Massive Insider Trading Through Capital One

Join me in hearing about Nan and Bonan Huang, two senior data analysts at Capital One who used their access to make millions of dollars through insider trading! This is eCrimeBytes.com Season 3, Episode 10 – Massive Insider Trading Through Capital One.

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Transcript:

00:00:00:00 – 00:00:21:39
Keith
What up, you crazy bastards! Welcome to another week of eCrimeBytes. This is where I research the court documentation and roast the criminals so you don’t have to. All right, so this week I’m bringing you massive insider trading through Capital One. Now, I’m going to stop right there. Capital One has nothing to do with this. They’re not the criminal.

00:00:21:44 – 00:00:46:46
Keith
They’re a victim in this case. All right. They because they offer credit and debit cards to companies and individuals out there, they became a victim in this case. So you can imagine they have millions of customers and not just individuals like me and my family, but they have businesses as customers. Okay. That’s going to become key here in a second.

00:00:46:51 – 00:01:08:50
Keith
All right. So let me tell you a little more about Capital One. They have this large nonpublic database of credit card transactions for their customers. You can imagine this makes sense, right? I mean, they got to when their customers pay for bills, they need to know how much they need to settle up with that vendor for their customer.

00:01:08:50 – 00:01:47:32
Keith
Right. So all this information has to be recorded somewhere. So if you’re looking at this going why do they have all this information? They just need it for their normal day to day business purposes. Okay. This is why this exists. And as you can imagine in now in today’s date and time, any time you have a big piece of a big database, a big data set like this, you’re going to have a bunch of data scientists behind the scenes running queries and analysis on it and things like that in order to figure out trends right?

00:01:47:32 – 00:02:18:24
Keith
Like, for instance, you might have a data scientist that would run different types of algorithms in order to predict who might default on their credit card payments. That’s just a normal business function that people like Capital One would have behind the scenes. Okay. So you could imagine there are people working there and they have access to this data, and it might be tempting to use this data for bad purposes.

00:02:18:24 – 00:02:21:02
Keith
But Capital One steps in and they’re like, Hey,

00:02:21:02 – 00:02:41:01
Keith
and I’m going to put on your screen for you one of the warnings that they give employees that work there and they say, Hey, we’re not going to tolerate or excuse any violations of insider trading laws, meaning you can’t use this information that I just described to you to do any type of insider trading.

00:02:41:02 – 00:03:08:29
Keith
Now, I’m going to talk in little bit, it’ll make a little more sense in a minute. Okay. But they’re now warning their employees, don’t do this, don’t take this information and do any type of insider trading with it. And then they go on in this this graphic that I’m showing you to just describe what insider trading is. Basically, in a nutshell, insider trading is trading on knowledge that’s not public.

00:03:08:33 – 00:03:14:23
Keith
Okay. Not public. Just like maybe this database that I just talked about.

00:03:14:23 – 00:03:35:47
Keith
And I wanted to highlight and I’m going to read the bottom paragraph of this warning, because this kind of this is what you would think most people would think when they have access to the data that I’m talking about. It says when in doubt, assume information is material and nonpublic and do not act upon it.

00:03:35:52 – 00:03:51:35
Keith
Simply put, you must not take part in any trading that may appear improper. So what they’re saying is, when you’re looking at this data, in your day to day duties of working here, don’t do any type of insider trading on this financial data that you have your hands on.

00:03:51:35 – 00:03:58:35
Keith
Okay. Well, guess what? There’s a couple employees that do. Okay.

00:03:58:40 – 00:04:23:16
Keith
So now enter the picture two individuals here, which I struggled at the beginning because I thought there were one at the beginning because they’re named so similarly. All right. The first individual here we’re going to talk about probably the main individual is the one that gets charged criminally, is the one that I found this case through. His name is Nan Huang, and I’m going to spell it for you.

00:04:23:17 – 00:04:47:08
Keith
His first name is spelled. N a n, just like in the computer nerd world that I’m in… not a number. That’s how it’s spelled. N A N and then his last name is spelled H u a n g. And these two individuals share the same last name. Now, I couldn’t figure out if they’re related or if this is just a common last name like Jones or how it worked out.

00:04:47:09 – 00:05:11:34
Keith
But both criminals in this case have the same last name, and I couldn’t find a family relation that I could rely upon. So it may have just been coincidence in this case. And the other individuals name his first name. Now get this. Bonan. So it’s B O N A N. I know you’re probably hearing this and going, how am I going to keep this straight?

00:05:11:38 – 00:05:37:05
Keith
I’m going to try to say Nan and Bonan. So you hear the b on Bonan and you just hear the Nan and the N. Okay, I apologize. Even those are so similar and they both share the same last name. So I can’t even use those throughout this. All right. So with that set aside, we have Nan and Bonan Huang and they are senior data analysts in the fraud department of Capital One.

00:05:37:09 – 00:06:02:31
Keith
So they are doing the job that I described a little earlier where they’re looking at this transactional data of their customers. And their typical job would be looking for fraud, maybe looking for people using stolen credit cards. They’re the people behind the scenes that I imagine build the algorithms that would text you when it would go, Hey, I see there’s this weird transaction.

00:06:02:40 – 00:06:26:49
Keith
Did you make this? I imagine they make those algorithms, or at least they go through the data to support those type of algorithms. Okay. Now they live in the Richmond, Virginia area, which is also the Glen Allen, Virginia area. It’s all kind of close around there. And they, through their job, had access to this credit card transaction database that I explained to you earlier.

00:06:26:54 – 00:07:03:20
Keith
So you can imagine basically all the financial transaction information at their fingertips. Okay. And if you have any type of criminal tendency, that’s not that’s not the access you want to have. That’s not the access you want them to have. Okay. Now there’s this thing called fiduciary duty. Now what it means is because they work there, they’re supposed to act on behalf or on the best interest of not only their their employer, but of the people that are in that transactional database.

00:07:03:20 – 00:07:23:43
Keith
Right. They’re not supposed to use it for criminal purposes. Okay. So I hope you have the stage here. Now, already. You should be saying, hey, I can’t imagine these two individuals. I got some pictures. I got some pictures of Nan. I couldn’t find any pictures of Bonan. So just hang with me, I got a bunch of pictures of Nan.

00:07:23:44 – 00:07:27:01
Keith
And you’re going to say, why are there children in these pictures?

00:07:27:01 – 00:07:47:12
Keith
And I’m just going to put the first one on the screen for you right now while I talk about this. Okay. And you say, why are you showing pictures of children with him in here and this wasn’t really my choice. Okay. Now all the pictures I could find of him, where I could attribute to him, came from him in the court documentation.

00:07:47:12 – 00:08:08:31
Keith
Okay. These are his pictures that he put in the public record to basically say, look how good of a father I am, because surprise, surprise, he was caught and charged and he needed a bunch of nice pictures to say, look, I am a nice guy and I have children and I do all these things for my children. So let me walk you through some of these pictures that I found in the court documentation.

00:08:08:36 – 00:08:31:20
Keith
This is the first picture. This is him with two children. I think I know the one on the youngest are his from other pictures, but I think both are his. And they’re just standing behind a fence. And I think they’re in China. And I’ll explain why later on because there’s a sign written in Chinese, obviously in front of him.

00:08:31:20 – 00:08:50:25
Keith
But there’s some other stuff that I’m going to introduce you to in the case in a second. And it’s kind of like he’s introducing, it’s like, hey, look, I’m out with my kids. Look, I’m spending time with my kids. Look at me. I’m not such a bad guy. Right? So the next picture is him behind a birthday cake with the youngest child, kind of like, Hey, look at me.

00:08:50:29 – 00:09:19:35
Keith
I’m enjoying his birthday celebration with probably my one year old. If I had to guess by the one candle and how young the child looks. And then you have this picture. And I was like, Gosh, I probably should have led with this picture. Right? This is both him and I think one of his children in this goldfish contraption that looks like it’s part of like this Merry-Go-Round ride of some sort.

00:09:19:40 – 00:09:36:48
Keith
And I just studied this for a little while because I was like, I didn’t understand this goldfish. He had goggles on and stuff, and I was like, no shit. I guess if a goldfish is out of water, you got to put water on his eyes so he can see correctly, Right? So that’s probably why there’s goggles on a fish out of the water.

00:09:36:53 – 00:10:03:32
Keith
But more importantly, you know, the any, any self-respecting dad will get in any contraption that looks like this for a child of that age just so that child can have a good time. So here you go. Here’s a picture of him in this crazy looking fish ride. And then this is one of my more favorite pictures here where he’s hanging on to the youngest child with this strap that goes around the back and stuff, apparently, because he’s probably just too lazy to hang on to the child.

00:10:03:37 – 00:10:25:45
Keith
I don’t know. It looked like they’re at an aquarium in this picture and he’s all proud of his child. And now this. This is where I can almost envision what’s going on inside his head. He’s reading something to I think this is the oldest child, but they are younger in this picture. If I had to guess, I don’t know, because it’s just a bunch of pictures that were in court documents.

00:10:25:45 – 00:10:50:53
Keith
But I can imagine he’s like, look, I am I am I am intricately in my children’s life. Look right here. I’m going child, let me read to you as he’s flipping through the book to maybe like a one or two year old. And then this next picture is like, child, I want you to smell these flowers as he pulls the tree branch down to the child’s face

00:10:50:53 – 00:11:08:44
Keith
and has the child smell it. And then the next picture, it’s like the child is standing in a chair and he’s like child, you look very hungry. Let me feed something to you as he feeds the child some food. Again, all these pictures in the court documentation. So by now you’ve got to be going this mother fucker… He is…

00:11:08:48 – 00:11:27:20
Keith
He is a family man. There’s no way he could do any type of electronic crime that I’m going to bring to you throughout the rest of this podcast. And then here’s another picture where it’s another birthday celebration of some sort where he’s like, Hey, look at me and my child. And the child looks up and is like, Why are you taking a picture of me?

00:11:27:20 – 00:11:50:11
Keith
I just want to enjoy my cake or whatever that they’re eating in this picture. And then you have a picture of him, and I think it’s his wife because she’s wearing a PayPal t shirt along with him. Now, if you watch all the way through, think about PayPal, because I’m going to try to mention it later on. But they’re wearing PayPal shirts because she works at PayPal.

00:11:50:15 – 00:12:11:00
Keith
Okay. I’ll connect those dots later on, because if I tell you too much now, I’m going to spoil some stuff for you. So those are the pictures that I found. And as I’m doing my research, there’s a bunch of other stuff that I found, like, he’s a loose fucking cannon on the road. I found some some some court documents that looked like he was.

00:12:11:05 – 00:12:32:56
Keith
He does a lot of speeding, at least twice that he admitted to or was charged with or was associated with. I guess I don’t know if he admitted to it, but he was at least found guilty of it. And he also an improper lane changes. Not only that, erratic lane changes. So this guy is a loose cannon.

00:12:32:56 – 00:12:58:31
Keith
So screw all those pictures I showed you. He’s not such a family man. He’s been 49 in a 35 here, which I don’t know what he was actually doing. If he had admitted or at the end of the day in the court record is 49 in a 35, that’s not much not much of a difference there. But hey, the other one, on the other hand, was 50 in a 35, which I can imagine he was probably doing more than that,

00:12:58:31 – 00:13:13:00
Keith
even. So 15 you’re kind of pushing it there Mr. Nan. And then he’s apparently a hunter, too, because in Glen Allen, Virginia, it looks like he had a hunting license in the year of 2010. All

00:13:13:00 – 00:13:15:23
Keith
right. So let me get you right to the crime. Okay.

00:13:15:23 – 00:13:26:58
Keith
This crime happened between 2012 and 2015. And as you can imagine, there’s this credit card database there at Capital One.

00:13:27:03 – 00:13:54:57
Keith
And there are other analysts that work with Nan and Bonan. And if you were to take Nan and Bonan on out of the picture for a moment and you said, Hey, Keith, between February 2012 and December of 2014, how many analysts were there? Well, there’s approximately 3800 analysts, so almost 4000 analysts. That’s a lot of analysts. Right? They all have access to this database.

00:13:54:57 – 00:14:27:04
Keith
And your next question would be how much or how often do they access that database? Well, when they later on in the investigation, they added this up. When they came back, the answer was three, about 3000 queries. So about one query per person, if you round down to about 3000 people, okay, keep that number in mind. To me, that sounds kind of low.

00:14:27:04 – 00:14:52:59
Keith
For two years, it seems like for 3000 people there would be a lot more queries. But let’s that’s the number that was in the court paperwork according to the government and the victims. So that’s what we’re going with. How many queries do you think Nan and Bonan Huang did on this database in comparison? Together, if you add those two together they did over 15,000 queries.

00:14:53:04 – 00:15:35:42
Keith
So five times the amount of everybody else in the company. I would imagine that right there, that alone should that should be a red flag. That should be some kind of cybersecurity alert of these two guys are doing 15,000 queries while you have 4000 employees over here only doing 3000 queries. That should be a huge red flag. Now, what they did, Nan and Bonan, is they looked at publicly traded companies because they have access to this financial data.

00:15:35:42 – 00:16:01:01
Keith
They would look at data only for publicly traded companies because you could easily tell which credit cards were being charged to, you know, JCPenney or some other vendor out there. Right. So they would only pick on publicly traded companies and then they would take these queries and they would aggregate their spending data to see if their business was increasing or decreasing.

00:16:01:01 – 00:16:27:26
Keith
So if I go back to the JCPenney example, if, let’s say a month one in January, if they saw them spending $1 million on their credit cards combined, and then they went to February and they saw $1.3 million being spent on credit cards, they would make an inference that JCPenney was doing better because they’re obviously spending more money.

00:16:27:31 – 00:16:57:19
Keith
Right. And according to Nan, the spending is actually he said spending is correlated to performance, at least in this scheme. Okay. Now, it’s not 100% proof here, but if you take them all combined, usually when you see the spending go up, the company is doing better. Sometimes the company’s tanking and they’re spending out of control. But that’s different story.

00:16:57:19 – 00:16:59:59
Keith
We’re talking about publicly traded companies here.

00:16:59:59 – 00:17:35:15
Keith
Now let’s talk about the inverse, right? Let’s say they’re only spending three quarter million dollars on their credit card. You could say, J.C. Penney might not be doing so well. Right. So in either case, you kind of know the performance of this company. So if you could capitalize on the fact that maybe the stock will go up or go down based upon knowing this performance data before the rest of the public does, you would make some money as a criminal.

00:17:35:15 – 00:18:01:47
Keith
Right. And that’s exactly what happened here is Nan and Bonan, they knew this information about a bunch of companies, but they knew it before the quarter and yearly earnings that are usually given to the public of the company’s performance and its financial status. They knew it ahead of time because they could see the the financial data in this in this database.

00:18:02:02 – 00:18:31:39
Keith
Okay. So what they could do is there’s this there’s this thing in stocks, okay? And I’m not going to go too deep into here other than just give you the cursory level explanation of what happened. There’s this thing in stocks called stock options. Okay. And basically the way it works is there’s two types of stock options. There’s a call option and there’s a put option Now, a call option.

00:18:31:39 – 00:18:49:37
Keith
The way it works is there’s this trickery behind the scene that I’m just going to tell you right up front, this hurts my head to even think about because there’s like borrowing of stocks and selling and just you have to have credit lines and there’s just it’s not the stock that you have probably come to learn of, just buy low, sell high.

00:18:49:39 – 00:19:22:06
Keith
Okay. Because a call is kind of like that where you expect the stock to go up. But this other thing called the put does exactly the opposite with how you borrow and sell stocks in this whole options. God, I hope I’m not confusing you. I’m trying to keep it very cursory level here. So just know you have an option of buying a call, which means I think the stocks going to go up or you have an option of buying a put, which means I think the stock’s going to go down.

00:19:22:11 – 00:20:00:56
Keith
So if you have this financial information up front, you could kind of bet, not even bet, but it’s almost a guaranteed bet. It’s a really, really well-informed bet on these public companies before they were to say publicly how they’re doing. Okay. Now, let me give you a concrete example. Okay. One concrete example out of this crime. Okay. So November 18th of 2013, what happened was Nan and Bonan

00:20:01:02 – 00:20:25:40
Keith
they they purchased 800 call option contracts. Now, again, I just explained to you call options. They are they want the stock to go up in price in order for the person that buys these options to make money. Okay. And there’s a strike price that you can buy them and he bought them at. Let’s see here. It’s $8.50 each.

00:20:25:45 – 00:20:54:41
Keith
Okay. That number is not quite as important as some other numbers I’m going to show you here in a minute. Two days later, November 20th, 2013. So he bought them prior to this. Okay. This is the important this is the important part. A press release is issued reporting positive sales figures for the third quarter of 2013. So I just told you that Nan and Bonan, they bought call options.

00:20:54:41 – 00:21:42:54
Keith
They want they’re betting on the stock going up. JCPenney, they just issued a press release saying we have positive sales figures for the third quarter. And then prior to that press release, JCPenney was trading at $8.71 per share. Okay. After this press release were there, they said, hey, we’re doing well. Stock jumped up to $9.44 per share, which might not sound like a lot, but if you own a bunch of shares, you’re going to be making a bunch of money because when you’re owning about 800 call options on it, like Nan and Bonan here and they cashed out when it was high, they made 23, almost $24,000 in profit.

00:21:42:54 – 00:21:57:33
Keith
So you can imagine for $24,000 of what they made in profit, what they did was they ran a bunch of queries out of database. And I, I say that in passing, but it was thousands and thousands of queries.

00:21:57:37 – 00:22:19:38
Keith
They picked a public company, J.C. Penney, in this case. They looked at the financial data and went, They’re spending more, they must be doing well. And then they went out and they bought the call options and J.C. Penney and J.C. Penney came out, said, Hey, we’re doing well. And then the stock went up. They cashed out the stock and they made the $24,000.

00:22:19:38 – 00:22:29:49
Keith
That was just one instance and one company. Now I imagine they did this for a bunch of companies. They did this for. I was going to read you a list of public companies here. They did it for J.C. Penney.

00:22:29:52 – 00:22:38:35
Keith
They did it for DSW. They did it for Cabella, Coach, Outer Wall, Chipotle.

00:22:38:35 – 00:22:45:35
Keith
Carter’s, Nordstrom Express, Inc, Guess, Ulta Salon.

00:22:45:35 – 00:22:57:53
Keith
Okay, so and there’s a bunch of other ones so what they did is they basically replicate what I just described to you for JCPenney to other companies and then just bet on it whether or not it went up or down.

00:22:57:53 – 00:23:09:46
Keith
Okay. And so at some point, I imagine Capital One probably figured out maybe there were too many queries being run by these people or maybe there was a bank account somewhere that said there’s too much money being made here.

00:23:09:46 – 00:23:16:16
Keith
We’re very confused on how this is all coming in. But somewhere along the lines, the SEC gets involved.

00:23:16:16 – 00:23:30:02
Keith
So the SEC, which is actually a civil lawsuit, not a criminal lawsuit. So you’re going to hear some different terms coming out of me throughout here. And I’ll try to walk you through where it’s important, but it’s kind of like an individual suing an individual.

00:23:30:02 – 00:23:59:47
Keith
But there’s a government entity as one of those parties that’s suing them. So the SEC says, we think you’ve done some insider trading, which yeah, I kind of agree. That’s exactly what I’ve described to you in this whole podcast, I think. And at the same time, Nan and Bonan, they were let go of their jobs at Capital One, which makes me think maybe they were let go first and then Capital One was like, Hey, S.E.C., you want to look at these two.

00:23:59:52 – 00:24:24:37
Keith
That’s kind of what I think happened. It wasn’t listed in the court documentation. That’s just my suspicion. Now, during the time of interest here, which is January of 2012 through January of 2015, when the government looked at some of these accounts that they owned, these trading accounts and they figured that there was about $150,000 that went into them.

00:24:24:42 – 00:24:55:20
Keith
Okay. And during the same time period, there was about $1.8 million that came out of them. That’s a pretty big increase in, you know, their seed money. There was almost what they got tenfold out of that. It’s just amazing. So whatever they’re doing for stocks right. You want to have the same tips as these two, because they’re obviously doing something right. Because what they’re doing is they’re taking their money out and then they’re putting it into other stocks and doing the same routine and then make some money, take that out.

00:24:55:20 – 00:25:25:40
Keith
Put into other stocks, do the same routine. And it built up to all this nearly $2 million. So the government figured at the end of the day, they made, the government says, about $2.8 million at the end of the day. And they said that represented approximately 1,819% return over three years. You want those guys as your stockbrokers, Right.

00:25:25:42 – 00:25:39:12
Keith
All right. So I have an actual court documentation screen capture on your screen right now where you can see both defendants’ addresses. And I was like, all right, hold my beer. We’re going to look at these, aren’t we?

00:25:39:17 – 00:25:46:35
Keith
So let’s hold onto that thought because immediately, immediately when this complaint came out, which is where this graphic came

00:25:46:35 – 00:26:05:58
Keith
from, Nan probably looked around, he was like, Fuck that shit. And he took off to China days later of being let go of his job at Capital One and this complaint coming out from the SEC. He remained there until April 23rd, 2023.

00:26:05:58 – 00:26:08:44
Keith
So let me set the stage for you if you didn’t catch that.

00:26:08:44 – 00:26:18:53
Keith
So now he had been in China from 2015 when he took off all the way up to 2023 when he was eventually caught.

00:26:18:53 – 00:26:39:49
Keith
And we’ll talk about that in a minute, that he was caught at San Francisco International Airport when he came back for a reason that I. I don’t want to spoil it for you here. So reportedly, when he took off, he went to China. He left his newlywed wife and kids and it sounded like they were like, our husband left.

00:26:39:54 – 00:27:03:23
Keith
Okay, well, I got to wrap some shit up. And like a month, month and a half went by and then they packed their stuff up and went to China, which I imagine now at this point they’re all together. And I think that point is where all those pictures came about that I showed you earlier with him, his wife and his children that he put into the court documentation.

00:27:03:28 – 00:27:22:34
Keith
Now, the SEC, they’re like, whatever, you’re in China, we don’t give a shit. Bonan is still here. We’re going to go to trial. And the government or the the court was like, Yep, yep. If he’s not going to come back, fuck him, we’re going to go to trial. So the trial actually happened from January 12th through the 13th, and this happened for Nan not Bonan.

00:27:22:34 – 00:27:35:01
Keith
And we’re going to talk about Bonan here in a minute. But Nan he’s he’s in China and his trial is now happening January 12th and 13th in 2016, he was found the equivalent of guilty.

00:27:35:01 – 00:27:45:23
Keith
So basically he’s found liable for this judgment and it ends up being $13.5 million.

00:27:45:28 – 00:28:08:17
Keith
He’s over there in China probably watching that going, fuck me! How are you to pay $13.5 million even as a criminal? That’s a lot of money to pay. And they also impose this thing called legal sanctions on him. And if you’re not a lawyer and you don’t deal with this space, probably doesn’t mean much to you. But just know that it’s not a good thing to have legal sanctions imposed on you.

00:28:08:22 – 00:28:26:36
Keith
He had that imposed on him because, you know, he went to China and all that stuff that I described to you earlier. So he’s sitting in a pretty bad position at this point because he’s looking at a 13.5 million judgment against him and the government was like, that’s fine. You don’t want to come back.

00:28:26:36 – 00:28:34:30
Keith
Hey, remember this house? Now, this house was the 2441 Hawkesbury Court in Henrico, Virginia.

00:28:34:35 – 00:28:56:10
Keith
I will put a picture on the screen here. I found this house on Google Maps for you and I found a nice clear picture for you. And it looks like it looks like a pretty pricey house around Richmond, Virginia. This is kind of in my area. So when I saw this house, I was like, he has some money. You know, if this house is maybe in Michigan or someplace more rural, I would say it’s probably an average house.

00:28:56:10 – 00:29:23:24
Keith
But out on the East Coast, this is this looks like a swanky house. So he bought it. You’re probably wondering, I did all the research on this. He bought it for $305,000 in June of 2013. Okay. When the government got its hands on it because they won. The SEC did. They sold it for $280,000. So this is in.

00:29:23:29 – 00:29:34:26
Keith
They eventually sold it in April 2018, which is about two years after the trial, and they sold it. It would be about a $25,000 loss of what he bought it for five years

00:29:34:26 – 00:29:42:09
Keith
prior. So I imagine that was like just a kick in the pants because, you know, they’re looking at that and they’re going, you owe $13.5 million.

00:29:42:09 – 00:30:01:42
Keith
We’re going to sell your house. And he’s like, God dammit! And then they’re like, oh hey and we didn’t get as much as you paid for it. So there’s an extra $25,000 you’ll be on the hook for. But we’re only going to use this $280,000 to pay off part of that $13.5 million that you owe us. Just unbelievable.

00:30:01:42 – 00:30:29:05
Keith
Right. And so I told you, hold on with Bonan because he’s watching this whole thing probably going, okay, he fled to China. God, They just had this $13.5 million judgment. Holy shit. Bonan looked and went… I’m just going to I’m to do the equivalent of pleading guilty on this one. But he doesn’t. He basically it works differently in civil lawsuits.

00:30:29:10 – 00:30:49:19
Keith
He basically does this thing where it’s kind of like pleading guilty, but he doesn’t plead guilty or say he has any responsibility. He’s just like, I’ll pay for the judgment. And they basically came back and they said, okay, your judgment, $4.7 million. And I was like, that’s a pretty big discrepancy from 13.5 earlier when we were looking at Nan.

00:30:49:19 – 00:31:08:25
Keith
So I imagine there was some logic behind almost, what, a 2 to 3 fold difference. But it is what it is. So Bonan was looking at about $5 million and Nan is looking at $13.5 million from the SEC.

00:31:08:25 – 00:31:28:04
Keith
So you can imagine they come in and they’re like, this account here, we’re going to take that. I’ll put an example on the screen of the court documentation for you now where just basically like, all these accounts here that you own, we’re just going to take that and all the money that ten of them and we’re just going to put it towards these judgments that you owe us

00:31:28:04 – 00:31:29:18
Keith
for.

00:31:29:23 – 00:31:41:17
Keith
Bonan, he’s got a House, too. I showed you Nan’s house earlier. Bonan’s house, on the other hand, was so new because he built it that I couldn’t get a profile shot of it.

00:31:41:17 – 00:31:51:29
Keith
So all I could get was this top down Google Maps photo that I’m putting on the screen for you now, which looks like it might be a nice house.

00:31:51:34 – 00:32:16:19
Keith
When I backed out and looked at the neighborhood, the neighborhood looked nice and the price that he bought it for in October for 2014 was just over a quarter I’m sorry, just over a half a million dollars. Okay. And this is again, these guys bought these houses during the crime spree. Okay. So I imagine they were spending money and trying to like live it up a little bit.

00:32:16:24 – 00:32:45:27
Keith
This house was a new construction, according to what I could tell. So that’s one of the reasons why I couldn’t get you pictures of the actual house from the side. And so then when the government took it and sold it, just like they did for Nan, they didn’t quite get half a million dollars. They actually got $395,000. So they lost, what, $105,000 on that in over a year

00:32:45:27 – 00:33:00:41
Keith
in, I’m sorry, two years of ownership of a new house. I can imagine the new person moving into that place only paying about $400,000, but getting a $500,000 house is probably like heh heh. Right?

00:33:00:41 – 00:33:12:33
Keith
But anyways, don’t don’t feel bad for Bonan, okay. Because he apparently has another home that I found. This is all this is in Glen Allen, Virginia. And I’m going to put a picture of it on your screen.

00:33:12:33 – 00:33:23:50
Keith
It doesn’t look as swanky as the neighborhood that I just showed you. And he could probably use a siding wash. If you look very closely here, it looks like there’s just a bunch of algae or something on his siding.

00:33:23:55 – 00:33:43:08
Keith
He bought this house for $100,000 in April of 2012. Looks like he tried to rent it out for a while. I’m not sure if he was able to get a renter or what. He still owns the house and it may be his main residence now, the best I can tell.

00:33:43:08 – 00:33:56:03
Keith
So in the scheme of things, you had Nan take off to China, got a judgment of $13.5 million against him from the SEC. Bonan says I’m not going to do that and he got a,

00:33:56:03 – 00:34:18:06
Keith
he basically pled guilty in a way and had about a $5 million judgment. And now an indictment comes out against both of them. And this is where it kind of gets weird. It’s against both of them. But the best I could tell, they only really pursued it against Nan. And I think maybe it was because Bonan came back and was like, Hey, I did it, I did it, I did it.

00:34:18:11 – 00:34:36:52
Keith
At least the tldr sense of I did it. I know legally he didn’t say that, but that’s what he basically did. And I imagine the government maybe took it easy on him. And then they looked at Bonan, they looked at Nan over in China, we’re like, It’s your turn now. And they charged him with just a ton of stuff.

00:34:36:57 – 00:34:54:59
Keith
Well, they charge both of them, but I’m just going to talk about Nan from here to the end. Bonan the charges just kind of stick out there as long as they don’t do anything, you know, nothing happens to him. But for Nan he looked he was looking at 26 counts. Okay. 26.

00:34:54:59 – 00:35:01:56
Keith
And I’m going to put the spreadsheet of counts two through 21 on your screen right now.

00:35:02:01 – 00:35:22:19
Keith
These are based on a bunch of different transactions that they made with insider trading. And let me go through these counts for you. The first one was the the the big one. It was conspiracy to commit insider trading. And this meant that they did it together. And then the table that you see, this is all the counts of insider trading.

00:35:22:19 – 00:35:31:28
Keith
So not only they charge them with doing it together, but they charge them with every individual count themselves of every individual trade.

00:35:31:28 – 00:35:51:18
Keith
And then there’s these counts 22 through 26, which sounds like a very generic crime that they probably just put in there so they could charge a book at him or throw the book at them. They said engaging in monetary transactions in criminally derived property.

00:35:51:22 – 00:36:17:55
Keith
My God, that sounds so generic. I mean, that sounds like almost any crime ever, right? It’s like you have you have something that was what, stolen and you did something with it that got you money. That’s how I read that crime. Now, at some point, I imagine Nan was like ahhhhh 13.5 million. Bonan he’s already out of this thing.

00:36:18:00 – 00:36:40:31
Keith
I’m just going to plead guilty. But listen, I’m not going to plead guilty to everything, okay? Not all 26 counts. That’s fucking insane. I’ll plead guilty to two counts. Count conspiracy to commit insider trading, and I’ll plead guilty to one insider trading count. We’ll just. We’ll just say count two. Okay? And then so the government, they were like, sweet.

00:36:40:33 – 00:37:21:06
Keith
He just pled guilty. So they started doing things like tallying out the amount of transactions that Nan did in this time period and stuff. And they said in order to do this crime, you actually performed over 6000 queries on the Capital One transaction database to aggregate material that wasn’t public on 216 companies. And I thought to myself, I was like, that was a that was probably a second full time job to do that many queries on that many companies to pull off this crime, that this government eventually got the guilty plea on.

00:37:21:10 – 00:38:00:04
Keith
They said you Nan with those figures that I just told you achieved a 12,929% return on your investment. My God that’s a lot. That’s a huge return. They said you accumulated a trading profit of $3.1 million. Wow. All right. And then they said the defendant, and I guess that was like combined amongst the two of them. They said the defendant. you Nan, personally took away $1.4 million of this.

00:38:00:09 – 00:38:28:06
Keith
So these two individuals, Nan and Bonan, they really I think they knew what they were doing, right. I mean, they were making some big bucks. They were good data scientists, bad, bad, bad end goal here, but they were good at what they were doing. So sentencing now rolls around for Nan and he pled guilty to two counts. So the first one I looked up was max was five years imprisonment and I was like, okay, five years.

00:38:28:06 – 00:38:49:34
Keith
That kind of sounds reasonable. Count two charge, which is the actual insider trading maximum term of 20 years in prison. I was like, my God, that was way more than I would have thought. I thought the conspiracy would have been closer to maybe ten and the insider trading would have been like five. But it was totally flipped when I did the research.

00:38:49:41 – 00:39:15:36
Keith
That’s why I always have to do the research, because I just can’t guess in these in these. And they said the fine in these cases for the first count was a quarter million dollars and the second count was up to $5 million. But he’s still staring at $13.5 million in payment to the SEC in the face, let alone this criminal penalty that he might get.

00:39:15:41 – 00:39:48:31
Keith
So you can imagine the defense goes up in the sentencing hearing and they’re like, listen, 20 years. That’s a lot of time. Even five years. A lot of time. Listen, he’s got to pay off $13.5 million. He’s going to suffer the rest of his life for this. He’s already been in jail when he’s come back and you guys arrested him at San Francisco Airport because and this is why I’m going to tell you now, his wife is a high paid I don’t know if it’s executive or what she is, but she’s highly paid at PayPal.

00:39:48:31 – 00:40:06:57
Keith
And she came back to America to make some dough. And eventually it sounds like he came back to be with her and the kids. And that’s why he was arrested at San Francisco. So there you go. That was the spoiler. And so the defense, when they’re up there talking to the judge, they said, you know, he has wife and kids.

00:40:06:57 – 00:40:14:25
Keith
Here’s all the pictures that I showed you at the beginning of this episode. He suffered. He just let him be with his family. Right.

00:40:14:25 – 00:40:17:49
Keith
He was teaching his kid how to eat. It was such a cute picture. Just let him be with his

00:40:17:49 – 00:40:28:04
Keith
family. We only want 11 months total instead of that that 20 years. And I can imagine the judge went back and probably was like, yeah, 20 years is pretty fucking stiff.

00:40:28:09 – 00:40:59:50
Keith
11 months is nothing. I’m going to give you two years. And I heard that I was like two years. That seems kind of light, but I read that except for the speeding, this guy didn’t have another criminal background. It was kind of like if he fell into crime because he was a good data scientist. Like he started seeing patterns in the data and was like, shit, I can make some money off this and that, only that he it sounded like he didn’t even know it was illegal upfront.

00:40:59:54 – 00:41:15:24
Keith
I don’t know if it was a cultural thing coming to America and maybe it’s just not illegal over there in China. I don’t know. But at the beginning he was making money and then later on he was like, shit, this is illegal. What I’m doing is illegal. And then, you know, eventually he ends up getting caught.

00:41:15:24 – 00:41:19:38
Keith
They said, Your imprisonment is going to be two years, your supervised release, very standard.

00:41:19:38 – 00:41:45:03
Keith
It’s going to be three years. And they didn’t have like any substantial restitution or anything like that, that added to the SEC $13.5 million. So that’s it. That’s the end of the case. And so I sat back and thought about this case from beginning to end, like I usually do, and I said he could have just stayed in China the whole time, never gotten caught and kept probably whatever money he made.

00:41:45:03 – 00:41:53:42
Keith
I imagine he probably transferred it at that point and lived a probably a very healthy life over in China with whatever he made here in the U.S.

00:41:53:44 – 00:41:58:21
Keith
But they came back because it sounds like she got a high paying job at PayPal.

00:41:58:26 – 00:42:01:16
Keith
You saw on their shirts in those pictures that I showed

00:42:01:16 – 00:42:27:53
Keith
you. So when he came back, he was caught and I sat there and I thought about it. I was like, even if he’s caught, though, how much is she making that now he has to pay off $13.5 million to the SEC. I just she she’s got to be very, very high in PayPal if they’re going to have any chance of paying this thing off, in my opinion.

00:42:27:58 – 00:42:52:15
Keith
Now, I think had he not run, he may have gotten away just with the civil penalty from the SEC as an insider trader and had to just deal with the 13.5 million judgment. I think maybe he wouldn’t have had to deal with the criminal penalties. But because he went to China, I think the government was like, nope, we are going to come after you now.

00:42:52:15 – 00:43:13:41
Keith
And they filed the charges against both of them. I to this day I still go back and forth. I don’t think they’re going to do anything with Bonan. Now in the court documentation, doesn’t really say one way or the other what they’re going to do with him. But I don’t think they’re going to charge him with anything criminally.

00:43:13:49 – 00:43:32:15
Keith
I mean, they did charge him, but I don’t think they’re going to go through with it and try to get prison time or take him to trial or try to make him come up with a plea. They may just leave it there and just let it go stale. Who knows? And I think that’s probably because he pled in SEC case.

00:43:32:15 – 00:43:49:37
Keith
He probably if you remember, I told you he looked at Nan was like, whoa, that was pretty stiff. And then he said, I’ll take whatever you give me. And it was $5 million judgment. I think when that point happened, the government probably started taking a easier on him than they did Nan. So that’s it. That’s the case. I hope you liked it.

00:43:49:42 – 00:44:14:25
Keith
Listen, listen, do me a favor. I pay money to pull this research. Court documents. It costs money. You wouldn’t expect it, but every court document, it’s like three, four, $5. So just pulling the the indictment and all this stuff, it costs money. So I’m not asking you to contribute to this at all. In lieu of any money for this research that I pull for you,

00:44:14:30 – 00:44:33:38
Keith
because, you know, this is my this is my tagline… I pull and read the court documentation and roast the criminal so you don’t have to. I’m not asking for money. All I want is your likes. That’s it. Just like the video. Subscribe. Subscribe. If you haven’t subscribed yet, I don’t know what you’re doing. Subscribe because I come out with an episode every week like this.

00:44:33:47 – 00:44:46:19
Keith
So please subscribe. And if you think you have a friend or two that might like this episode, this episode or this podcast, share them. Please share them.

00:44:46:19 – 00:44:55:43
Keith
So with that, I enjoyed spending this week with you and I hope you come back next week and we’ll pick up on another bonkers case. Thanks. Bye.

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