WEBVTT - BNY Mellon's Pandiri on Real Time Data For Asset Flows (Audio)

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<v Speaker 1>one point eight three percent. And that's a Bloomberg Business

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<v Speaker 1>Flash is Taking Stock with Kathleen Hayes and Prim Fox

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<v Speaker 1>on Bloomberg Radio, continuing a very special live broadcast today.

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<v Speaker 1>We are at Dove Mountain near Tucson, Arizona, the Ritz

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<v Speaker 1>Carlton here in the midst of the Tortalita Mountain range.

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<v Speaker 1>We are broadcasting live it invested sixteen. It's the power

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<v Speaker 1>of Big Ideas of bn Y Melon client conference. Joining

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<v Speaker 1>us now is the person who kicked off the conference

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<v Speaker 1>last night down by the pool with little burning crucibles

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<v Speaker 1>in the water and a beautiful Arizona evening. And I'm

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<v Speaker 1>referring to Samir Pandery. He's executive vice president and global

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<v Speaker 1>CEO of Assets Servicing at b in why Non Semir,

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<v Speaker 1>Welcome to Taking Stock and thank you for inviting us

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<v Speaker 1>to the confidence. Thank you for having us on your program.

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<v Speaker 1>Uh the uh the challenges that your client's face and

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<v Speaker 1>of course you goose is an intimate group about two

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<v Speaker 1>people from across the country and around the world. The

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<v Speaker 1>big questions what what? What is the biggest one at

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<v Speaker 1>the top of the list. When you're looking particularly at

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<v Speaker 1>UH some of the regulatory changes that have occurred lately,

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<v Speaker 1>it seems that that no matter whether you're a servicer

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<v Speaker 1>or a money manager, everybody is still grappling with some

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<v Speaker 1>of the big changes. Yeah, you know, I think fundamentally,

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<v Speaker 1>for example, if you're a money manager or if you're

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<v Speaker 1>a money investor, what you really want to do is

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<v Speaker 1>focus on managing money. So that means all of the

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<v Speaker 1>other things, the operations, the technology, those are things that

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<v Speaker 1>are not a creative to your core function. So I

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<v Speaker 1>think what regulation does. It adds responsibilities to your non

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<v Speaker 1>core activities, and I think that is a huge burden.

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<v Speaker 1>You know, there's non core activity. Like my job if

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<v Speaker 1>you're my client, is to make sure that you're invested

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<v Speaker 1>in the right securities, the right assets, just to save

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<v Speaker 1>money and make money exactly. And so if you have

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<v Speaker 1>to distract or you know, spend part of your time

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<v Speaker 1>doing other things like worrying about cybersecurity or worrying about

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<v Speaker 1>your technology architecture or how you're actually um robust. From

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<v Speaker 1>an operating infrastructure perspective, it's very difficult UM and it's

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<v Speaker 1>very expensive. So again, I think one of the things

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<v Speaker 1>that people are looking for or solutions where they can

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<v Speaker 1>take advantage of scale, they can take advantage of people

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<v Speaker 1>that are that can do this in a professional way

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<v Speaker 1>so that they can really focus on their core business activities.

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<v Speaker 1>How can the customer also take advantage of all the

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<v Speaker 1>data that you have? Uh, the idea being that it's

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<v Speaker 1>no longer playing vanilla investing stocks, bonds, cash, it's everything alternative,

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<v Speaker 1>non cord less on. You built a model of yes.

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<v Speaker 1>So you know, we have a digital ecosystem called Nexon,

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<v Speaker 1>which is really, i think technologically ten years ahead of

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<v Speaker 1>where the industry is and really where we're driving the

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<v Speaker 1>transformation of this company. And the digital ecosystem is based

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<v Speaker 1>on a couple of fundamental principles. We collect large amounts

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<v Speaker 1>of data, so we for example, collect about one point

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<v Speaker 1>four billion transactions on a daily basis, because the cost

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<v Speaker 1>of story that data is significantly cheaper now compared to

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<v Speaker 1>a decade ago. But then the second part, which is

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<v Speaker 1>really the harder part, is taking the data that is

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<v Speaker 1>important and relevant and making it consumable in a way

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<v Speaker 1>that's useful to the client. So again, if I can't

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<v Speaker 1>take that and translated into a form that's usable, it's

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<v Speaker 1>um you know. So that's really the trick and that's

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<v Speaker 1>the challenge. So give us a specific example of a

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<v Speaker 1>batch of data compiled over the years by B and

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<v Speaker 1>Y melon that relates to something that be very specific

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<v Speaker 1>that before you created these technologies like next in and

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<v Speaker 1>digital polls, that it was just kind of a lot

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<v Speaker 1>of data out there, and now you can say, look specifically,

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<v Speaker 1>here's something someone can learn. What's one example of that.

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<v Speaker 1>So one example is if you look at our pension universe.

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<v Speaker 1>We have about three and a half trillion dollars worth

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<v Speaker 1>of pension assets that we administer. About a decade ago,

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<v Speaker 1>three percent of those assets were invested in alternatives. Today

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<v Speaker 1>that number is two so hedge funds, private equity, real estate.

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<v Speaker 1>So as these flows happen into these real assets, you know,

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<v Speaker 1>clients would like to get that information on real time basis,

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<v Speaker 1>so we provide them the data on the huge asset flows,

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<v Speaker 1>the transformations that are happening in real time so that

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<v Speaker 1>they can actually look at where they are invested relative

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<v Speaker 1>to their peer group and really decide if that's really

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<v Speaker 1>what they want to be in terms of the risk spectrum. Uh.

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<v Speaker 1>And by the way, this was not information that we

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<v Speaker 1>were able to provide. Let's say even five to ten

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<v Speaker 1>years ago. We had the data, but was not consumable.

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<v Speaker 1>Now I think with the technology you can actually consume

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<v Speaker 1>that data in real time. You also get the issue

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<v Speaker 1>of many investors are paying for alpha, but they're really

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<v Speaker 1>just getting beta. It isn't that kind of also going

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<v Speaker 1>to be a look into what you're paying for and

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<v Speaker 1>what you're getting in terms of the holistic universe of investments. Yes.

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<v Speaker 1>So one of the things that our data allows. So

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<v Speaker 1>if you have, for example, as an investor our clients

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<v Speaker 1>they might be using multiple managers, we can actually show

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<v Speaker 1>them not only what their manager is delivering in terms

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<v Speaker 1>of alpha, but what are they delivering relative to their

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<v Speaker 1>peer group. So it's very clear, very transparent in terms

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<v Speaker 1>of what the performances. And again we have a g

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<v Speaker 1>r S which is called a Global Risk services um

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<v Speaker 1>business which is really predicated on giving that comparisons so

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<v Speaker 1>that as an investor you can have a really good,

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<v Speaker 1>solid foundation to make these comparisons the fintech firms, disruptors, innovators.

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<v Speaker 1>Is that a threat to be in White Milon and

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<v Speaker 1>its model or is it an opportunity In some sense,

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<v Speaker 1>I think it's a threat if we did nothing about it.

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<v Speaker 1>We are obviously very very engaged UM and we're also

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<v Speaker 1>trying to think about how we should perhaps disrupt our

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<v Speaker 1>own models. So, you know, as an example, we are

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<v Speaker 1>looking at the use of technology. We're using it the

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<v Speaker 1>use of robotics, UH in terms of our operational processes

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<v Speaker 1>to really see if there is a better way to

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<v Speaker 1>actually um, you know, create the end product you know

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<v Speaker 1>that the clients. So robots can really do what I

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<v Speaker 1>would call the mind numbing things that are you know,

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<v Speaker 1>task oriented but rule based that you can actually program

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<v Speaker 1>that you don't need to have a person do, so

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<v Speaker 1>you can actually have the person focus on the exceptions

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<v Speaker 1>and the higher value added things that require some kind

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<v Speaker 1>of a cognitive ability to make a decision and using

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<v Speaker 1>all of this data. One example I was given this

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<v Speaker 1>morning had to do with emerging markets. Investing in a

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<v Speaker 1>non market correlated fund that specializes in emerging markets looking

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<v Speaker 1>at capital flows into and out of emerging markets and

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<v Speaker 1>trying to make a decision to see whether there's a relationship, right,

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<v Speaker 1>because you've got the emerging market fund, but then you've

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<v Speaker 1>got the capital flows. What they found was almost counterintuitive.

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<v Speaker 1>As the flows went into emerging markets, this fund actually

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<v Speaker 1>did poorly. Why because everyone was benchmarking against the m

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<v Speaker 1>s c I and yet the investments were not part

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<v Speaker 1>of the MSCI index. So this is going to allow

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<v Speaker 1>not only the investor, but also the people that manage

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<v Speaker 1>the money to differentiate themselves in a new way. Yeah,

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<v Speaker 1>I think, you know, the the data is the issue here, right,

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<v Speaker 1>because you know, when you have metadata that can go

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<v Speaker 1>at a much deeper level, you can drive analytics that

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<v Speaker 1>you actually couldn't do before. So and again I think

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<v Speaker 1>this is an example where if you actually have data

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<v Speaker 1>at the most underlying, basic transactional level, where you see

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<v Speaker 1>the flows going in and out, and if you can

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<v Speaker 1>digitize that and make that consumable, you will have information

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<v Speaker 1>that's not aggregated, that's general and non specific. But you

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<v Speaker 1>know the contrary. So I think that's really the power

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<v Speaker 1>of technology and data which is really I think, you know,

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<v Speaker 1>driving decision making now very differently than even just five

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<v Speaker 1>ten years ago. What's the challenge for individuals who worked

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<v Speaker 1>in this industry? You have a very interesting background. You

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<v Speaker 1>you start out in chemical engineering and got your NBA

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<v Speaker 1>and finance, and you worked at JP Morgan and you've

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<v Speaker 1>worked on the trust side at being my Melon. You're

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<v Speaker 1>involved with some of the emerging market issues. What is it?

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<v Speaker 1>What is it? What? What? What do I need to know? What?

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<v Speaker 1>What is the challenge for for the professional in this industry? Now?

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<v Speaker 1>I think in UM in my business and I have

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<v Speaker 1>some of this background. UM. I think there's three things.

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<v Speaker 1>You know, we are a very global organization. I lived

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<v Speaker 1>abroad for over a decade UH in Asia and Europe.

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<v Speaker 1>I think, you know, having that global perspective is absolutely

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<v Speaker 1>critical if you want a problem solving this industry. I

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<v Speaker 1>think the second thing you have to have the ability

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<v Speaker 1>to deal with change and drive the change in the

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<v Speaker 1>industry as opposed to letting that happen to you. Having

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<v Speaker 1>great change management skills I think are really important. And

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<v Speaker 1>I think the last thing is you have to be

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<v Speaker 1>able to disrupt you know, traditional mental models and business

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<v Speaker 1>models and really come up collaboratively working in different ways

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<v Speaker 1>with your clients, with your regulators, to solve problems that

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<v Speaker 1>you couldn't solve before. So again, I think having that

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<v Speaker 1>sort of open environment in terms of how you solve

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<v Speaker 1>problems is going to be really important. So I would

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<v Speaker 1>say those things are probably really important globality, change management

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<v Speaker 1>and being able to work with different business models. Thank

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<v Speaker 1>you very much for spending time with us. Samir pent Deer,

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<v Speaker 1>he's the executive vice president, chief executive Asset Service. Thing

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<v Speaker 1>coming up we're gonna be taking a look at the

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<v Speaker 1>markets with Stavilson our stock Sedator