Money Matters Episode 296- Exploring the Intersection of AI and Investing W/ Ravi Koka

Ravi Koka: Money Matters Podcast Interview

October 9, 2023 . 9:57 AM . ID: 562411621

Transcript

00:00 - 00:03
[speaker unknown]
This conference will now be recorded.

00:05 - 00:09
Chris Hensley
Good morning, everybody, you're listening to Money Matters, I'm Chris Hensley.

00:10 - 00:13
Chris Hensley
It is ..., we've got a great show lined up for you today.

00:13 - 00:30
Chris Hensley
Imagine a world where artificial intelligence isn't just a figment of our imagination, but our reality that Intertwines with our daily lives, a world where the lines between man and machine blur and the digital realm becomes as tangible as the air that we breathe.

00:30 - 00:33
Chris Hensley
This isn't just the plot of a sci-fi novel, but the world.

00:33 - 00:34
Chris Hensley
We're stepping into.

00:35 - 00:38
Chris Hensley
Years ago, I delved into the pages of the book, ...

00:38 - 00:40
Chris Hensley
Answer, that was back in middle school, right?

00:41 - 00:45
Chris Hensley
Tell that painted a vivid picture of a future dominated by AI.

00:45 - 00:51
Chris Hensley
Fast-forward to today, and it's astonishing, how much of that fiction has morphed into fat.

00:51 - 01:00
Chris Hensley
But as we marvel at the advancements of AI, we must also ask how is it reshaping the industries that have stood the test of time.

01:00 - 01:09
Chris Hensley
Today, we dive into deeply into the world of wealth management around where AI is not just a tool but a game changer.

01:09 - 01:14
Chris Hensley
And I want to welcome today Ravi Coca who is the CEO and the founder of Stock snips.

01:15 - 01:17
Chris Hensley
Ravi, thank you so much for joining us this morning.

01:18 - 01:18
Ravindra Koka
Thank you.

01:18 - 01:20
Ravindra Koka
Thank you for having Makers.

01:21 - 01:22
Chris Hensley
Absolutely, absolutely.

01:22 - 01:25
Chris Hensley
Well, so, let's, Let's dive right into it.

01:26 - 01:37
Chris Hensley
Can you give your audience just a brief story into your personal connection, or, or what motivated you for exploring this intersection of, of AI and wealth management.

01:39 - 01:39
Ravindra Koka
Sure.

01:39 - 01:40
Ravindra Koka
Thanks.

01:40 - 01:42
Ravindra Koka
Thanks, Chris, for having me on this show.

01:42 - 01:47
Ravindra Koka
Uh, well, story goes back almost more than three decades.

01:48 - 02:03
Ravindra Koka
When I, you know, I came to the United States to study Computer Science, and then I had the great opportunity of working with one of the leading lights and artificial intelligence, actually.

02:03 - 02:07
Ravindra Koka
The person who invented the first speech recognition system.

02:08 - 02:20
Ravindra Koka
And that's what opened up my eyes, and I became very passionate about the use of artificial intelligence, especially natural language processing, because that's what is used for speech recognition.

02:21 - 02:37
Ravindra Koka
However, AI did not take off, in the late eighties nineties, though, it's called the AI winter, mainly because of lack of computing power, and, and also the, you know, just just the technology wasn't ready for prime time.

02:38 - 02:40
Ravindra Koka
Fast forward to today.

02:41 - 02:44
Ravindra Koka
You now have, you know, very powerful computers.

02:44 - 02:48
Ravindra Koka
Everyone's walking around with a supercomputer in their pocket, which is your smartphone.

02:49 - 02:55
Ravindra Koka
And, and, and also, there's been a quantum leap in natural language processing.

02:55 - 03:03
Ravindra Koka
What is called Large Language Models, popularized by Chat GBT, which was introduced by Open AI.

03:03 - 03:12
Ravindra Koka
However, you know, that's, that's what I've been using for the last five years, to derive sentiment by reading, large amount of articles.

03:12 - 03:18
Ravindra Koka
So, that's what I was very passionate about, is the intersection of AI and the world of investing.

03:18 - 03:21
Ravindra Koka
And that's, that's where we are today, woodstock's steps.

03:22 - 03:22
Chris Hensley
I love it.

03:22 - 03:30
Chris Hensley
Now, you mentioned quite a few things that we, just to share with listeners, the idea that this is not a new idea, this has been around for awhile, right?

03:30 - 03:43
Chris Hensley
And you talk about the, the AI winter, The idea that it, you know, that, if there was kind of a pause between the eighties and the nineties, and, and really kind of having stuff catch up, but that the large language models, this is stuff that you dealt with early on.

03:43 - 03:53
Chris Hensley
And then the idea about sentiment And I know, You know, I've explored your stock snips and that's one of the things that you're using in there.

03:53 - 04:03
Chris Hensley
So I will talk a little bit more about that, because it's fascinating to Me AI's aimed at extending human cognitive ability in the context of wealth management.

04:03 - 04:10
Chris Hensley
How do you see AI addressing challenges in enhancing the advisor client relationship?

04:12 - 04:15
Ravindra Koka
So, the, you know, you're absolutely right.

04:15 - 04:32
Ravindra Koka
What AI is, is nothing but another tool that extends human cognitive ability, just like the human motor ability was extended by, you know, like the airplane or the summary view that allowed you to explore the oceans and the skies.

04:32 - 04:53
Ravindra Koka
So, AI is going to allow humans to explore the, there are competent cognitive things, you can do, things that, otherwise, you would not be able to do such as, for example, we are reading 100,000 articles a day, and able to precisely find out what is being said about a particular company.

04:53 - 04:55
Ravindra Koka
Which humanly not possible, right.

04:55 - 04:58
Ravindra Koka
Just, you know, how many articles can you read in a day.

04:58 - 04:59
Ravindra Koka
And how much can you remember.

05:00 - 05:04
Ravindra Koka
This is where AI is very, very powerful, That's a particular use case.

05:04 - 05:12
Ravindra Koka
Um, so, in the case of wealth management, there are several areas where I see AI will get used.

05:13 - 05:17
Ravindra Koka
What's tartars, seeing the use of ...

05:17 - 05:20
Ravindra Koka
For things like communications, right?

05:20 - 05:25
Ravindra Koka
You know, organizing your e-mails or, or, you know, any other?

05:26 - 05:35
Ravindra Koka
Any other type of fun, for example, generating your newsletters or doing some research that you wanted to share with your clients.

05:35 - 05:36
Ravindra Koka
This is called Generative AI.

05:36 - 05:39
Ravindra Koka
That's the use of generate a right AI.

05:39 - 05:46
Ravindra Koka
However, the more advanced applications of AI, which is what we have been working on, is, How do you construct?

05:46 - 05:49
Ravindra Koka
How do you pick stocks based on AI algorithms?

05:49 - 06:05
Ravindra Koka
So, instead of Portfolio Manager picking stocks, you can actually use AI algorithms that can be trained so that they can see how market conditions are changing, and you are able to pick in your portfolio that they did the right stocks.

06:05 - 06:11
Ravindra Koka
So that you are able to leverage, you know, the changing market conditions and the trends in the marketplace.

06:13 - 06:35
Chris Hensley
And that alone, I mean, that's amazing to me, because, you know, as an investment advisor, we look at, you know, the headlines each, each and every day, but there's only so much, we can keep up with the idea, you mentioned 100 articles a day, that, you know, this is something that AI is really good at, compared to human, it's a, I think, but even the idea of this sentiment indicator.

06:35 - 06:47
Chris Hensley
Can you tell us a little bit more about what that means as far as, What sentiment is, you know, in context with AI?

06:48 - 06:58
Ravindra Koka
So, the, the basic hypothesis is that stock prices for any of the equities, you're whether it's US equities or global equities.

06:58 - 07:06
Ravindra Koka
It's not just driven by fundamentals, by fundamentals, may remain revenue, earnings, price momentum, things like that, right.

07:06 - 07:08
Ravindra Koka
So, these are called fundamentals.

07:08 - 07:18
Ravindra Koka
There is the behavioral finance aspect of it, which says that stock prices react to human emotions, which are, which is basically investor emotions.

07:19 - 07:23
Ravindra Koka
However, there wasn't a way to precisely measure investor emotion.

07:23 - 07:23
Ravindra Koka
Right?

07:23 - 07:25
Ravindra Koka
That's what we came up with.

07:25 - 07:38
Ravindra Koka
We came up with a set of algorithms using natural language where we read the articles, pick the relevant facts in that article attributed to the right US equity, for example.

07:38 - 07:42
Ravindra Koka
And then then also be able to say, is that what is being said?

07:42 - 07:43
Ravindra Koka
Is it positive or negative?

07:44 - 08:02
Ravindra Koka
And that basing then, of course, there's more data massaging you have to do and you come up with a measure, which is called The Daily Sentiment, that means that anytime during the day, for any of the 5000 US Equities, we were able to accurately measure and said, this is what the investor sentiment is.

08:03 - 08:10
Ravindra Koka
And we also then went ahead and proved statistically, prove that that investor sentiment is a lead indicator of price.

08:11 - 08:15
Ravindra Koka
Not not 100% of the time, but majority of the time.

08:15 - 08:19
Ravindra Koka
So that's what investor sentiment is, That's what we're measuring.

08:19 - 08:25
Ravindra Koka
And it's all algorithmic, there's no human, there's no human judgement here in the sense once the models are trained.

08:26 - 08:34
Ravindra Koka
They, it's the AI algorithms that are coming up with the score and then that score is used in constructing portfolios.

08:36 - 08:36
Chris Hensley
Nice.

08:37 - 08:40
Chris Hensley
So I know, so I'm gonna make my compliance people happy here.

08:40 - 08:53
Chris Hensley
Because anytime we talk about investing, I always want to say, you know, we as an, as an investment show that this is for educational purposes, and not one specific system is going to be all things to all people.

08:53 - 08:58
Chris Hensley
So always consult with a financial advisor before making financial decisions.

08:58 - 09:00
Chris Hensley
With that being said, what you just talked about.

09:00 - 09:11
Chris Hensley
Human emotion, investments, sentiment, these are very similar things to that equities people have looked at in the past as far as indicators and things.

09:11 - 09:20
Chris Hensley
So this isn't, This isn't that far out there, as far as things that we use, In fact, I think if we have a litmus test of things we're looking at for investing in stock.

09:20 - 09:28
Chris Hensley
The idea of sentiment is, is an important one to look at, however you use it, and then the idea that you guys are using it as a gage.

09:28 - 09:36
Chris Hensley
One of the things that you've kinda do a ranking, and it's positive or negative, right?

09:37 - 09:40
Chris Hensley
Tell us a little bit more about them, and then we'll get back to the bigger picture.

09:40 - 09:43
Chris Hensley
But I'm so fascinated about Stuxnet is I want to talk a little bit more about.

09:44 - 09:45
Ravindra Koka
Yeah, you're right.

09:45 - 09:48
Ravindra Koka
Sentiment is not new, in the old days, you know.

09:48 - 10:00
Ravindra Koka
People would know in New York and Wall Street, people would get together in a coffee shop, talk about, talk about stocks, and talk about what's going on, and what are the trends, and, you know, talk about inflation and talk about something else.

10:01 - 10:04
Ravindra Koka
But, and that's how they used to make up their mind and burden sentiment.

10:04 - 10:16
Ravindra Koka
That is one way of doing, you know, engaging what people are feeling about, about a particular equity, what has become more sophisticated, because there's been an explosion of information.

10:16 - 10:23
Ravindra Koka
In fact, IBM had a report, but 90% of all of the information has been created in the last few years.

10:23 - 10:32
Ravindra Koka
So, the question is, with this huge amount of information, including, you know, online media, you know, social media, et cetera, how do you keep up with it?

10:32 - 10:39
Ravindra Koka
That's where the algorithms are much better than what a human can keep track of the second.

10:39 - 10:45
Ravindra Koka
The second thing is that How, how would you then, there's more research.

10:45 - 10:47
Ravindra Koka
Right, You, just because you have sentiment?

10:48 - 10:58
Ravindra Koka
The other thing people look at, before I go on to what we do, is people also look at, for example, fund flows, you know, how much funds are flowing into a particular stock.

10:58 - 11:06
Ravindra Koka
For example, all people look at no report on 30 enough filings or insider trades and so on.

11:06 - 11:09
Ravindra Koka
So what it does is that these are all gages.

11:10 - 11:14
Ravindra Koka
Sentiment, but none of them are forward looking, and they are not continuous.

11:14 - 11:16
Ravindra Koka
So those are the two important things.

11:16 - 11:21
Ravindra Koka
By looking at all the news, that news captures a 360 degree view.

11:22 - 11:24
Ravindra Koka
What's your cash capturing of the ...

11:24 - 11:37
Ravindra Koka
Macro indicate a macro news, for example, what's going on in our war in Ukraine or whether it's a rise in interest rates, or whether it's oil prices and how that affects a particular stock, right?

11:37 - 11:46
Ravindra Koka
That is one type of neos the other type of neurosis specific to accompany, how are the company's products doing or how are their global sales doing?

11:46 - 11:48
Ravindra Koka
What are they having any supply chain problems?

11:49 - 11:51
Ravindra Koka
So, all of that type of information is coming in.

11:51 - 12:03
Ravindra Koka
When we talk about reading articles, we are picking up all of these things, both macro and micro indicators of, of how, you know, how, how something is going to impact that stock.

12:03 - 12:04
Ravindra Koka
So, it's a 360 degree view.

12:04 - 12:06
Ravindra Koka
The second part is, it's continuous.

12:08 - 12:10
Ravindra Koka
That means, at every instant, that is changing.

12:10 - 12:18
Ravindra Koka
It's not something, no, six weeks ago or 10 weeks ago, if you look at fund flows, that's after the fact you're going to get that information.

12:18 - 12:29
Ravindra Koka
You know, after the, for example, the, the, the, the regulatory reports have been filed and you're going to get the information much later than it's not real time.

12:29 - 12:31
Ravindra Koka
So we're doing it real time.

12:31 - 12:35
Ravindra Koka
The second part of it, what you're saying is how do you measure?

12:35 - 12:36
Ravindra Koka
So the measure is zero to 100%.

12:36 - 12:42
Ravindra Koka
So, when we say sentiment, we are translating into a score, which is zero to 100%.

12:43 - 12:45
Ravindra Koka
So, Apple may be at 80% positive.

12:46 - 12:54
Ravindra Koka
Amazon may be at 70% positive, which means that Apple has, uh, the, from an investor, sentiment perspective has a higher score than, say, Amazon.

12:55 - 12:57
Ravindra Koka
However, there's another factor.

12:57 - 13:00
Ravindra Koka
How fast is sentiment changing?

13:00 - 13:01
Ravindra Koka
Either positive or negative.

13:01 - 13:12
Ravindra Koka
For example, Amazon, in this case, Amazon, may be lower, but if it is going up, 10% incentive went from 70 to 80, and Apple is going only from 80 to 82.

13:13 - 13:15
Ravindra Koka
That means Amazon has a higher sentiment momentum.

13:16 - 13:25
Ravindra Koka
So we take that also, so our ranking takes into account both the sentiment, which is 0 to 100, and also, the change in the rate of change in sentiment.

13:25 - 13:28
Ravindra Koka
Just like just like a measure change in price.

13:28 - 13:32
Ravindra Koka
What is called price momentum, V two, sentiment momentum.

13:33 - 13:40
Ravindra Koka
The way we arrived at these factors, there were several studies done by Wall Street equity research firms.

13:40 - 13:53
Ravindra Koka
Academic studies, our own internal studies that actually ran portfolios and measured against other indicators, like RSI and price momentum, and our earnings revision estimates.

13:53 - 14:03
Ravindra Koka
These are, you know, what typically are used for by quantitative portfolio managers and they found all these studies found, that's our signal.

14:03 - 14:09
Ravindra Koka
Was holding up well and was actually a good indicator of price behavior.

14:09 - 14:10
Ravindra Koka
And that's how we enter ended up.

14:11 - 14:23
Ravindra Koka
Where we are today, which is not only do we provide an investor sentiment signal for the 5000 US Equities, but we also went ahead and start to build portfolios which pick stocks from.

14:23 - 14:27
Ravindra Koka
Whether it's from the Russell one thousand or the S&P 500.

14:27 - 14:31
Ravindra Koka
We pick the stocks that you shouldn't be holding, within a, within a given strategy.

14:33 - 14:37
Chris Hensley
So, I can see where this, for advisors, this could, This could help.

14:37 - 14:44
Chris Hensley
I mean, you know, I'm, it's no secret, I use like a total return approach for my clients and their retirees.

14:44 - 14:50
Chris Hensley
And so, that's one of the things that we use as an active manager, but there's a whole slew of different tools that you can use.

14:50 - 14:59
Chris Hensley
And this seems like just another one that you can put on there, that to give you good direction, and in that, in those, in that way.

14:59 - 14:59
Chris Hensley
Really.

15:00 - 15:11
Chris Hensley
So I'm gonna pivot for a moment, kinda go bigger picture here again because you taught, you touched earlier about the idea that AI can free up advisors time to make more personalized and impactful decisions.

15:11 - 15:17
Chris Hensley
Can you elaborate on how AI tools can help advisors tailor their services to individual clients?

15:18 - 15:28
Ravindra Koka
So, so this goes back to the big picture, if you look, look at the last decade, The passive, what is called passive, indexed investing.

15:28 - 15:35
Ravindra Koka
That means, you know, basically, there's no, these are systematic, they are tied to an index like an S&P 500.

15:35 - 15:37
Ravindra Koka
For example, the ticker SPY.

15:37 - 15:43
Ravindra Koka
So roughly 50% of all assets move to what is called passive index swaps.

15:43 - 15:48
Ravindra Koka
So actively picking stocks and managing portfolios has become a real challenge.

15:48 - 15:56
Ravindra Koka
For example, a lot of advisors who were would have their own portfolios and they would use some algorithm, maybe a dot C, right Or some some algorithm.

15:56 - 15:58
Ravindra Koka
Right, which is a momentum algorithm.

15:59 - 16:08
Ravindra Koka
That has become extremely difficult because you are not able to outperform the, the passive index, right, if you are able to beat the market.

16:08 - 16:17
Ravindra Koka
So, with the result, what has happened is, know, that there has been a lot of pressure on the fee structure, as well as the time of the advisor.

16:17 - 16:22
Ravindra Koka
Are you going to sit there picking stocks, and building portfolios and monitoring them?

16:22 - 16:24
Ravindra Koka
That's that's a lot of time.

16:24 - 16:36
Ravindra Koka
So that takes away time that you would otherwise be spending with financial planning, client relationship, you know, advising your clients on how to meet their investment goals, et cetera.

16:36 - 16:36
Ravindra Koka
Right?

16:36 - 16:48
Ravindra Koka
So, that's what a, an algorithmic systematic AI based approach and picking the stocks and managing the portfolio, as not necessarily as a core strategy.

16:48 - 17:00
Ravindra Koka
But as a satellites or sleep strategy, you might still have the core strategy, could be, could be bonds, so it could be, you know, a passive fund like, a, like an S&P 500 fund.

17:00 - 17:09
Ravindra Koka
However, if you want to capture alpha times when the market it's a bull market, then you don't want to lose out on that extra alpha.

17:09 - 17:13
Ravindra Koka
Because, you know, you want to do slightly better than what the market does.

17:13 - 17:14
Ravindra Koka
That's where.

17:14 - 17:18
Ravindra Koka
No, you need, you need an active strategy, along with your core strategy.

17:19 - 17:25
Ravindra Koka
And an AI based strategy, especially if it's systematic and low cost without any human byes.

17:26 - 17:36
Ravindra Koka
And obviously, it must have a track record, and it should perform, that would relieve the advisor, and spend more time with the client requirements and his goals.

17:36 - 17:40
Ravindra Koka
And at the same time, be able to manage the portfolio.

17:40 - 17:44
Ravindra Koka
Instead of just a standard 640, 6040 did not work very well.

17:44 - 17:49
Ravindra Koka
In 20 22, it went down, 90, 800, 19%, right?

17:49 - 17:53
Ravindra Koka
So, a lot of clients are saying, you know, What have you done for me?

17:53 - 17:57
Ravindra Koka
How are you going to, you know, navigate when?

17:57 - 18:00
Ravindra Koka
When there's a bull market and when there's a bear market.

18:00 - 18:10
Ravindra Koka
And this is where active strategies have to be part of the mix, you know, when, when you're building a building, a broader set of asset, classes for your plots.

18:12 - 18:13
Chris Hensley
I love it, I love it.

18:13 - 18:14
Chris Hensley
This is all good stuff.

18:15 - 18:18
Chris Hensley
Data is indeed crucial for AI applications.

18:18 - 18:27
Chris Hensley
Could you explain how wealth management firms can effectively gather, process, and leverage data, to deliver better financial advice and strategies?

18:29 - 18:36
Ravindra Koka
Um, I think the data part, that, there are more, and more tools becoming available.

18:36 - 18:42
Ravindra Koka
I mean almost, whether it's Morningstar, whether it's any, any of the tab platforms, 30 use.

18:42 - 18:50
Ravindra Koka
You're going to see much and much more, you know, sophisticated analysis that AI is going to allow.

18:50 - 18:53
Ravindra Koka
Think of these as personalized Co-pilot's.

18:53 - 18:58
Ravindra Koka
So think of you think of every advisor walking around with a personalized co-pilot.

18:58 - 19:07
Ravindra Koka
Which means that the type of data that it's going to alert you to is very specific to your clients and in their client portfolios.

19:07 - 19:16
Ravindra Koka
As opposed to just, you know, right now you get broad market information saying, well, the market's going down, because, know, something is happening in.

19:16 - 19:18
Ravindra Koka
Oil prices are going down.

19:18 - 19:19
Ravindra Koka
It's dragging the market down.

19:20 - 19:21
Ravindra Koka
That's useful.

19:21 - 19:22
Ravindra Koka
But that's not personalized.

19:22 - 19:25
Ravindra Koka
That's nothing specific to a person's portfolio.

19:26 - 19:52
Ravindra Koka
So that's where AI can be tailored and, and then you can actually personalize it So that no, for example, if if a particular portfolio has more exposure to certain sectors and something is going on in that sector, the this this this will analyze the data and say look: 40% of this person's portfolio is impacted by these sectoral shifts.

19:52 - 19:53
Ravindra Koka
So you better give give.

19:53 - 19:59
Ravindra Koka
Notice you give no more attention to that and maybe maybe even do a rebalance, right?

19:59 - 20:00
Ravindra Koka
That might even trigger.

20:00 - 20:03
Ravindra Koka
You may sit down with your client and say, look, this is what's going on.

20:04 - 20:09
Ravindra Koka
And, you know, we better, maybe there's, maybe nothing happens, maybe it's just a discussion.

20:09 - 20:20
Ravindra Koka
But the whole way in which you are dealing with clients and the amount of information you're using, is this going to dramatically increase?

20:21 - 20:40
Ravindra Koka
And you're going to look, you know, in terms of your client, you're going to look, the value you are going to add is going to be much, much superior than broad brush, newsletters and broad brush in all market trends, which is what, you know, a lot of the AFL firms do today, which, which is very difficult for me as an individual investor.

20:41 - 20:45
Ravindra Koka
How am I going to figure out what all this means to me, to my portfolio?

20:45 - 20:46
Ravindra Koka
What should I do?

20:46 - 20:48
Ravindra Koka
That's what, that's what the client is asking, right?

20:49 - 20:54
Ravindra Koka
That's, that's where I think personalization, using AI, co-pilots, going to help you.

20:55 - 20:55
Chris Hensley
I love it.

20:55 - 20:56
Chris Hensley
I love it.

20:56 - 21:06
Chris Hensley
And I've actually, in real life, been doing a test case, or a use case for the, this is for when we do review meetings.

21:06 - 21:10
Chris Hensley
We've been doing for the virtual ones like this, where you and me are talking live.

21:10 - 21:20
Chris Hensley
I've added a company called ..., where they do voice transcription for the meetings, but it's more than that, because it brings in AI.

21:20 - 21:31
Chris Hensley
So, what happens is, if I do a review meeting, at the end of that meeting, it's taking all of the dialog and put it into a set of notes.

21:32 - 21:47
Chris Hensley
And it's a real sharp set of nodes, because I've been able to kinda set it up for myself as a template, and it also, what we've talked about earlier, the sentiment, that's the part that's amazing to me, because it will point out positive experiences in that meeting, negative experiences in the meeting.

21:47 - 21:48
Chris Hensley
And it's a real time saver.

21:48 - 21:53
Chris Hensley
I don't know if you see it, but I'm sitting here taking notes, since I don't have it going right now.

21:53 - 21:55
Chris Hensley
I know I'm an Obsessive Notetaker, right?

21:56 - 22:02
Chris Hensley
What it allows me to do is listen more, really allows, you know, goes in there and it records it and that sort of stuff.

22:02 - 22:05
Chris Hensley
So just what we're talking about, these time savers, these things.

22:05 - 22:07
Chris Hensley
It's kinda like you mentioned a co-pilot there.

22:08 - 22:14
Chris Hensley
Let's, let's shift and talk about because we've only got a few minutes here before we hit the end of the show talk, about risk assessment.

22:14 - 22:24
Chris Hensley
You know, I consider myself a risk manager above all things, That's what, you know, especially since my clients are retirees, That's what we're using active management, That's what they're hiring me for risk.

22:25 - 22:27
Chris Hensley
Assessment is a critical aspect of wealth management.

22:28 - 22:35
Chris Hensley
Can you delve into how AI technologies contribute to identifying and mitigating risk in an investment portfolio?

22:36 - 22:36
Ravindra Koka
Right?

22:36 - 22:51
Ravindra Koka
So, what AI has established or proven is that, they can identify, patterns, patterns that are not necessarily linear patterns, non-linear patterns, and also timeliness, right?

22:51 - 23:00
Ravindra Koka
The ability to go through large amounts of information on a short period of time, that's where risk management will start to see, start to leverage that.

23:00 - 23:00
Ravindra Koka
Right.

23:00 - 23:18
Ravindra Koka
Because, again, risk management, at a very high level, the risk management is, Do I move into cash, or do I no rebalanced by portfolio to, know, either increase or lower my equity exposure versus bonds versus cash, or That's the kind of risk management that an advisor does.

23:19 - 23:19
Ravindra Koka
And, yes, you can.

23:20 - 23:23
Ravindra Koka
There is help there Also, for example, Can you make that dynamic.

23:23 - 23:26
Ravindra Koka
Can you make that more adaptive instead of a fixed 60 party?

23:27 - 23:32
Ravindra Koka
Can you, if it's a bull market and you want 70, 30, or 82, how do you decide that, right?

23:32 - 23:37
Ravindra Koka
Obviously, that there's a risk associated with it and aeritalia associated with it.

23:37 - 23:58
Ravindra Koka
So, AI can actually balance those types of no competing goals and say, look on a risk adjusted basis, we think, you know, the allocation should be this, More importantly, the time, the timeliness of the alert in an intelligent agent, should be able to deliver an alert?

23:59 - 24:01
Ravindra Koka
No, at the right time, at the right place, right?

24:01 - 24:05
Ravindra Koka
There's no point in delivering an alert after the fact, it's too late, right?

24:06 - 24:09
Ravindra Koka
And that's what happens with most of the risk stuff.

24:09 - 24:13
Ravindra Koka
By the time you you react to something, it's too late.

24:13 - 24:19
Ravindra Koka
So, it's the question here is: the problem is, again, this is not, this is a lot of hard work, and there's more work to do.

24:20 - 24:27
Ravindra Koka
But, there will be sophisticated AI tools, risk management tools, which will become available.

24:27 - 24:36
Ravindra Koka
Dart will allow you to be much more, much faster in terms of your actions, when some, some conditions are changing.

24:37 - 24:45
Ravindra Koka
And this is, this is again a combination of specific information about a company or broad sectoral, shifts that, that happen.

24:45 - 24:48
Ravindra Koka
So that's, that's, that's the promise.

24:48 - 24:49
Ravindra Koka
We're not there yet.

24:49 - 24:56
Ravindra Koka
Just just to be clear, I do not know of risk management tool that's going to be exactly right every time.

24:56 - 25:03
Ravindra Koka
However, they're getting more and more sophisticated The big the big guys like JP morgan.

25:03 - 25:14
Ravindra Koka
They're beginning to use AI more in the risk management than for example, generating Alpha because they're sitting on a large amount of data, and they are using that too.

25:15 - 25:22
Ravindra Koka
You know, find patterns and be able to alert their clients and their advisors much sooner than other ones.

25:23 - 25:29
Chris Hensley
Alright, and so we are, we've got about four minutes left, and I've got the big one for you.

25:29 - 25:30
Chris Hensley
This one is important.

25:30 - 25:41
Chris Hensley
Because as AI plays an increasing role in finance ethical and regulatory aspects becomes significant, What are some of the challenges wealth management professionals should anticipate in this regard?

25:43 - 25:44
Ravindra Koka
Yes, there's a lot of debate.

25:44 - 25:56
Ravindra Koka
In fact, last night on 60 Minutes, Geoffrey Hinton, but one of the fathers of modern AI, he was there talking about the potential problems of AI.

25:56 - 25:56
Ravindra Koka
He's here.

25:56 - 26:06
Ravindra Koka
He's the one who created this neural networks, which led to the creation of large language models and all the other type of models that you're seeing, Chad U.p.d., and so on.

26:07 - 26:16
Ravindra Koka
And he was warning that if these models could: could could get so smart that they could, they'll get better than humans, right?

26:16 - 26:18
Ravindra Koka
So that's the one very high level risk.

26:19 - 26:30
Ravindra Koka
I don't think in the asset management world, there's always going to be oversight, the regulatory industry, So I do think the SEC is going to step in and port guidelines that they already have.

26:30 - 26:36
Ravindra Koka
For example, if you're going to use an AI model, I would ask the following questions, right?

26:36 - 26:44
Ravindra Koka
Just like you would ask of any portfolio, any new strategy, who, who is the, who are the people who created this strategy?

26:45 - 26:48
Ravindra Koka
What are, what are their backgrounds are the ethical people?

26:48 - 26:51
Ravindra Koka
Are there people who have knowledge of this particular area?

26:51 - 26:54
Ravindra Koka
The second question is, what data are they using?

26:54 - 26:58
Ravindra Koka
You know, the third one is, What are the algorithms?

26:58 - 26:59
Ravindra Koka
How?

26:59 - 27:01
Ravindra Koka
How have these algorithms been tested?

27:02 - 27:09
Ravindra Koka
Do they have no experience with live trading, not just some back test, but they proven themselves and live trading.

27:09 - 27:12
Ravindra Koka
So, these are all, again, What I'm saying is not new.

27:12 - 27:13
Ravindra Koka
I'm pretty sure.

27:14 - 27:19
Ravindra Koka
Whenever you look at any new strategy, these are all the basic things that you would ask.

27:19 - 27:25
Ravindra Koka
So in that sense, an AI strategy is nothing but a more advanced quantitative strategy.

27:25 - 27:29
Ravindra Koka
So you would ask the same questions, and you would ask saying, Show me.

27:29 - 27:33
Ravindra Koka
Show me, you know, show me what, you know, explained to me, all of these things.

27:34 - 27:39
Ravindra Koka
And then you can make, you can make your own judgement on, is this a risk that your willing to take.

27:40 - 27:42
Ravindra Koka
One question people ask is, are we too late?

27:42 - 27:47
Ravindra Koka
The answer is no, you're absolutely not late, is it the right time?

27:47 - 27:55
Ravindra Koka
I absolutely think it is the right time because these are early, early days of AI, whoever gets, you know, the early bird catches, the worm, right?

27:55 - 28:02
Ravindra Koka
So, whoever gets then, and get some experience under the belt, will be able to serve their clients better than others.

28:03 - 28:19
Ravindra Koka
You would need experience with picking an AI strategy, you know, trying, trying it out, Seeing what the experience is, then you're in a much better position as the as this AI wave starts to take off, then you are not late to the game.

28:19 - 28:28
Ravindra Koka
This, this is the right time, I believe, to get in because of the technology has has matured and there are more and more AI strategy is becoming available.

28:29 - 28:30
Chris Hensley
Ravi, thank you so much.

28:30 - 28:31
Chris Hensley
This is fascinating.

28:31 - 28:37
Chris Hensley
I could sit here and talk to you about this for another half-hour but we're we're right here at the end of the show.

28:37 - 28:40
Chris Hensley
For listeners who would like to learn more about Ravi.

28:40 - 28:43
Chris Hensley
Ravi, what's the best website for them to reach out to you?

28:43 - 28:47
Ravindra Koka
It's WWW dot stock snaps dot AI.

28:48 - 28:51
Ravindra Koka
I repeat, are WWW dot ...

28:51 - 28:56
Ravindra Koka
Dot AI, that'll give you a lot of information about how we are using AI in the world of investing.

28:57 - 29:04
Chris Hensley
Is there anything I forgot to ask you that you'd like to share with listeners to leave them on a note here?

29:05 - 29:13
Ravindra Koka
I think, yeah, I think you did a pretty good job of covering all the way from the origins of AI to, to how it's impacting investing.

29:13 - 29:16
Ravindra Koka
So I think at all, there's a lot to chew on here.

29:16 - 29:21
Ravindra Koka
So, and I'm happy to do another follow on, if there's more interests, I'm happy to do more.

29:22 - 29:28
Ravindra Koka
Deep dive and get into specifics of how a particular AI portfolio model performs.

29:29 - 29:31
Chris Hensley
I love it, I love it, Robi, Thank you so much.

29:31 - 29:32
Chris Hensley
Have a good rest of the day there.

29:33 - 29:34
Ravindra Koka
Thank you, Chris.

29:34 - 29:35
Ravindra Koka
Thank you very much for having.

29:35 - 29:37
Ravindra Koka
And thank you all for listening.