar Srivastava, MD & CEO, PNB Met Life
Dr. S Prakash, MD, Star Health & Allied Insurance
Moderator: N Mahalakshmi, Editor, Outlook Business
#Money #OutlookMoney #OutlookMagazine #OutlookGroup
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NewsTranscript
00:00 (upbeat music)
00:02 - So welcome gentlemen to the panel discussion
00:21 on claim settlement best practices.
00:22 I have with me a very diverse and eminent panel of speakers.
00:28 Bhargav Dasgupta, MD and CEO, ICICI Lombard General Insurance
00:32 Mayank Batwal, CEO, Aditya Birla Health Insurance Company,
00:35 Dr. S. Prakash, Managing Director of Star Health
00:39 and Allied Insurance, and Ashish Kumar Srivatsav,
00:43 MD and CEO of PNB MetLife Insurance.
00:45 Gentlemen, thank you so much for taking the time out
00:47 to be with us today.
00:49 So gentlemen, please allow me to start this discussion
00:54 with an issue that is really, to my mind,
00:57 at the heart of this discussion around claim settlement,
01:01 which is that across the world,
01:03 the insurance industry is the one
01:06 that is the least trusted amongst customers
01:09 and companies don't trust customers,
01:12 customers don't trust companies
01:14 and we are caught in this circle of mistrust.
01:17 First of all, what has got us to this position
01:20 and how do we really break this circle of mistrust?
01:25 Anyone can take that question.
01:27 - So that's a tough question, Mahalakshmi.
01:31 So if you're okay, I can try to answer part of it.
01:34 And I guess collectively,
01:36 we can probably answer your question.
01:37 So what you said is absolutely correct,
01:40 that there is, by the basic design of insurance,
01:44 there is a potentially a breach of trust that happens.
01:49 Let's understand the dynamics, right?
01:51 So when you look at insurance,
01:54 you look at pulling together a small premium
01:57 from many people and you expect that few people
02:02 will suffer some kind of a disaster,
02:05 an accident or a health event or whatever it might be,
02:08 and you pay out of that pool.
02:09 Now, one of the responsibilities that we have
02:13 is to keep the premium low,
02:14 because if the premium isn't low,
02:16 then too many people don't come into the pool
02:18 because it just becomes too expensive.
02:20 And if you look at the premiums that we charge,
02:22 typically would be one or two rupees
02:25 for the total sum insured of, let's say, 100 rupees.
02:27 I'm just giving you a rough number.
02:29 It varies across different types of insurance.
02:32 So what happens is if,
02:34 the expectation is that there is what we call
02:37 utmost good faith,
02:38 which means that we trust the customer
02:40 to give us full information when they come in.
02:43 And because if they come in with existing diseases,
02:47 let's say for health,
02:48 then that model fails because you'll have many people
02:51 who will come in with small premium
02:53 and they will take a big claim.
02:54 And if too many people do that,
02:55 then the pool mechanism fails.
02:57 So one of the things that insurers do is,
02:59 first, they do a lot of underwriting
03:01 to select people to come into the pool.
03:03 Now in medical, you realize that a lot of things
03:06 you cannot control even through underwriting
03:08 because you can manage even that process.
03:10 And at times you find people who come in with diseases,
03:15 which without disclosing all of that to us.
03:18 The second thing that happens is in our industry,
03:21 the service is provided by a third party.
03:25 So a health insurance claim is consumed in a hospital.
03:29 And at times there is an adverse incentive
03:31 for hospitals to inflate bills.
03:33 So we have to get in and look at each of those bills
03:36 and control unnecessary expenditures.
03:40 Because if unnecessary expenditure happens,
03:42 again, the premium will go up
03:43 for the rest of the population.
03:45 So there is a bit amount of friction at many stages,
03:48 which creates a bit of distrust
03:49 because a lot of people may not understand
03:51 why we are doing this.
03:52 If we don't do this,
03:54 what will happen is the premium
03:55 for the rest of the population who are honest
03:57 and who are genuine and who are coming for good reasons,
04:00 the right reasons, for them the premium would go up.
04:03 But it's difficult for insurance companies
04:04 to eliminate who is a priory,
04:07 who is potentially misusing the system and who is not.
04:10 And hence at times,
04:11 everyone kind of goes through a difficult journey.
04:14 And that probably at times creates a bit of trust deficit.
04:17 - Sure.
04:18 And how do we really reinstate this trust, Dr. Prakash?
04:23 Because this is like a chicken and egg,
04:28 who is going to address the problem first?
04:31 And collectively, even as a society,
04:34 do we really have some sort of a mechanism
04:36 to get people to behave in a certain way?
04:40 What can insurance companies do?
04:43 - Thanks, Mahalakshmi.
04:46 Actually, the insurers have to approach at three levels,
04:51 at the customer level, at the hospital level,
04:53 and at the organization level.
04:56 So the customers, they should understand
04:58 as Mr. Bhargav rightly said,
05:00 we are only custodian of the common fund.
05:03 And insurance is supposed to be for protection.
05:07 It is not an entitlement.
05:09 So this message should clearly reach the customers
05:11 and to that effect, we have to train the intermediaries
05:15 who work to distribute the insurance business.
05:18 And we design the product,
05:20 but when it comes to delivery of services,
05:23 customers do not come to us, they go to the hospital.
05:26 And the hospitals are not aware
05:27 of 33 plus insurance companies
05:29 having 500 plus different products.
05:31 So naturally there is a design delivery disconnect.
05:35 And this has to be addressed.
05:37 So a good communication with the hospitals,
05:40 constant effort to bridge the gap
05:42 between payer and provider.
05:44 Already a lot of industrial bodies
05:46 are taking these initiatives.
05:48 Constant effort should be taken to bridge this gap.
05:52 Insurers should have a good understanding
05:53 of what is happening in a hospital.
05:56 And insurers should have a mechanism
05:58 to recognize and identify quality players.
06:00 That is in fact the first way to eliminate fraud.
06:04 At the same time, hospitals also should understand
06:09 the nuances, the objectives,
06:12 noble objective of the health insurance,
06:14 and they should work in tandem
06:16 with the requirement of the insurance.
06:17 Because both of them should understand
06:20 that both the hospitals and insurers
06:22 should coexist for this ecosystem to flourish.
06:26 - Mayank, you've been in insurance all along.
06:31 And what is your experience in terms of where is,
06:36 is there an education gap?
06:38 And what is it that we can really address
06:41 through better communication?
06:42 And what part of it is something that we have to just
06:46 take for granted that is not gonna change?
06:48 - Yeah, so I'll probably try and add to what
06:54 Bhargav and Dr. Prakash mentioned.
06:56 So see, I'm talking specifically, of course,
07:00 of health insurance.
07:02 When a customer is buying a health insurance product,
07:05 the product per se is linked to health conditions, right?
07:09 So even if you want to really make it as simple
07:13 as you wish to be, there are medical conditions,
07:16 et cetera, involved in the way product is,
07:19 the benefit that the product is trying to cover.
07:21 So sometimes in layman's language,
07:24 I mean, they tend to become a bit of jargons
07:27 because sometimes medical terminology
07:29 is to define conditions and all might differ.
07:31 So even if you standardize,
07:32 there is still a possibility of a confusion.
07:34 Plus, to make sure that the price is effective
07:39 and there are some benefits like exclusions
07:42 like to your waiting period for let's say,
07:44 a cataract operation.
07:45 But if you were to allow it day one,
07:47 then there is possibility of anti-selection, right?
07:50 That the customer will buy it.
07:51 Anyone who wants to go for an operation will buy it
07:53 and go for it tomorrow.
07:54 So typically there are some benefits which have
07:57 either exclusions or waiting periods and so on and so forth.
08:00 Now, the question is how effectively do you make sure
08:03 that the customer understands what's really covered
08:06 and what's not covered in the benefit
08:08 for what period or et cetera?
08:10 And how do you make sure that they understand it
08:12 in the language that they can, right?
08:14 That's the, to me, a challenge that the industry faces.
08:18 And one way to do that is just remove all exclusions.
08:22 Just make it everything is covered.
08:23 Of course, if you do that,
08:24 firstly, it has to happen for the entire industry.
08:26 It can't be that's one player.
08:28 For example, in South Africa,
08:30 where our partners come from,
08:31 there are minimum prescribed benefits.
08:34 You virtually cannot have an exclusion.
08:36 But everyone does that.
08:37 And then the product becomes very expensive
08:39 because now, anyone who needs a condition,
08:42 they'll end up buying the product and so on and so forth.
08:45 So that's a journey to travel.
08:46 I think RADA has already made an effort
08:48 to kind of remove some exclusions lately
08:50 in the standard product.
08:52 So I think the effort has to be one
08:54 at an individual player level
08:56 that they put all efforts in the selling process,
08:58 in onboarding, let's say when you onboard a customer,
09:00 do a calling and re-explain the benefits.
09:03 And some at the industry level
09:04 that some of these benefits,
09:06 which are in any case,
09:08 standard exclusions or waiting periods across all products,
09:11 how do we as an industry do that?
09:13 So in that context,
09:14 industry did start a whole campaign around awareness
09:19 just pre-COVID,
09:20 unfortunately, because of COVID,
09:21 that campaign has got deferred a bit.
09:26 And I'm hoping that we can revive it as soon as we can,
09:29 because those are efforts
09:31 where customers start understanding benefits
09:33 and so on and so forth.
09:35 And that effort has to be made
09:36 by the entire industry together,
09:38 plus each player.
09:39 I do want to add one more point though,
09:42 that's not the specific question you asked me on,
09:44 the claims experience.
09:45 Please understand that the claims experience today,
09:48 not just about exclusions or deductions or non-payment.
09:53 One of the reason why customers are unhappy is the time,
09:56 just the sheer time
09:58 and the experience that they go through in hospital.
10:00 I mean, for example, if you're getting discharged,
10:02 an insurance customer will take three, four hours more
10:04 than a customer who's paying cash.
10:07 Why does it happen?
10:08 Because they have to get approval
10:09 of the insurance company and so on and so forth.
10:11 Why does that happen?
10:12 Because the paper is flowing
10:14 in the most archaic manner in India today.
10:16 Technology integration between payer and provider,
10:19 which is so important,
10:20 that's just not there.
10:22 And I think that is an effort
10:24 which one single player can never make.
10:26 It has to be at an industry level.
10:27 There are international standards of pipes,
10:30 technology pipes between payers and provider,
10:33 which makes data and information flow through so seamlessly
10:36 that the experience is actually much better
10:38 than even a cash paying customer.
10:40 Those are journeys that we have now started.
10:42 I'm hoping that we can expedite it
10:44 also through the national mission, health mission,
10:46 and also IRDA is trying to IRB.
10:49 So it's a journey, Mahalakshmi,
10:50 and I think we all have to do it, make it happen together.
10:53 - Sure, I'm going to come to that point
10:56 on efficiency in a bit.
10:57 But before that, Ashish,
11:00 on this point of very pertinent point of exclusion,
11:02 because this is one of the grouses everyone has,
11:06 that you buy an insurance
11:07 and then you see that this is not covered.
11:10 At what stage of the industry
11:13 or at a certain level of penetration or numbers,
11:17 would it really make sense for,
11:19 or one can hope that exclusions
11:24 be completely done away with?
11:26 Because I would tend to think
11:28 that it is a question of arithmetic.
11:30 - Yeah, so Mahalakshmi,
11:34 you pose a very interesting question.
11:36 So, and my friend, Mayank Bhargav and others,
11:41 they spoke about it.
11:41 So it's not very different with life.
11:45 If you want to have a policy with no exclusions,
11:48 the price point,
11:51 because we also have customers
11:53 who are very price sensitive in India,
11:55 and the price point will be much higher.
12:00 In some cases, it may not be even affordable.
12:02 And the good thing is,
12:07 the good thing is Mahalakshmi,
12:09 players like us, for example,
12:12 with a very strong parentage,
12:14 met life with 152 years of insurance experience globally.
12:20 We are bringing in sort of products and solutions,
12:24 which are sort of acceptable across,
12:29 and are bringing to India.
12:31 I think the point is that if we can improve our technology,
12:36 for example, we are now,
12:39 some players have adopted it,
12:40 we've also started it.
12:42 We've started looking at pre issuance video verifications,
12:47 where we speak to the customer,
12:48 we can see the customer,
12:50 customer agrees to a certain,
12:52 we explain the product,
12:55 the customer is getting to know more,
12:59 we are doing analytics, et cetera, et cetera.
13:01 So as the awareness grows,
13:06 as people get to understand the insurance products
13:09 more and more,
13:10 they buy according to their needs,
13:13 which is again, one of the mandates that even IIDA has.
13:18 For example, in this COVID situation,
13:21 all of us sold a lot of what we call protection products,
13:25 the term insurance,
13:26 and that's the need of the hour.
13:28 And there are no exclusions there.
13:30 It's a simple product, it's term,
13:34 you buy it, there is a big cover,
13:36 and things will, and everybody's happy.
13:39 The improvement that we've seen, Mahalakshmi,
13:44 while I understand it's a complex product
13:47 and therefore it may lead to some dissatisfaction,
13:51 the matrices, if I look at customer complaints,
13:56 and they are coming down,
13:59 as technology improves, as analytics improves,
14:02 as customer propositions improve,
14:06 customer complaints are coming down,
14:07 claims, you know, is a public disclosure.
14:11 - Right.
14:12 - And you look at the claims experiences,
14:13 98, 99% claims experiences.
14:16 So things are improving.
14:19 And as we improve, as customers start looking
14:23 at these claims numbers,
14:25 you know, the belief in the system will grow.
14:28 And, you know, unfortunately COVID has,
14:31 has, you know, let people to, you know, now,
14:37 you know, understand, you know, it's a,
14:39 it's a, you know, negative situation,
14:42 but in some sense, the awareness on insurance has gone up.
14:46 And I do hope, you know, we, you know,
14:49 as an industry can use this to say,
14:54 to stand by, you know, the customer
14:56 and sort of increase the belief in the system.
15:00 - What you said is very well taken,
15:04 but you haven't answered my question
15:05 on how far are we from a world of no exclusions?
15:10 What would it take to create a world
15:14 where anybody who buys a health insurance
15:16 can sleep well at night thinking that whatever happens,
15:20 my company is, you know, going to honor the claim
15:24 and it's not going to be,
15:25 it's not going to be a burden on me.
15:27 - Okay, so I'll try and, you know,
15:31 you know, give it a go once again.
15:34 - For example, of course,
15:35 United States is not the best example
15:38 when it comes to health at all.
15:41 Yet, you know, at least when you buy an insurance,
15:43 you know that, you know, you are safe to that extent.
15:46 Of course, the cover may be less this, that,
15:48 and the other, that's a different story altogether.
15:50 Still, you know, you paid for something
15:54 and it's not going to get rejected.
15:56 - So, Mahalakshmi, I think, you know,
15:59 one of the things which would help is data.
16:04 And, you know, when we design products,
16:07 we, you know, there are various assumptions
16:09 at the back end.
16:11 And the assumptions are also based on the data
16:13 which is available.
16:14 Now, in India, and you're right, you know,
16:17 you're comparing it, you know, say with US.
16:19 Now look at, you know, how much data is available,
16:23 what are the disclosures, medical history,
16:27 you know, medical centers,
16:30 all the infrastructure which is there
16:34 to support the assumptions and therefore the experience.
16:38 Otherwise, as, you know, the other panelists
16:41 were talking about, you know,
16:43 there is a certain basic principle that we, you know,
16:46 work on, you know, that principle wouldn't work.
16:49 And unfortunately, the disclosure norms,
16:52 the basic infrastructure is not available
16:56 for us to improve those assumptions on our own.
16:59 - Right.
17:00 - And till that happens, I think, you know,
17:03 we will have to live with, you know,
17:06 certain exclusions, as I said, you know,
17:09 things are improving.
17:10 We are now getting more and more customer centric
17:13 and explaining to the customer that, okay,
17:15 this is what you are, you know, you are buying.
17:17 So I think there will be, there is improvement,
17:22 but there's still some way to go.
17:24 - Sure.
17:25 - Can I try and dig, you know,
17:27 can I take a try at that question of yours, Mahakshmi?
17:30 See, insurance is a concept of anti-selection
17:34 that, you know, you can't create a product
17:36 where people who necessarily need that insurance
17:39 only buy that product, right?
17:41 That's a core principle of that you cannot, you know,
17:44 you have to avoid and eliminate anti-selection.
17:47 So, you know, you ask that question that, you know,
17:49 how can you remove exclusions?
17:51 You know, corporate product, for example,
17:53 there is, you know, typically there are no exclusions.
17:54 Everything is covered.
17:55 Why?
17:56 Because there is no anti-selection.
17:57 Everyone in the company is covered.
17:59 So the moment you eliminate the risk of anti-selection
18:03 and use, for example, technically, if you say,
18:05 everyone in India has to buy insurance
18:08 and no one can go without insurance,
18:09 you can remove, you know,
18:10 potentially as many exclusions as you want,
18:13 because then you're not, you know,
18:14 running the risk of only people
18:16 who really need insurance buying insurance.
18:17 So I think that's a key from a principle perspective issue
18:20 that you have to eliminate.
18:22 - Sure, sure.
18:24 All right, so coming back to the point on efficiency,
18:32 you know, everything's gone digital
18:35 and I presume that pre-COVID also,
18:39 digital would have accelerated in many ways
18:43 over the last three years.
18:44 But Bhargav, can you expound on how post-COVID,
18:49 are there any procedures that have got eliminated?
18:53 How has this whole claim efficiency improved post-COVID
18:58 and how much of it do you think has a secular impact
19:02 in the sense that it's got more efficient for the good?
19:06 - Yeah, so I'll answer that question,
19:09 but before that, I just want to touch up
19:11 on the earlier question that you asked
19:13 and add to what both Ashish and Mayank said,
19:18 because this is a very important aspect to understand
19:20 for your readers and, you know,
19:22 this is important for, as an industry,
19:24 for us to communicate what, you know, what it means.
19:27 So when you talk about the US example,
19:29 it is actually the same group format
19:31 that Mayank talked about.
19:32 Most of the insurance, health insurance is actually
19:35 through corporates who buy insurance
19:37 for all their employees.
19:39 In India, all group policies come without exclusions
19:42 in terms of, you know, pre-existing and, you know,
19:44 the time period caps that we have.
19:46 And that is because of the reason that Mayank said,
19:48 that we don't worry about the anti-selection.
19:51 And I'll give you one more statistic,
19:53 which probably will emphasize the point,
19:56 which is, if you look at,
19:57 there was a few years back a WHO report,
19:59 which talked about the frequency of incidence rates,
20:03 which means that out of how many, out of a hundred Indians,
20:06 how many people fall sick in a year?
20:08 That number for the nation was about two to 3%.
20:11 For retail insurance pools, where these exclusions come in,
20:14 I don't have the industry statistic,
20:17 but my guess is, based on anecdotal evidence,
20:19 is it will be about 6, 7%, maybe around 7%,
20:23 which shows that you anyway have a lot of anti-selection
20:25 that is happening.
20:26 People buy insurance without disclosing
20:29 that they have a disease that they want payment for.
20:32 So that's something that we have to keep on guarding against.
20:34 And the second point that I would,
20:36 so if you really want no exclusion,
20:38 it has to be universal coverage,
20:39 the point that Mayank made.
20:41 But there's one more progress that has happened,
20:43 which potentially can, you know, improve things,
20:45 which is the digital health stack.
20:47 So if you have your health record available,
20:50 you know, to the insurer,
20:51 then you could, you know, trust the data and, you know,
20:54 give policies without too many exclusions,
20:56 too many, you know, time periods.
20:57 And that's a good progress that we are seeing,
20:59 you know, from the National Health Agency.
21:02 Coming back to your specific question on digital.
21:05 So yes, I mean, you know, for all of us,
21:07 going digital has been the way, you know,
21:10 for quite some time,
21:11 but obviously COVID has accelerated that journey.
21:14 So I'll give you a couple of examples.
21:16 So one of the things that has happened is,
21:18 we talked about the fact that there is a lot of paperwork
21:22 that happens between the provider and the payer.
21:26 In the past, we used to have a lot of faxes,
21:29 people would send, you know,
21:31 claim documents in, you know, through mails.
21:33 That was a high percentage.
21:35 During COVID, one of the things that the industry did,
21:39 and the regulator completely supported that,
21:42 was to move everything into scanned document.
21:45 We do not necessarily insist on physical copies of paper,
21:48 we work on scanned documents.
21:50 I can speak for ourselves and ICJ Lombard now, today,
21:53 95% of the claims that we settle on health
21:56 is without any physical intervention.
21:58 It could be, you know,
22:00 e-claim that is coming from the provider,
22:02 or a scanned image coming from, you know, someone else.
22:06 But there is a lot of progress that is happening
22:08 beyond just, you know, digitization, et cetera.
22:10 I think there is a lot of technology development
22:14 that has happened these days in terms of using,
22:16 you know, machine learning,
22:17 using AI to speed up the process.
22:20 So for example, the, you know, when you go to a hospital,
22:23 you, as an, if you're an insured customer,
22:26 the hospital has to take an authorization
22:27 from the insurance company,
22:29 saying that, you know, can I go ahead with the procedure?
22:32 So we had a ML solution which would authorize that
22:36 without a doctor intervention.
22:37 So it happens in a matter of minutes.
22:40 Normally the process would take, you know,
22:41 maybe 30 minutes or 45 minutes.
22:43 That process, before COVID,
22:46 was addressing about 25 to 30% of our claims,
22:50 today, of our group health claims.
22:52 Today, that number has gone to 60%.
22:54 And I think this is a secular change.
22:55 It's not going to go back to 24%,
22:57 because the engine has got even more trained
22:59 and competent to handle some of these things.
23:02 So I think COVID has had a tremendous impact
23:04 in terms of a step change in this journey of digitization,
23:07 which is all for the betterment of,
23:09 both for customer experience and, you know,
23:11 convenience for them, and, you know,
23:13 effectively better cost and control for insurance companies.
23:16 - Right.
23:18 But from a digital perspective, Dr. Prakash,
23:21 I mean, does this, you know,
23:26 in terms of digital,
23:27 do frauds go down or up the possibilities?
23:32 Does it make it easier for frauds to happen
23:35 on a different count,
23:36 or does it make it,
23:37 the whole system more efficient?
23:42 - Definitely digital should help
23:45 to unearth and prevent fraud.
23:49 Today, the industry is more dependent
23:52 on people-driven process.
23:55 Slowly it should be data-driven,
23:57 and from people-driven,
23:59 we have to move into process-driven.
24:01 So there is a greater role for fraud analytics tool,
24:06 which can look at customer-related fraud,
24:09 hospital-related fraud,
24:12 adjudicated-related fraud,
24:13 or intermediary-related fraud.
24:15 So all these informations have to be, like, you know,
24:19 fed into the system,
24:20 and insurance companies should come up
24:22 with such fraud analytics tool
24:25 with a good rule engine,
24:27 which can apparently detect claims
24:29 with a high index of suspicion.
24:32 And those claims can be looked in depth.
24:35 Naturally, digital is going to help us
24:37 unearth more and more fraud.
24:38 And it is already, you know,
24:41 giving us a lot of favorable results.
24:43 - Sure.
24:44 - And we are from Star Health Insurance.
24:45 We are very keen on straight-through processing
24:48 and robotic process automations.
24:50 And all these things,
24:51 we are trying to develop a rule engine
24:53 so that all the claims can pass through the rule engine
24:56 before the final approval is given.
24:58 - Sure.
25:00 Mayank, what has been your experience?
25:02 You know, what percentage of your business now
25:05 is completely digital?
25:07 And in terms of claims,
25:09 how much is getting processed digitally?
25:12 And what is the incidence of, you know,
25:14 fraudulent transactions in digital versus the physical?
25:19 - Yeah, so very similar experience
25:25 as what Bhargav mentioned, right?
25:27 That firstly, the need for physical documents
25:31 has been eliminated, right?
25:32 So documents are now flowing through, you know,
25:35 digital mediums, either through our website
25:38 or app uploads or, you know, scan images.
25:41 And even with the hospitals, you know,
25:43 they're coming through portals
25:45 and therefore all the information flows through that portal.
25:48 But that still, to my mind,
25:50 is not a very efficient process, right?
25:51 The efficiency will lie,
25:52 as I mentioned very briefly earlier,
25:55 where typically we move the international way.
25:57 Now, National Health Agency,
25:59 along with the participation of all the industry members,
26:03 and at the same time, RADA,
26:04 so entity IIB, again, along with all the players,
26:07 is now trying to create two different claims,
26:09 what I call digital claims platform.
26:11 Now, these claims platform will sit
26:13 between the insurance companies
26:15 and the healthcare industry.
26:17 And I'll give you why it is important, right?
26:18 Suppose each of the four providers here,
26:22 suppose, you know, health,
26:23 and from a health perspective of,
26:24 let's say my organization, Bhargav's organization,
26:26 and Dr. Prakash's organization,
26:27 go and say to hospital A, integrate with us.
26:30 And so it's a mammoth job for that hospital, right?
26:33 But whereas if you all integrate to one claims platform
26:36 and that claims platform goes to each hospital
26:38 and integrates, it becomes a very simple process.
26:41 That is where ultimately we have to move to, right?
26:44 And therefore, all our collective effort
26:46 is to make that process happen.
26:48 I'm very happy that there'll be, you know,
26:51 I think the government, the regulator industry
26:53 is now making serious effort on that.
26:55 Now, which is a sometime, it will take some time,
26:58 but when it happens,
26:59 then I think the whole process of claims management
27:02 will be very, you know, disruptively different
27:05 from what you're experiencing today.
27:07 On your, so, but as of now,
27:09 we are virtually doing everything on digital documents,
27:14 not on paperwork,
27:15 though it does create some challenges because,
27:17 you know, for example, if they're, you know,
27:19 emailing scanned images, a lot of these images are large
27:21 and though the customer is having to send multiple emails,
27:24 sometimes it creates no logistical problem,
27:26 but anyway, I mean, it's better than the customer
27:28 having to deal with not being able to courier, et cetera.
27:31 On the fraud piece, see, you know, what we are doing,
27:37 I'm sure all other peers of all ours as well,
27:41 is that because of machine AI and machine learning,
27:45 you can now really using data,
27:48 create smart rules which start predicting,
27:52 you know, detecting potential frauds, right?
27:54 So they create, I mean, unlike human intervention
27:57 where you look at the documents and apply your rules,
28:00 now machine is applying rules
28:02 and it is throwing up potential fraud.
28:03 So to the point that Bhargava was earlier making,
28:06 that you end up investigating cases
28:08 and you find that actually there's no fraud there
28:10 because it's a genuine case.
28:11 Machine, you know, AI and ML can actually start
28:14 helping you detect them much better.
28:16 There'll still be what is called false positives,
28:18 but you know, over a period of time,
28:19 as you make your data better and better and better
28:22 and your rules better, you know,
28:23 that false positives comes down
28:25 and you're able to detect frauds better.
28:27 I think what it does is,
28:29 it also sends a very strong message
28:31 to the fraudsters in the market that, you know,
28:33 these organizations are able to detect our frauds, right?
28:36 So unless there is a large scale, you know,
28:39 what I would say, you know, some real fraud,
28:42 like what happens in, you know,
28:44 something that happened in some part of Haryana
28:46 where a personal accident, you know, frauds, et cetera,
28:48 you know, this is going to keep reducing.
28:52 Plus the experience of Ayushman Bharat
28:54 where the government, NHS,
28:55 created a lot of these fraud engines for detecting fraud,
28:58 even at the scale of Ayushman Bharat.
29:00 All of that can be now leveraged, you know,
29:02 over a period of time with NHS now saying
29:04 that work together to create products,
29:06 leveraging the infrastructure that we have created.
29:08 So I think it's a journey, Mahalakshmi.
29:10 I think we are working on it,
29:11 but if you, my sense is two years from now,
29:14 the scene will be very, very different.
29:17 - Sure.
29:18 Ashish, what kind of challenges have you seen,
29:21 have you experienced in accelerating your, you know,
29:25 digital enablement over the, you know,
29:28 during this period of pandemic
29:31 and how much have you gained in terms of efficiency?
29:35 - So, Mahalakshmi, I think, again,
29:42 similar experiences, I believe, across.
29:44 So a lot of acceleration, given, you know,
29:49 the COVID situation.
29:50 So we, in some sense, we are, you know,
29:53 we are, you know, sort of processing everything digitally,
29:57 but, you know, as Meng says, you know,
29:59 there is a lot of, some, you know,
30:01 scanned images coming, this and another.
30:03 So some bit of, you know, manual intervention.
30:06 The good thing is the propensity models
30:10 that we've deployed now are helping, you know,
30:14 detect frauds and make us much more efficient.
30:16 So I do believe that, you know,
30:19 we are getting more and more efficient.
30:21 For example, you know, we, you know,
30:22 we, you know, came out with what we call a claims promise.
30:26 We say, you know, we say that, you know,
30:28 any normal claim is processed within 24 hours.
30:32 And now we are looking at, you know,
30:34 reducing that even further.
30:35 So we are getting more efficient, for sure.
30:38 I think the trick is how do we reduce the inflow?
30:43 And therefore we are now, you know,
30:45 so detecting a claim at the, you know,
30:49 detecting a fraud at the claim stage is okay.
30:54 But, you know, the fact that this policy came in,
30:58 so we are trying to now focus at the policy
31:01 pre-issue stage on how can we, you know,
31:04 detect and, you know, work with different agencies,
31:06 government agencies, working with IDA,
31:09 you know, other players, et cetera,
31:10 to see how we curtail that at the inflow stage itself.
31:15 - So Dr. Prakash, you know, my worry as a consumer,
31:20 as we talk about more and more AI, ML,
31:23 early fraud detection, what I'm hearing is,
31:26 it will be industry move from adverse selection
31:29 to favorable selection,
31:30 which is going to adversely impact my premiums,
31:34 mean more exclusions for me,
31:36 more exclusion of pre-existing conditions, higher risk,
31:40 which is exactly the premise for which
31:43 I would buy an insurance,
31:45 the data is going to work against me.
31:47 So how do we, how real is my fear?
31:52 And what can we do to guard the customer's interest?
31:57 - That's a very nice question,
32:00 because as a doctor,
32:03 having moved into insurance from clinical practice,
32:06 I see a lot of people asking for an insurance cover
32:09 after they are diagnosed with a disease.
32:11 Like in India, a lot of people are suffering from diabetes
32:15 and they are looking forward to a day one cover
32:18 with all inclusions.
32:20 Somebody is affected with a heart disease
32:22 and he undergoes a stent or a bypass surgery,
32:24 and after that he realizes the importance of insurance.
32:27 And even today with the early diagnosis,
32:31 there are a lot of cancer patients
32:32 who are successful warriors.
32:35 They live, like, you know, they have a quality of life
32:38 almost equal to after a successful cancer treatment.
32:42 But unfortunately today,
32:43 people who are diagnosed with a major ailment or a disease,
32:46 they are not given an insurance cover.
32:50 So ideally, insurance should come forward
32:54 to create disease-specific covers.
32:56 Somebody diagnosed with a kidney disease or a cancer
33:00 should have an health insurance cover.
33:02 It can be a specific cover to accommodate those people
33:06 who are diagnosed with an ailment,
33:08 because as a medical person, I find this,
33:10 that is the reason why in Star Health Insurance,
33:13 we have introduced for the first time
33:14 an health insurance for someone
33:17 after a diagnosis of cancer.
33:20 After a year, she undergoes a bypass surgery
33:23 or a coronary stenting or an angiogram,
33:25 we want to give an insurance cover.
33:27 So I think the way forward should be,
33:28 as you rightly pointed out,
33:30 instead of fearing about, you know, adverse risk,
33:33 we have to go in and we have to start covering
33:36 the certainties from risks to certainty.
33:40 That should be the transformation
33:41 the industry should look forward in the near future.
33:44 In that way, we can also win the trust and confidence
33:46 of more and more people.
33:48 And insurance as a concept can help more people
33:52 living with a diagnosis of a disease.
33:55 - Sure.
33:55 Bhargav, how do you,
33:57 can you expound on this whole principle of fairness?
34:01 How do we really approach this?
34:03 And like I go back to, you know, the trust factor,
34:08 reinstate faith that all of this digital AI, ML,
34:12 whatever tools that we have,
34:14 will in the end build trust
34:17 and provide coverage as it should?
34:21 - Well, I think that's a great question, Mahalakshmi,
34:23 because the whole idea of insurance
34:24 is that how do you provide universal coverage to everyone?
34:29 Now let's pick up the specific point that you made,
34:31 that, you know, let's say there is a risk pool
34:34 that I talked about right in the beginning, right?
34:36 And you need to ensure that the pool
34:38 is constituted with similar risk profiles.
34:41 So when we talk about the fact
34:43 that you want to identify who is different
34:45 in terms of risk profile,
34:47 you're trying to be fair to the people
34:49 who are of the same risk profile.
34:50 And that's one element of fairness.
34:52 But what about the people who are at risk,
34:54 what Dr. Prakash was talking about?
34:56 So just by eliminating is not the solution,
34:59 we have to find a solution for them.
35:00 - Right.
35:01 - And I think as the industry evolves
35:03 and matures and scales up,
35:04 there will be specific products.
35:06 You know, all of us have had specific products
35:08 for specific diseases, as Dr. Prakash talked about.
35:11 Some of us have taken a bigger lead in that,
35:13 but as the industry matures,
35:14 we will have products for them.
35:15 Now, one of the journeys that we believe
35:17 insurance can play a big role in,
35:19 and, you know, IDA has allowed us
35:22 to do a lot of experimentation under the sandbox regime,
35:26 is to do disease management, for example.
35:28 Let's look at a high risk pool of people
35:31 who are maybe at, you know, risk of, you know,
35:35 maybe they've had a cardiovascular event in the past,
35:38 and you need to manage that risk.
35:40 I think there is a lot of good work
35:41 that insurance companies can do,
35:43 and globally there are examples of companies doing this.
35:46 You know, in South Africa and in US and et cetera,
35:49 where insurance companies step in
35:50 and provide you with disease management services
35:54 to keep you healthy.
35:55 And one thing we must understand and appreciate
35:57 is that our interest as an insurance company
36:00 is completely aligned with the consumer,
36:02 because we also want the consumer to remain healthy.
36:05 Because if a customer remains healthy,
36:07 we save money in terms of claims.
36:09 And obviously as a customer, everyone wants to stay healthy.
36:11 So the point is segregation of the pool
36:13 and finding appropriate solutions to different risk pools.
36:17 One to the healthy pool where premiums will be low,
36:20 you do a lot of wellness and preventive stuff.
36:22 There could be a high risk pool
36:23 where you come in with a slightly higher price,
36:25 but if you manage the disease well,
36:27 and we can help you through that process,
36:30 your premium will stay under control
36:32 and potentially come down.
36:33 Now, these are the journeys that we will see
36:35 evolve in insurance in India,
36:37 and we are beginning to see some of those early steps.
36:40 - Sure, Barkha, you talked about,
36:42 interestingly about alignment,
36:43 and that's the next point I want to raise.
36:46 That of course there is alignment to some degree
36:49 between the insurance company and the seeker.
36:54 But the villain in this equation seems to be the hospitals,
36:59 who tend to, are often accused of inflating prices.
37:03 And obviously there is a clear conflict
37:06 in terms of what the insurance companies would want,
37:09 which is to always have a lid and cap
37:11 and checks and balances in terms of containing costs
37:14 versus what hospitals,
37:16 because that's their primary business,
37:18 would want in terms of always making the most of a situation.
37:23 So how do we create this alignment, Dr. Prakash?
37:28 And is there anything that you are doing differently
37:32 in terms of negotiating with hospitals
37:34 to achieve this alignment?
37:38 - So it's a million dollar question,
37:41 and globally, a final consensus between payer and provider
37:46 is yet to be reached,
37:49 because there is always expectation mismatch.
37:51 But definitely we should create a platform
37:55 for the service providers, hospitals,
37:58 to express their concerns and misconceptions
38:02 on the insurance concept.
38:03 And we should also be able to explain to them,
38:06 as Mr. Bargo beautifully said,
38:08 it is we are only managing the common pool.
38:12 It has to be made very clear to the hospitals and doctors
38:15 so that they cannot think that it is only insurance
38:18 is paying so they can charge more.
38:20 It is not insurance paying from their pocket,
38:23 it is again, they collected money from so many people,
38:26 the customers.
38:27 It's a common, we are only custodian of their common fund.
38:30 So this, the concept of insurance,
38:34 that it has to help people who are in need.
38:36 This has to necessarily reach
38:40 the years of treating doctors.
38:43 Particularly today, insurance policies are sold
38:47 for 50 lakhs uninsured and one core uninsured,
38:50 meaning that these patients are going to reach
38:53 high-end corporate hospitals.
38:55 So the specialist and super specialist in such hospitals
38:58 should take time to fill the pre-authorization request
39:02 and send it to the health insurance companies
39:04 with all relevant details.
39:05 They should not look at it as a job to be done
39:08 by a junior doctor or an administrator.
39:11 There is a lot of lack of transparency
39:17 because the treating doctor thinks of a different plan
39:19 of management and the information that reaches
39:22 the insurance companies or for the front office
39:24 or all administrators.
39:26 So this is creating a lot of mismatch.
39:28 So the hospitals, the front office,
39:31 they should be well-equipped about the basic information
39:35 and fundamental strategies that they should know.
39:37 Because hospitals are getting a huge traffic
39:43 and a turnover from insurance business.
39:46 Last year, for example, we would have paid more,
39:50 the industry as a whole would have paid more
39:52 than 20 million, two crore claims.
39:55 We would have paid an amount of maybe 6 billion rupees.
39:59 - Right.
40:00 - So there is a huge opportunities that exist
40:03 with the insurance companies.
40:05 And today, hospitals without any effort on marketing,
40:09 advertisement or reaching smaller hospitals for referral,
40:12 they're getting a direct business.
40:14 The only thing that they should do is spend some time
40:18 on understanding the nuances,
40:19 understanding the requirements
40:21 of the health insurance company
40:22 and giving the due respect to a health insurance request,
40:25 pre-authorization request.
40:27 Whatever may be the qualification of the super specialist
40:30 or a specialist, he may be.
40:32 He should come forward
40:33 and he should fill the pre-authorization form.
40:35 He should make the diagnosis
40:36 and he should make it very clear
40:38 about what is his plan of management.
40:40 This can be the first step towards reducing
40:42 unnecessary queries from insurance companies
40:44 and giving a very similar,
40:46 hassle-free service to the customers.
40:48 - But is that really a procedural matter
40:53 or a transparency issue or a basic conflict
40:56 in terms of what the payer would like?
41:00 I mean, the insurance company would like to pay
41:02 versus what they would like to get paid.
41:05 Isn't there a conflict right there?
41:09 And I think that's the bigger bridge
41:11 that we need to bring about
41:15 than a procedural transparency issue.
41:19 - Apart, you're right.
41:20 Apart from the procedural issues,
41:22 but here, the hospitals,
41:28 as a whole, we cannot take as one entity.
41:31 There are some hospitals which are running for generations,
41:35 very ethical, very professional, highly transparent,
41:38 and they are really saving lives.
41:40 And at the end, there are hospitals
41:43 who wanted to maybe make more.
41:46 I do not know what charging it comes under fraud.
41:48 If that comes under fraud,
41:50 then it'll be a big number.
41:52 There are hospitals which want to bundle two, three procedures
41:55 and claim as different entities.
41:56 There are people who want to abuse antibiotics
41:59 and have a high trade margin on consumables and prosthetics.
42:02 These things happen.
42:04 So the hospitals cannot be looked at as one entity.
42:07 In my experience, I've seen people
42:09 who are very fair and transparent players
42:12 and who are very well respected in the community
42:14 and also respected by the insurers.
42:16 At the other end, there are people
42:18 who are trying to go away from ethics.
42:23 So that is the reason why I always claim
42:26 that to eliminate fraudulent practices,
42:29 my first job as a medical man in the insurance sector
42:32 is to recognize and identify people who are straightforward.
42:36 That is the first step to eliminate fraud.
42:39 - Sure.
42:40 Sure.
42:42 Maya, from your perspective,
42:47 I mean, since you brought this point saying
42:50 that if overcharging is really a fraud
42:53 and has to be recognized as a fraud,
42:55 then there'll be a huge replication.
42:57 What is the regulatory framework around frauds right now?
43:02 And does it really cover hospitals as institutions
43:06 that can be brought to book
43:08 to make this whole system more efficient?
43:12 - Maya Malish, this is a very complex subject.
43:18 If my senior colleague, Dr. Prakash,
43:20 coming from the medical fraternity,
43:23 he was expressing his sharing.
43:26 So you can understand that there's no easy answer.
43:28 Firstly, health regulations,
43:31 the central government can only propose a model regulation.
43:34 Each state has to adopt the Clinical Establishment Act.
43:37 There was a model proposed,
43:38 but every state had to enact it.
43:40 And if you look at how many states actually enacted it,
43:43 you'll be surprised to see the number.
43:45 So firstly, there's a whole issue.
43:47 And even the regulator, RADA,
43:49 cannot technically regulate the health hospital.
43:52 I mean, they can only provide some guideline
43:55 like their own registration, et cetera,
43:56 but there's no way you can regulate.
43:58 When we talk about cause,
44:01 there is, we talk about something called
44:03 fraud, waste, and abuse, FWA.
44:05 You spoke about fraud earlier.
44:07 Waste and abuse actually is an equally important part
44:10 of the whole issue that the industry has to deal with.
44:13 Now, there are two or three issues.
44:15 Like one, is the patient being given the treatment
44:19 which is as per a standard protocol?
44:22 That means this is basically the treatment
44:24 that you can give.
44:25 I mean, there are standard treatment guidelines
44:27 which have been issued.
44:28 There are drafts which have been issued
44:29 by the national government,
44:30 and so that they can be proposed now under Aishwarya Bandra,
44:34 they are being used,
44:35 they are being proposed and so on and so forth.
44:38 But have they been adopted?
44:40 No, not yet, right?
44:41 I mean, various industry bodies
44:43 with the blessings of RADA
44:45 propose that nothing happened on that.
44:47 So there itself, some hospitals end up giving treatment
44:51 which, as non-medical people have coming from,
44:56 the health insurance,
44:57 especially cannot question it beyond a point of time.
44:59 They can only raise an issue that, is it there?
45:01 You cannot say, oh, this has to be given or not given
45:03 because that's completely at the medical fraternity
45:06 to decide, right?
45:07 - Right.
45:08 - The second one is what I call abuse.
45:09 That just because the guy has got a five lakh summer short,
45:14 even if the treatment can be done in three lakh
45:16 and the guy can be released in seven days,
45:19 you keep them in the hospital for 15 days
45:22 and especially for ones
45:23 who don't have a very high occupancy.
45:25 So all of this wastage and abuse
45:27 happen across the healthcare ecosystem,
45:29 which is so fragmented in India.
45:32 And as an industry, even at the large body like ours,
45:36 we cannot do beyond a point of time.
45:38 It's an ongoing dialogue.
45:39 You take what has happened in COVID times, right?
45:42 I mean, there's already an issue
45:45 whether the council has been trying to talk
45:48 to the healthcare industry, trying to propose,
45:51 because this is where the first time
45:52 that at least from a treatment protocol perspective,
45:55 the government had issued a protocol
45:57 that this is the COVID treatment protocol,
45:58 every hospital, private, public, small, big has to follow.
46:02 So then at least we can have a range of cost and all, right?
46:05 Still, there is a big challenge.
46:07 So it's an ongoing thing.
46:08 I don't, and the one way to do that is
46:11 as under the national health, the Aushwabhan Bharat
46:14 and as they're trying to increase their coverage,
46:16 the more and more guidelines start getting adopted
46:19 for larger scope.
46:21 And as insurance penetration increases,
46:24 the ability of the industry to then negotiate
46:26 and talk together increases,
46:28 but there's no simple answer to my mind on this Mahalakshmi.
46:31 - Sure, I'm loving this conversation,
46:33 but unfortunately we are racing against time.
46:36 So one last question, Ashish, maybe you can start,
46:40 but I would want everybody's take on this.
46:43 What is it that you would expect to do
46:45 as an insurance company over the next one to three years
46:48 to alter the customer experience,
46:52 may I say, make it magical from where we are today?
46:58 You're not audible, Ashish, to me.
47:06 - Sorry, yeah.
47:07 So, I think it's a fantastic question and magical it is.
47:12 That's the target.
47:16 As honestly, during these COVID times,
47:20 I think this has been discussed, debated,
47:24 saying people, our customers are getting,
47:30 are used to now online transactions,
47:34 which are much, much smoother and how can we reach there?
47:38 And just to add a little on the last point you made,
47:42 Mahalakshmi, on all these tech analytics platforms,
47:46 AI, et cetera, is it making customers' lives more difficult?
47:51 I would say all these are in the backend.
47:56 To be honest, all this is helping us
47:58 making customer journeys even more simpler,
48:01 so at the front end,
48:03 because what happens is we get more confident
48:06 that we are able to weed out the unwanted, the fraudsters,
48:11 and therefore we provide simpler journeys.
48:14 For example, you see that even us,
48:18 we increased our, what we call non-medical limits
48:22 for a category of customers.
48:25 So, if you go in, you can just buy online,
48:28 simple journey closed
48:33 within a few hours,
48:36 to say the least.
48:39 So, we do want to improve our customer journeys
48:44 and take it to a level where,
48:48 when we speak to some distributors, they tell us,
48:52 particularly the online ones,
48:53 they tell us we want customers
48:55 to buy insurance in three clicks.
48:58 - Right.
48:58 - And that's the target, to be honest.
49:01 And whatever we need to do at the backend,
49:05 introduced RPA, analytics, AI, blockchain, whatever,
49:10 that's the target.
49:11 And I can tell you, at PnV MetLife,
49:13 at least we are focusing,
49:15 we've made a global team to handle this situation.
49:21 - Sure.
49:23 With respect to claim settlement, Ashish,
49:26 what will be your, any initiatives
49:29 or something that you would pursue to make it better?
49:33 - So, after the claims are sure that we've launched,
49:37 which is 24 hours claim settlement,
49:39 we are now looking at a claim settlement
49:40 within three to four hours.
49:43 And that's the next target.
49:45 - Okay, sure.
49:46 Barkha, what is your next milestone
49:49 with respect to claim settlement
49:51 and magical customer experience?
49:53 - So, let me take the first one first,
49:55 the second one first, the magical experience.
49:58 Look, I think a lot of points have come through
50:00 during the course of this discussion.
50:03 As Ashish said, clearly the endeavor has to be
50:07 to take advantage of the technology that is available today
50:10 to make the journey simple, easy to understand,
50:14 convenient for customers.
50:15 And all the technology investment
50:17 that we are doing behind is for that.
50:19 Second thing that we are trying to do is a lot of DIY,
50:22 as in, empower the customer to do things on their own.
50:25 We've been talking about health,
50:26 but let's say motor, which is also one big part
50:29 of our business.
50:30 Let the customer do the survey
50:32 rather than wait for a survey to come.
50:34 And these are initiatives that we've launched before COVID,
50:37 but we've seen tremendous increase
50:39 in the percentage of customers
50:40 who are doing the survey using a mobile app.
50:42 And there is a technology behind it.
50:44 You can do it using an AI
50:46 and the complex ones can go to a surveyor
50:48 sitting in his home and do it for you.
50:51 So, put more power in the hand of the customer
50:53 so that he's in charge of what he's doing.
50:56 That's the second part.
50:57 But the third, and I think the biggest effort really is,
51:00 we've spent a lot of time talking about fraud.
51:02 We can debate the number,
51:06 but it's still single digit percentage of our customers
51:09 who are probably themselves wanting to abuse the process.
51:13 And it's very important for us to,
51:16 with a lot of certainty,
51:16 identify the guys who are genuine guys
51:19 and the guys who are not.
51:20 And that's where a lot of the claims analytics,
51:23 the fraud propensity models, et cetera, that we do,
51:26 is to ensure that the guys that we can trust
51:28 and increasing the trust score to us is a big, big journey.
51:32 So that we identify who are the guys that we can trust
51:34 and make the process magical.
51:36 For the others, we don't want it to be magical
51:38 because that's also our responsibility to control fraud
51:41 because otherwise the genuine customer suffer.
51:43 So I think those are the three journeys,
51:45 simplicity through digitization, et cetera,
51:48 a more DIY and increasing the trust score.
51:53 - Sure.
51:54 Dr. Prakash.
51:55 - Yeah.
52:00 So I can only compliment what Mr. Bhargava
52:05 has nicely summarized.
52:06 So insurance is a,
52:08 actually the power of insurance is settlement of claims
52:11 and it is a business of deep pockets.
52:14 And definitely, we have to understand the hospitals
52:17 and both of us should coexist.
52:19 Insurance companies and hospitals should be partners
52:23 in progress.
52:25 That is very important.
52:27 And we have to work together to see that
52:31 how we can eliminate exploitation at both ends.
52:36 Finally, I can say one thing,
52:37 seven to eight lakh crore is the money spent on healthcare.
52:40 But unfortunately, there is no regulator.
52:42 So how long will it take to bring in a regulator for health?
52:47 - Right.
52:50 Sure.
52:51 Mayank.
52:54 - I, you know, so when I visited my partner's operations
53:02 in South Africa, they cover all benefits, right?
53:06 Not just hospitalization, but in South Africa,
53:08 they cover pharmacy, doctors, medicine, et cetera,
53:11 et cetera, testing.
53:13 95% plus of their claims are adjudicated
53:18 human-less and paperless,
53:22 which means no human involvement,
53:23 no paper involvement, machine to machine, right?
53:26 I wish we can get to that stage someday in India
53:30 because that's where the experience has to be.
53:33 And I'm, you know, whether it's 95%,
53:34 even if we can start and say, you know, 5%, 10%, 15%.
53:39 Now in a country which exports technology to the world,
53:42 why can we not make that happen?
53:45 So with all of the national digital health stack,
53:47 the health stack that is being created,
53:49 like we have done for Aadhaar,
53:51 I mean, India has got the best technology stack today,
53:55 JAM, right?
53:56 I wish that, and I hope that the health stack
53:59 that is being proposed in India
54:02 can help us create that infrastructure as an enabler
54:06 to create this experience for our customers in India.
54:09 I mean, I would love to be able to see that one day.
54:13 - And I think if I can add to Mayank,
54:14 that is probably one of the biggest national agendas
54:16 that we have on the health side.
54:18 Really, that's something that we can do.
54:20 And the biggest challenge is a fragmented system
54:22 where the states will step in and not allow this to happen.
54:26 If anything that we can do as a nation,
54:28 this is not something that we can do as an industry.
54:30 This is, I think, one of the most important agendas
54:32 that we have as a nation.
54:34 - Sure, absolutely.
54:36 Thank you, gentlemen, for this really lovely,
54:39 lively discussion.
54:41 I really enjoyed every bit of it and educated myself.
54:44 Thank you so much.
54:45 And of course, till we meet next,
54:47 I hope there is a healthcare regulator in place
54:51 and the healthcare tax also becomes a reality.
54:56 Thank you.
54:57 - Thank you so much.
54:57 - Thank you.
54:58 Thank you, Malakshmi.
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