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As technology supercharges data access and transparency, opportunities to bring the benefits of sound investing to more individuals multiply. Industry veteran Stephen C. Daffron outlined how data science can continue to remove friction for financial professionals as they bring wealth management solutions to more investors.

This was a SIFMA Main Stage Keynote event with Thomas F. Price, Managing Director, Technology, Operations, and Business Continuity SIFMA.


Stephen C. Daffron

Thank you, Tom. It’s really nice of you guys to have us here. Been looking forward to this, partially because I get to see people I haven’t seen in a long time.

And I look across the audience and out in the hallway, [at] the ones eating the donuts. A lot of you, I have worked with over the years, and [it’s] really good to see you again.

I’ve looked forward to this, and I guess I look forward to it especially because at 50 years, SIFMA can look back…and I guess I’ll address myself primarily to the ops and tech and the data guys who are in the room, if SIFMA could look back and see all the things that we’ve done, you’ve done.

And when we ops guys, we tend to…the glass of water is always half empty, right? We’re never satisfied. We want to do better. We want everything to be perfect. But sometimes it’s a good thing just to pause, and look over your shoulder a minute, and just appreciate how far you’ve come. You have done some amazing things. You’ve made amazing progress.

I’m going to talk about things you still want to do today. But listening to Art Thomas and Norm Ecker and those guys talk this morning about the things that they’ve seen, made me realize just how much we should appreciate the things that Art, and Norm, and…I can add a few more names: Brian Shea, and Paul Compton, and Robin Vince, and the people who were there when we created a lot of the things that are going on here, and have made the process that you have now. Which is not perfect! But, God guys, it’s just so much better than it used to be! …and to appreciate the progress you’ve made.

Show of hands: how many people here were around when Long-Term Capital Management went down? [raises hand]

Okay. You guys can see it, right? Remember the scramble we had then? Remember what happened? Remember what we had to do?

Now think at where we are now. LTCM was…I won’t use the word, but it was one of those shows!… [chuckles] But we learned something from it, and we’ve gotten better. And you should give yourself a round of applause for the progress you’ve made, please. [applause]

And we should also give appreciation to SIFMA. Tom’s right, we were there a while ago when we were first started putting the ops and tech pieces together. SIFMA has kept us on track. You’ve given us forms to work with. You’ve given us support. You’ve given us, you know, the ability to talk to each other about this in ways that made sense.

And so I think another way to start this conversation off would be to acknowledge that not just for the last 50 years, but especially I’m thinking over the last decade, of how much progress SIFMA a has made for us. So let’s give SIFMA a round of applause! [applause] Okay!

Thomas F. Price

But you know, Steve, we can’t do it without folks like you and others in this audience from helping us, in terms of forming the agenda, supporting us in terms of the mission…so it’s folks like you that help us, and folks in the audience that help us, be able to achieve on your behalf, right? To create a better, more resilient financial system. And I think that’s paramount to all the discussions we have today. For the folks, for the YOUNG folks in the audience, there’s a great book called, “When Genius Failed.”, about the Long-Term Capital Management.

And I would advise anyone that’s interested to really pick up that book, ’cause that really gives you a flavor of how the crisis management works.


She’s probably in the room somewhere. We were talking yesterday, and I mentioned – we were talking about LTCM – and a young woman in the room said, “Yeah, I remember that! It was a case study when I was at graduate school or something. Yeah, it was a case study.” Man, do I feel old!


[laughs] Well, once again, thanks for joining us today. And I know as we started formulating this conversation, I know we wanted to focus on the concept of technology, and how that’s creating a better, faster, more transparent access to data, which ultimately brings more individuals access to sound investing.

And a lot has transpired over the last few months: a lot of volatility in the banking industry, which has brought the idea of consumer trust into the spotlight.

To start things off, I’d like to get your views on how technology and data can be instrumental in building back that trust.


Well, isn’t it amazing how fragile that trust is? I mean, we have been working at this for 50 years, and even then, in the near term, the last decade, since the financial crisis of how much work we put into making the processes work better. But the investing public still is very, very volatile, and they react to us with great negativity very, very quickly. And the volatility, to a large degree, is a function of the things we’ve done: to create the ability to move money, to move security, to do things at the flick of a switch, at the click of a phone.

Take…can we all think about Silicon Valley Bank? They announced their capital raise at 12:30. By 4:30, $42 billion had moved. Four hours, $42 billion. That’s instantaneous: people moving billions of dollars on their phone! Can you imagine?

And for those of you in the room – and I can pick out some of you ’cause we were there that weekend at the Fed – can you imagine if that capability had been there when Lehman went down? That volatility caused this thing to collapse faster. Four days after that first announcement, and Silicon Valley Bank was swept under the warm embrace of the FDIC. [snaps fingers] Four days, just like that. It felt like it came out of the blue! It should be a wakeup call, ’cause when things can come out of the blue, they can come out of the blue all the time, right?

No, not right. Every ops guy, every tech guy, every data scientist in the room knows that when something like that happens, when that dam breaks, it didn’t just break just then. That in the weeks and months and years before then, there were cracks in that foundation that we could see if we had the right tools, the right focus, the right…the right attitude. We could see those cracks…if we are willing to acknowledge them.

And I’m looking, again, I’m looking at the ops and techs and data guys, who actually are the foundation of this. We’re the ones who have to say: “Here’s what we see, here’s where we see it” – beforehand. When we can see the data for what things are happening before the dam breaks, that’s when the public loses trust: not just when the dam itself breaks, but in the fact that we have all the capabilities to solve the problem beforehand. And we can! That erosion of trust, that collapse of the dam is not a given.

The name of this talk is – when Tom and I first started talking about it – I said, let’s call it, “Know Better, Do Better.” It reminds me, it came to something my mother used to tell me, “Stephen Curtis…” – yeah, she was a pretty hard marker! – she’d say, “Stephen Curtis, if you know better, you should do better.”

Every time! We know better.

We, in this audience, we and the people who are the foundation of the securities industry, who are doing the operations and the technology and the data support for this entire industry, for those clients…those clients’ demand curve relies on us to do what we do, so they can have confidence in what we do every day. And we do it well! But sometimes – and the Silicon Valley Bank illustrates it, as does Lehman Brothers, as does LTCM, as does – I mean, go all the way back to ’87 and IBM: all the things that are happening after the fact, we see where the cracks are happening.

We have the tools, now, to do better.

We have the people, way smarter than me. A lot of you who have worked for me, over the years, have said – you always heard me say this – “We have the tools and the ability to do better, if we choose to do it.”

We need to choose to do it.

We know better; we can do better.

And we have to, because it’s not going away. It’s going to get harder. The pressure’s going to grow, you know…in a good way, we are in this business because the growth is happening; because the way that demographics work, the businesses we are supporting are growing because people need to do more and better investing.

Three major factors. The first one’s called democratization, which is just a fancy term some social scientists put on more people investing in more things at a faster rate. Democratization means that you’re going to have a lot more people investing in a lot more, and more complex products, all the time. That adds to that pressure; that adds to the potential for cracks.

And on top of that democratization comes personalization, because one of the big things that’s happening in that democratization is that the investors aren’t my age or Tom’s age. They’re our kids! And soon, they’ll be our grandkids! And they are sophisticated, and they’re tech savvy, and they know what they want, and they want it now.

That democratization, and the personalization with the need for advice, it just means the size and shape of the data burst that supports what we do is going to get bigger and more complex. The pressure behind the dam will grow.

We’ve got to do our job better. We know better; we’ve got to do better.

And we will. I have confidence.


So Steve, when we talked about this, right? What we’re talking about is, that cracks equal risk, really. We’re talking about risk in the system. We can’t eliminate risk. But, I think your point is, we can get in front of some of those risks, so we don’t create an environment where the dam breaks.


Exactly right. And…again, I’m speaking to the people who are in the room who are the ops and techs and data guys, who are facing off to people who are worried about this quarter’s EBITDA. Okay, I got it. This quarter’s EBITDA is important. We all have to make sure we have a profit, and we’re making proper businesses. But, we also have to be prepared to speak truth to power: that sometimes, this quarter’s EBITDA is not nearly as important as making sure we have the right controls in place, the right kind of leadership in place to speak truth to power, to say, “We got to make sure the dam doesn’t break.”


Yeah. One of the things that, when we talk about this as well, one of the things we talk about, data and information and the free flow, and the instantaneous or near instantaneous information. How do we prevent investors from overreacting, right? Creating bank runs, or creating crowded trades in the marketplace that create these anomalies in the market?


The answer is, you can’t – we can’t – control the investor. We can’t control the way the world works these days, and the rapidity of the information flow – we can’t control that.

So you’re going to sail your ship into a storm. Here it is. That storm’s not going to go away. If anything, the storm’s going to get worse, but you’re going to sail your ship there anyway, ’cause we have to do it to support our clients. What do you do? You build to ship to handle the storm. You build the kind of resiliency into your processing flows, into your data structures, into your teams, so that you’re able to handle that kind of turbulence.

You can’t make the risk go away. You can learn to manage it.


So, I know you’re a data scientist at heart, right? No doubt. And what part of the broad symphony of data science and data governance is driving your thinking these days? I know we touched on some of that.


Yeah. Well, I’m a data science at heart because, yeah, I’ve studied it; but, more than anything else, it’s just because over the last three decades, I’ve figured that understanding where to find things before they go wrong…you get it by following the data. Let’s see…what’s the Watergate thing? “Follow the money.” Well, in our business, it’s “Follow the Data.” And the data scientist is following the data, because what you’re doing is you’re looking to find out what’s working well, and what’s not. And you’re listening carefully to what the clients are saying, ’cause it’s not just the data, and no insult to LSEG or to ICE or to David Schwimmer or Joe Sprecher, but that’s not just the data I’m talking about. I’m not just talking about pricing and a reference date. I’m not just talking about the data that it takes to price a trade, or the data it takes to report a gain or loss. I’m talking about the data that that advisor needs at the coalface. That advisor sits across the desk, the screen, from his clients or her clients, every day. What data do they need? And what are we doing to make sure that they get the data they need, when they need it?

And when we – and my guys at BetaNXT hear this all the time – we’re listening. We’ve got to make sure we’re listening to what the clients are telling us, ’cause there’s … It’s like a four note chord that you hear constantly from the clients: from Wells Fargo to AssetMark, you hear the same things constantly. First: complete, complete digitization is what they’re asking for. Complete digitization, not just the…

[points to audience] Hey, Murray! ‘Cause of the lights, I can only pick out names occasionally. Gloria, I could just see your face shining there.

Complete digitization. We’ve been talking about it for years. We can do it now, from the client to the books and records: digitization all the way through. Why? ‘Cause it empowers that advisor. It gives that advisor what she needs when she needs it.

Do you have complete digitization now? Do you?

Look at your corporate actions right now. Honestly, look at your corporate actions. Think of the work of the corporate actions from the time that announcement of corporate action comes out, until the client makes a decision, till it goes back. Look how many times you have to touch that data.

If that’s happening, you do not have complete digitization, which is the first part of the chord that clients are asking us to do. We should be doing that religiously, making sure it works, from that portal where the client touches it, all the way through the books and records, and back up to the client. Why? Because that’s what they need! The first part of these four chords is saying, we want to know what that transaction costs.

Cost basis is a good example. When that client does that transaction, they need to know what it costs, when it costs, and how they deal with it. That advisor needs to be able to see that, that day. Are you getting same-day cost basis? Are you able to do that with your advisor the same day? If you’re not, then you don’t have complete digitization. But then, you got things digitized, then you have to visualize them.

The other thing that happens when you have this much data flowing this quickly – and again, listen to the advisors, especially the ones who’ve been doing this a while – they talk about the data flowing so quickly, they can’t grasp it!

Remember that movie, the Matrix? When the guy looks at the screen, and all he sees is the code coming down? Sometimes that’s what they think about us. They think we give them all this data, which is…now it’s digitized, but it’s flowing so quickly where they can’t keep up with it. They can’t see it’s a bus coming. They can’t see the bus coming. And then: WHAM!! It hits ’em.

Part of what we have to do, and this goes to your technologists especially, is to be smart about how to take that stream of digitized data, and give it to the advisors in a way they can use it, and visualize it themselves.

And then third, they ask for something which is not something that’s normal, the normal part of our conversation, which is what I call curation. If we fully digitize the data, if we’ve actually given them the visualization they need, they still need context for it.

You know, I take my grandson to the Museum of Natural History, and he has read about the woolly mammoth, but it was only when he got in the Museum of Natural History, and he could see that display, that he got a sense for how that woolly mammoth lived, and what it ate, and how it worked with other members of its herd. It was only when he had the context [that] he truly understood it.

That’s part of what the client, the advisors, are asking us for. When you go to the client, the advisors, and they say, “I don’t just want streams of data. Even if I can see it and visualize it, I can’t do anything with it unless I can have the context.”

Again, cost basis. Do I know what it costs? Do I know how this is going to affect my tax reporting? Can I do tax optimized trading? If I don’t have that context, the data itself is necessary, but not sufficient.

And then the fourth note – and this one, I’m going to tell you, is…is a little scary – the fourth note is automation, or AI. ‘Cause if you have fully digitized data, if you have visualization, if you’re able to curate it, can you use AI to make that better for the advisor?

I’m of two minds.

First mind – this is the part of the chord you’re raising the seven; this may turn into a blues chord, I don’t know, it’s a little scary – Chris Skinner, who – a lot of you guys probably read The Financier – he wrote a good piece on this. He talks about when you have fully digitized data and advisors getting it, that’s good; but, if you’re doing it in an embedded way that doesn’t let the advisor and the client see what’s happening with their money – then even if it’s more efficient, it’s not going to be good in the long run. Because you…his survey data – which is pretty good! – says 90% of the people really want to see what’s happening with their money; want to understand it.

So, do I like the use of AI? We can talk more about it, but I’m…I’m torn. I can see good things for it; I can see good things they could do with it. I especially see, in a way, to make the advisors more productive. Advisors, when I talk to them, they don’t like the fact that they spend so much of their time doing things that aren’t working for their clients. They spend so much time swivel chairing it, and AI might help us with that, but I don’t know. That fourth note is…is a question mark in my mind…so…


How about I…




Do you envision a world where, as an investor, I can get a model portfolio where the beta’s less than one, and alpha’s oversized? [chuckles] I mean, that’s what we’re all looking for, right? So…


Do I envision a world where that’s possible? Sure! But, I also think the moon should be made of green cheese. [Laughter]


I did want to say that, to your point on corporate action, SIFMA put out a corporate action position paper, which is really a call to the industry to create, as you suggest, standardization in the age-old problem of unstructured information and dissemination of that information in the marketplace.


Seen it.


Yeah. So, I appreciate you touching on that. You know, maybe at some point, as I was thinking about what you were suggesting in this whole debate about – or, conversation – around AI, perhaps in the future, and 25 years or so from now, we’ll have two computers talking to each other on the stage, [chuckles] as opposed to people, I mean, about the direction of the industry! Who knows…


After my time!


I know you’ve done a lot of work on the world Economic Forum, and their thought leadership work, regarding the future of capital markets. How do you see data as a driving force in creating better outcomes for a broad range of investors?


Oh, I play a small part in it. If you and your firms are not aware of it, the World Economic Forum does a lot of work in this space. It’s good for us…sort of like Henry and Akash Shah from Bank of New York Mellon are people who’ve led the heavy lifting and provided a lot of the support for it. But it’s…it’s a little like SIFMA: it’s being done on the basis of doing good, not just doing well.

We put out a white paper last August. If you haven’t seen it, I recommend it. It’s called The Future Capital Markets, focused on retail investing. But in it, it spends a lot of time talking about what the clients want, and what they care about, and we’re still working on it. We’re actually working into phase two now. And it’s mostly about figuring out how the demands of the clients are changing. It’s looking at things like the democratization of private investing; private equities. It’s looking at, you know, what people are learning and the empowerment of people, through financial education. It takes all that and it turns it into – wait for it, of course – into data. Data we could look at to see where the clients are trending; to see what their demands are going to be down the road. It’s a good thing. Why? Because that’s what we are going to do.

Think of how much this business has changed in the last decade. Think about what’s changed in the last twenty years. It’s going to change that much more in the next decade! More than that, ’cause the pace is faster.

It’s good to have actually spent time and effort and money understanding where the clients are moving and where they’re headed towards. Remember what I said before, about the generational change in wealth? That’s what this is showing us.

Understanding where they’re going will help us do a better job of servicing. Giving those clients better what they’re asking for, and interestingly enough, one of the things that the first part of the paper showed was when we do that, we show them what we’re doing effectively with their data, with their inclinations; we improve their willingness to trust us; their willingness to trust institutions, which – it’s interesting, too, in terms of where it is, U.S. versus international – but, it’s also willingness to see their trusting institutions in terms of how they think we’re dealing with them, and understanding what they need, and both harvesting their demands, and protecting their interests.




Yeah, I recommend it.


So, I’m looking across this room here, and I see a lot of innovators who are driving positive change across the wealth management industry. What do you think our collective goals should be?


Well, collective goals? Well, I look across the room, I see innovators, but I also see fierce competitors. I mean, come on, look at this room: this is capitalism distilled right here. These guys are all about doing what they need to do to make sure that their businesses work. And that’s good! We’re a capitalistic business. We’re about making money, that’s – I’m not embarrassed at all to say that. At the same time, while we are fierce competitors, we also have to work together. You can’t play on a field if the field isn’t there. You can’t do something unless the industry itself is able to support you in it; you’re NOT an island.

It reminds me of…when I was a kid, my first career. I was a soldier, and I used to jump out of airplanes for a living. But one of the things you do is, when you’re jumping out of a [plane], in a military jump, you’re really tightly packed together, ’cause the idea is to get on the ground as rapidly as possible. So, you’re packed into an aircraft and you stand up, and your equipment’s behind you, and the guy you’re with’s equipment’s in front of you. And the last thing you do before the door is open, the green light comes on, and you go out the door, and the C-141, [in] the time it takes to fly over a football field, there’s thirty-two guys going out [of] that plane, just as rapidly as you can jump. And unless your equipment is properly situated – not just yours, but the guy’s behind you, and the guy’s in front of you – you get tangled and you…die. So, you’re incented to make sure that not only that your equipment works, but that his equipment works, and he has an incentive to make sure the guy behind him is checking him the way you’re…

That’s the way we are, guys.

We’re fierce competitors. We’re going to do this ourselves. We’re going to run our own businesses. We’re going to make our own decisions. At the same time, we also got to be doing this together, ’cause we’re all going out of the plane together, what, May 28th of next year, right?

T+1 happens where the green light goes on, and we’re all going out the door. Unless we’ve checked each other’s equipment, unless we’ve asked each other the question, are you seeing what I’m seeing? Do you understand where we’re going next? What are your clients saying about this? Do you have the right testing? Did you see the results of that test? Are you talking to DTCC? What did DTCC say to you? Oh, Goldman said that? What did JP Morgan say? What did Morgan Stanley say? What did Wells Fargo say? What did Stifel say?

Talking to each other about how your equipment fits is how we get through this together; how we make it work, how we serve not only our own companies, our own institutions, but we serve our clients en masse, because we check each other’s equipment, we check each other’s testing. We do it together. And we do it by asking each other the hard questions, and not being embarrassed about it! We won’t get it all right, but, talking to each other about it, and asking each other the hard questions, being willing to say, “I got it. I learned from it.” It gets us how we’ve…

I’ve done this all the way from T+5 to now, and every time we work together well, it works well. And when it doesn’t, we don’t do well, and our clients see it! Our clients’ trust in us, it’s not only about what we do for them every day to deliver their portfolio, deliver their investments, but also what we do to make sure the industry is stable, to make sure that trust stays that way.

We have done this before. We’ve done this before. I mean, how many crises have we gone through? How many times, how many major changes have we made in this industry?

And we’ve done it before and done it well. We’ll do well this time, ’cause when we know better, we do better, right?


Now we’re trying to get to, we’ve been trying to get to T+1 since 1995, so it’s been 29 years and now we have a date certain by regulatory mandate. I do want to make sure that folks know right: that the U.S. is moving on May 28th, and our Canadian partners north of the border are moving on May 27th. So that’s on our website, folks should know that; but also, checking with industry colleagues, Mexico and Bermuda have also agreed to move on the same day as we are. So that’s good, and then of course, the European and Asian colleagues are looking at this as well.


And the testing process is working well, I’m seeing it. Tim Rutka and I talk about this constantly. We are constantly here interacting with this. I actually see this, I saw the survey you guys did before, when Graham and his guys were up here.

I thought that was a pretty flaky survey, Graham. I thought that was pretty flaky. [audience chuckling]

Yeah. Yeah. I, because I…when I talk to people, and I can tell you I’m in our world, we’re spending a lot of time and a lot of effort making sure that we’re buttoned up for T+1. Yeah, it’s May 28th of next year, but that’s all too soon. We’re paying attention to it. We’re listening to make sure we’re paying attention to it. Okay?


We have a countdown clock on; I think it’s about 380 days, give or take a few days. So folks, we have a playbook. We’ve spent a lot of time working with the industry, ICI, DTCC, and our partners. So just advise folks to…we’ll have a couple of sessions on that over the next few days. Please look at all that material. It’s really important. If you have any questions, you can certainly contact me.


We’re almost out of time. Do you want to let some…


Yeah, we have a couple of questions, I think, that folks—

Voice, off camera

Sure. Our first question is: What do you see as the necessary profile of the next generation of operational leaders?


[laughs heartily] The third generation? I don’t know how many generations we’ve got here. Norm? Art? Still in the room? I think we might qualify as the first generation, and Graham and Tom and company might be the second. This would be the third generation? I don’t know.

What do I think? Well, I’ve been recruiting people into this space since the late ’80s. And I could tell you when I started out in that, I was looking for people who were industrial engineers, who could do workflow, who could do cost efficiency, who could do, ’cause – you won’t remember it, but there were huge banks of clerks at that time, getting those sheets with the holes in them at the edges – and we needed people who were able to see how that could go into a more automated fashion. That’s still a necessary part of the process, but now you also need a level of sophistication of technology. I don’t care that much about coding, ’cause right now, coding is not the point.

But I need, and this next generation needs, to have a sense for how the technology can work on a cloud-based environment: to move things more rapidly towards complete digitization, towards rapid visualization, towards on-demand curation. That technology, those technology chops are now our requirement. And you want to – and I talk to people all the time, people who are running some of my portfolio companies – and say, “Well, what are the things that you need to do to run a portfolio company in the private equity world?” That’s a start: the workflow piece, understanding the details.

Tom will remember this. I used to make you do T-accounts on my whiteboard. Remember? Okay…anybody here still remember T-accounts? No?! You need to learn your T-accounts! That kind of stuff you start with, that’s the base that’s still there. The technology chops come second. And now third, and probably most importantly these days, is, in fact, the data! Understanding data flows, understanding the applied statistics it takes to run the data in this environment. If you can’t play that game…you can’t play. You can play double A, but you can’t play in the majors.


Steve, I know we’re going to have room for one more question, because we’re running out of time. We could do this all day, but I do want to say the third generation, the young woman sitting right over there, her name is Erica Price from Fidelity. She graduated from Syracuse a number of years ago. So we do have third generation members here.


Oh, that’s really good. Hey Erica! Really! Look at this!


And we have another question here—


And it gets better, each generation!


[chuckling] Yeah, it does, it does.


[pointing to audience] One more question.

Voice, off camera

Sure. Final question here. Earlier you mentioned AI as an enabler of better wealth management services. Are there concerns about how useful AI could be, given it may need to train on confidential and protected data?


Well, as I said before, this one worries me, and I won’t tell you it’s…I’ve got an answer, a crisp answer, ’cause I don’t. But, think about it in terms of a defensive perimeter. BetaNXT has…we have 50 million investors who, every day, turn on their screens and have to interact with BetaNXT. Those 50 million investors have social security numbers, have PII. So, we have a 100+ million social security numbers that we’re dealing with. That protection comes first.

Do I want to use AI to be more efficient? Yeah, I do. But only if I could be absolutely sure, from a cybersecurity perspective, from a physical security perspective, that I’ve got that in control. AI is not…it’s not binary. It’s either yes, not AI. Yes, IR, no AI. It’s the data structures that you’re using to make the AI pipe. If you make any data out there available…HUGE risks that go with it. The risks that go in the dark web, the risks on the entire social networking schema. I don’t see that anywhere…coming near, anywhere near our investing, and… protecting our clients.

Now, when I bring it in smaller, and I get it around just the data that we use for our purposes, can I possibly see using AI in that space? Yeah, I think so. Why? Because I’m back to trying to do it in a way that balances the risk I’d be taking as long as I’m fully in control of where that data is, how it’s controlled, how it’s maintained, and then I get able to use the AI inside that to do things that are good for those advisors. Again, I’m most focused…I spend most of my time, a lot of our time, the guys that work for me get tired of it, but constantly saying, “Are we listening to those advisors? What do they think? What do they need?”

If that can be used to make them more effective, not just more efficient – yeah, efficiency counts, and I care about the dollars, we can do it more cheaply – but more effective means they get more time to spend understanding what their clients need…then that AI might be useful, under control.


I think we ran out of time about five minutes ago, Mr. Daffron, but I do want to thank you. A true legend in financial services. Let’s give it up for him! [starts clapping]

[enthusiastic applause from the audience]


Thank you.


Thank you so much, sir.

Source: SIFMA Operations 2023

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