1 00:00:02,480 --> 00:00:06,840 Speaker 1: Bloomberg Audio Studios, podcasts, radio news. 2 00:00:08,320 --> 00:00:11,320 Speaker 2: When Sandeep mcganty first moved to the US from India 3 00:00:11,360 --> 00:00:14,440 Speaker 2: for college, he had a passion for technology and a 4 00:00:14,520 --> 00:00:16,200 Speaker 2: laser focus on the future. 5 00:00:16,480 --> 00:00:19,560 Speaker 3: I was a teenager that was hoping to build a 6 00:00:19,560 --> 00:00:22,600 Speaker 3: whole new life and whole new career and trying to 7 00:00:22,680 --> 00:00:25,840 Speaker 3: see where my lux are all my hard work takes me. 8 00:00:25,920 --> 00:00:28,800 Speaker 2: At that point, after getting a computer science degree from 9 00:00:28,840 --> 00:00:32,440 Speaker 2: Arizona State University, he teamed up with a fellow Asulum 10 00:00:32,479 --> 00:00:33,639 Speaker 2: to launch a startup. 11 00:00:33,880 --> 00:00:37,280 Speaker 3: It's an AA powered real estate investment platform. We run 12 00:00:37,560 --> 00:00:40,120 Speaker 3: the models on the back end, predicting the revenue of 13 00:00:40,320 --> 00:00:43,760 Speaker 3: a short term real estate investments or a commercial real 14 00:00:43,840 --> 00:00:44,760 Speaker 3: estate investments. 15 00:00:45,159 --> 00:00:47,960 Speaker 2: Sindeep said. They raised four hundred thousand dollars from a 16 00:00:47,960 --> 00:00:51,280 Speaker 2: private investor and turn their idea into a company valued 17 00:00:51,320 --> 00:00:54,160 Speaker 2: at over a million dollars. It was just a few 18 00:00:54,240 --> 00:00:56,120 Speaker 2: years into his time in the US and he was 19 00:00:56,160 --> 00:00:58,080 Speaker 2: already on track to build the kind of life and 20 00:00:58,160 --> 00:01:01,920 Speaker 2: career he dreamed of as a teenager, but something else 21 00:01:02,040 --> 00:01:04,880 Speaker 2: loomed over him. He'd managed to stay in the country 22 00:01:04,959 --> 00:01:08,440 Speaker 2: legally through a student visa and a series of work authorizations, 23 00:01:08,959 --> 00:01:12,000 Speaker 2: but a status in the States was still temporary, and 24 00:01:12,040 --> 00:01:14,400 Speaker 2: that meant he was living with a lot of uncertainty 25 00:01:15,160 --> 00:01:17,720 Speaker 2: and throughout all this sun deep did your immigration status 26 00:01:17,720 --> 00:01:20,600 Speaker 2: weigh on you at all? How did it impact your work? 27 00:01:21,120 --> 00:01:24,679 Speaker 3: So that's been the whole problem. You can't have a 28 00:01:24,760 --> 00:01:28,679 Speaker 3: solid decisions or like anything solid till you have your 29 00:01:28,720 --> 00:01:32,120 Speaker 3: immiglations plans solid because you can't buy a house, or 30 00:01:32,160 --> 00:01:35,320 Speaker 3: you can't build a business, or you can't do whatever 31 00:01:35,360 --> 00:01:37,720 Speaker 3: you are looking for in your life. It's not something 32 00:01:37,959 --> 00:01:41,200 Speaker 3: you can be stable on. It impacts in every decision 33 00:01:41,240 --> 00:01:42,640 Speaker 3: that you are making in your life. 34 00:01:42,920 --> 00:01:46,040 Speaker 2: Sundeep wanted a more long term plan, so he stepped 35 00:01:46,040 --> 00:01:48,120 Speaker 2: away from the day to day of running his startup, 36 00:01:48,480 --> 00:01:51,640 Speaker 2: got a job at another US based company, and set 37 00:01:51,640 --> 00:01:55,000 Speaker 2: his sights on the H one B, a visa designed 38 00:01:55,040 --> 00:01:58,760 Speaker 2: for highly skilled workers with employers in the US. A 39 00:01:58,800 --> 00:02:01,400 Speaker 2: limited number of H one BE visas are handed out 40 00:02:01,440 --> 00:02:04,520 Speaker 2: each year through a lottery system, and the first time 41 00:02:04,560 --> 00:02:09,240 Speaker 2: he applied he wasn't picked, or the next or the next. 42 00:02:09,560 --> 00:02:13,600 Speaker 3: It was really devastating for me. I was like eighty 43 00:02:13,680 --> 00:02:17,239 Speaker 3: years into the United States and I still don't have 44 00:02:17,680 --> 00:02:20,440 Speaker 3: a life which I can rely on or a carrier 45 00:02:20,520 --> 00:02:22,560 Speaker 3: that I can rely on, so I don't have a 46 00:02:22,560 --> 00:02:24,240 Speaker 3: clarity on what I need to do. 47 00:02:25,720 --> 00:02:29,000 Speaker 2: Sandeep had the job and the sponsor, but his lottery 48 00:02:29,000 --> 00:02:30,200 Speaker 2: ticket wasn't drawn. 49 00:02:30,600 --> 00:02:35,600 Speaker 1: His qualification didn't matter. He's investment and entrepreneurship didn't matter. 50 00:02:36,040 --> 00:02:39,240 Speaker 1: The fact that he was already employing people and starting 51 00:02:39,240 --> 00:02:43,040 Speaker 1: a company here didn't matter. It was a complete game 52 00:02:43,080 --> 00:02:43,480 Speaker 1: of luck. 53 00:02:43,880 --> 00:02:47,160 Speaker 2: Eric vonn is an investigative data reporter at Bloomberg and 54 00:02:47,200 --> 00:02:49,560 Speaker 2: for the past few months he's been looking into how 55 00:02:49,600 --> 00:02:52,400 Speaker 2: the h to one B system actually works, and he 56 00:02:52,520 --> 00:02:55,680 Speaker 2: found that there's something else at play, making that game 57 00:02:55,720 --> 00:02:59,320 Speaker 2: of luck even more precarious, and it's stacking the deck 58 00:02:59,400 --> 00:03:05,880 Speaker 2: against work and employers who seem to be doing everything right. Today. 59 00:03:05,919 --> 00:03:09,440 Speaker 2: On the show, a Bloomberg investigation reveals how companies have 60 00:03:09,480 --> 00:03:12,840 Speaker 2: been exploiting loopholes to gain the H one B system 61 00:03:13,040 --> 00:03:15,680 Speaker 2: and what that could mean for hundreds of thousands of 62 00:03:15,760 --> 00:03:26,040 Speaker 2: visa hopefuls. Every year, employers in the US submit hundreds 63 00:03:26,080 --> 00:03:29,320 Speaker 2: of thousands of applications for H one b's, hoping to 64 00:03:29,360 --> 00:03:32,280 Speaker 2: give their employees a shot at a visa. N H 65 00:03:32,360 --> 00:03:34,880 Speaker 2: one B typically lasts up to six years and is 66 00:03:34,920 --> 00:03:38,240 Speaker 2: often an on ramp to permanent residency. The number of 67 00:03:38,280 --> 00:03:41,560 Speaker 2: visas awarded every year is currently capped at about eighty 68 00:03:41,600 --> 00:03:44,480 Speaker 2: five thousand. But when Eric tried to figure out the 69 00:03:44,600 --> 00:03:47,720 Speaker 2: chances of getting one, he noticed that between twenty twenty 70 00:03:47,760 --> 00:03:50,920 Speaker 2: and twenty twenty three, the number of applications for that 71 00:03:51,040 --> 00:03:55,040 Speaker 2: limited pool had doubled. That meant the odds of getting 72 00:03:55,040 --> 00:03:57,800 Speaker 2: an H one B visa were getting worse fast. 73 00:03:58,400 --> 00:04:00,760 Speaker 1: So as I talk to my friend, they said, go 74 00:04:00,880 --> 00:04:04,720 Speaker 1: on line. It became very apparent that there's a huge 75 00:04:04,720 --> 00:04:06,240 Speaker 1: problem in the system. 76 00:04:06,120 --> 00:04:08,480 Speaker 2: And that problem goes back to the way the system 77 00:04:08,600 --> 00:04:09,240 Speaker 2: was designed. 78 00:04:09,840 --> 00:04:12,880 Speaker 4: Since the very beginning, the program has sort of been 79 00:04:12,960 --> 00:04:17,760 Speaker 4: dogged by concerns that certain companies were kind of finding 80 00:04:17,800 --> 00:04:22,720 Speaker 4: a way to get a disproportionate share of the visas. 81 00:04:23,800 --> 00:04:27,840 Speaker 2: That's Bloomberg investigative reporter Zachmeider. He says the flaws in 82 00:04:27,880 --> 00:04:29,920 Speaker 2: the system trace back to the way that H one 83 00:04:30,000 --> 00:04:33,159 Speaker 2: B program was set up in response to pressure from 84 00:04:33,200 --> 00:04:36,120 Speaker 2: tech companies that started building in the nineteen eighties. 85 00:04:36,520 --> 00:04:40,160 Speaker 4: Employers in the US were telling Congress, we can't get 86 00:04:40,240 --> 00:04:43,880 Speaker 4: enough workers in certain fields, especially kind of high tech fields, 87 00:04:44,240 --> 00:04:47,719 Speaker 4: and so when Congress reformed its immigration laws in nineteen 88 00:04:47,760 --> 00:04:50,320 Speaker 4: ninety they said, we're going to create this category of 89 00:04:50,440 --> 00:04:53,360 Speaker 4: visa called H one B that's going to be specifically 90 00:04:53,400 --> 00:04:56,560 Speaker 4: for kind of high skilled workers that you don't think 91 00:04:56,600 --> 00:04:58,560 Speaker 4: you can find in the American job market. 92 00:04:59,120 --> 00:05:02,640 Speaker 2: At first, this system was first come, first serve. The 93 00:05:02,760 --> 00:05:05,680 Speaker 2: vision was that employers would apply for the visas gradually 94 00:05:05,720 --> 00:05:08,560 Speaker 2: throughout the year, and once they ran out, the government 95 00:05:08,600 --> 00:05:11,640 Speaker 2: would stop granting them. But by the mid two thousands 96 00:05:11,680 --> 00:05:14,479 Speaker 2: it was clear that the system needed to change because 97 00:05:14,520 --> 00:05:18,239 Speaker 2: on April first every year, when the visa application window opened, 98 00:05:18,600 --> 00:05:23,360 Speaker 2: the United States Citizenship and Immigration Services Office would be overrun. 99 00:05:23,720 --> 00:05:28,719 Speaker 1: Hundreds of thousands of applications would comeing in literal paper 100 00:05:28,760 --> 00:05:33,000 Speaker 1: boxes from FedEx, and the US government would have so 101 00:05:33,120 --> 00:05:36,760 Speaker 1: much trouble process in those paperwork there wasn't enough time 102 00:05:36,800 --> 00:05:40,520 Speaker 1: for them to figure out who came first and who 103 00:05:40,600 --> 00:05:44,640 Speaker 1: came second. It became a necessity to run a random. 104 00:05:44,360 --> 00:05:49,000 Speaker 2: Lottery, a random lottery with very expensive tickets. 105 00:05:49,360 --> 00:05:54,000 Speaker 1: Imports had to file a full visa application, which run 106 00:05:54,440 --> 00:05:57,239 Speaker 1: hundreds of pages. They have to pay thousands of dollars 107 00:05:57,320 --> 00:06:01,360 Speaker 1: in application fees. They have to describe exactly what job 108 00:06:01,440 --> 00:06:04,839 Speaker 1: they want to fail here's the individual, here's the job, 109 00:06:05,080 --> 00:06:07,159 Speaker 1: here's the salary we kind of pay them. Here's the 110 00:06:07,160 --> 00:06:08,880 Speaker 1: location to go work from. 111 00:06:09,040 --> 00:06:11,600 Speaker 2: But in any lottery, the odds of winning go up 112 00:06:11,680 --> 00:06:14,800 Speaker 2: if you buy more tickets. The same principle applied to 113 00:06:14,839 --> 00:06:17,760 Speaker 2: the H one B lottery. Employers who could submit more 114 00:06:17,800 --> 00:06:21,239 Speaker 2: applications had a better chance of getting their employees' visas, 115 00:06:21,839 --> 00:06:24,839 Speaker 2: and zach says that gave an advantage to certain types 116 00:06:24,880 --> 00:06:29,960 Speaker 2: of companies, like huge it outsourcing firms mostly based overseas. 117 00:06:30,240 --> 00:06:34,120 Speaker 4: Let's say you're an outsourcing company that has two one 118 00:06:34,200 --> 00:06:38,280 Speaker 4: hundred thousand workers in India and you have a need 119 00:06:38,320 --> 00:06:41,240 Speaker 4: for a certain number of those workers to be in 120 00:06:41,279 --> 00:06:44,400 Speaker 4: the United States for a certain period of time. If 121 00:06:44,440 --> 00:06:47,560 Speaker 4: you say, figure you need a thousand of them next year, 122 00:06:48,279 --> 00:06:51,719 Speaker 4: but you're not too particular about which thousand, then you 123 00:06:51,760 --> 00:06:54,479 Speaker 4: can simply do the math and you could say, well, 124 00:06:54,480 --> 00:06:58,000 Speaker 4: my chances of success in the lottery are are, you know, 125 00:06:58,040 --> 00:07:01,960 Speaker 4: twenty five percent, and I need one thousand people. So 126 00:07:02,080 --> 00:07:04,760 Speaker 4: I'll put in four thousand applications of people who would 127 00:07:04,800 --> 00:07:07,880 Speaker 4: be good enough at those roles and I'll get about 128 00:07:07,880 --> 00:07:11,280 Speaker 4: one thousand. And so while your company that just had 129 00:07:11,280 --> 00:07:13,640 Speaker 4: the one worker has a twenty five percent chance of 130 00:07:13,680 --> 00:07:16,480 Speaker 4: getting what they want. The outsourcing company can kind of 131 00:07:16,560 --> 00:07:20,200 Speaker 4: leverage its foreign workforce to get one hundred percent of 132 00:07:20,240 --> 00:07:21,080 Speaker 4: the visas they want. 133 00:07:21,640 --> 00:07:25,320 Speaker 2: In twenty twenty, the Trump administration changed the application process. 134 00:07:25,880 --> 00:07:28,840 Speaker 2: Instead of entering the lottery with a full fledged application, 135 00:07:29,320 --> 00:07:31,679 Speaker 2: employers would only need to fill out a short form 136 00:07:31,800 --> 00:07:34,440 Speaker 2: and pay a ten dollars fee to get their employee's 137 00:07:34,480 --> 00:07:38,120 Speaker 2: name in the mix. Then, only if their lottery ticket 138 00:07:38,160 --> 00:07:40,040 Speaker 2: was drawn would they need to go through with the 139 00:07:40,080 --> 00:07:43,680 Speaker 2: whole application. The goal was to cut down on paperwork 140 00:07:43,760 --> 00:07:47,400 Speaker 2: and save money, but it also had another effect. 141 00:07:47,480 --> 00:07:52,960 Speaker 1: And that massively increase the opportunity to flood the lottery. 142 00:07:54,200 --> 00:07:57,040 Speaker 2: When tickets got cheaper in twenty twenty, Eric and Zach 143 00:07:57,080 --> 00:08:00,360 Speaker 2: said it created opportunities for another kind of company to 144 00:08:00,400 --> 00:08:05,320 Speaker 2: gain the system. Staffing firms. These firms essentially work as 145 00:08:05,360 --> 00:08:09,120 Speaker 2: middleman recruiting foreign workers and connecting them with contract jobs 146 00:08:09,120 --> 00:08:12,280 Speaker 2: at US based companies, and part of their pitch is 147 00:08:12,320 --> 00:08:14,320 Speaker 2: that they can get you in each one B visa 148 00:08:14,760 --> 00:08:18,000 Speaker 2: because of how a depth they've become at gaming the system. 149 00:08:18,200 --> 00:08:22,200 Speaker 4: The new opportunity worked like this, if I have a 150 00:08:22,240 --> 00:08:25,360 Speaker 4: person who I want to help get a visa. I 151 00:08:25,360 --> 00:08:28,880 Speaker 4: can simply just create a bunch of other companies or 152 00:08:28,920 --> 00:08:32,440 Speaker 4: just conspire with other companies that already exist to put 153 00:08:32,480 --> 00:08:37,760 Speaker 4: that person's name in multiple times. And so it becomes 154 00:08:38,000 --> 00:08:41,520 Speaker 4: a system where essentially, if someone wants a visa and 155 00:08:41,559 --> 00:08:43,440 Speaker 4: they can kind of work with these a group of 156 00:08:43,480 --> 00:08:47,600 Speaker 4: these very small companies, they can almost be guaranteed to 157 00:08:47,640 --> 00:08:51,360 Speaker 4: get one. And so the chances really skyrocket for people 158 00:08:51,360 --> 00:08:53,960 Speaker 4: who are willing to work with these kind of companies 159 00:08:54,000 --> 00:08:56,959 Speaker 4: that are willing to cheat and kind of budge ahead 160 00:08:56,960 --> 00:08:59,560 Speaker 4: in the lottery. And so anybody who's just doing it 161 00:08:59,600 --> 00:09:01,600 Speaker 4: the old fact way of like I actually have a 162 00:09:01,640 --> 00:09:04,400 Speaker 4: real job and I want this work or to have 163 00:09:04,440 --> 00:09:06,560 Speaker 4: an H and B, they get pushed to the end 164 00:09:06,559 --> 00:09:09,559 Speaker 4: of the line because they're not putting the person's name 165 00:09:09,600 --> 00:09:10,280 Speaker 4: in more than once. 166 00:09:10,880 --> 00:09:13,360 Speaker 2: Zach says. Those staffing firms have been able to fly 167 00:09:13,559 --> 00:09:16,480 Speaker 2: under the radar because many of them are very small. 168 00:09:16,960 --> 00:09:20,600 Speaker 4: If it was Apple or Tesla that did this, I 169 00:09:20,640 --> 00:09:24,120 Speaker 4: think with thousands of employees, I think the government would 170 00:09:24,120 --> 00:09:27,160 Speaker 4: have caught on pretty quickly and probably tried to do 171 00:09:27,280 --> 00:09:30,520 Speaker 4: something to them. But these are all like companies you've 172 00:09:30,520 --> 00:09:34,320 Speaker 4: never heard of. Often that don't really have much physical existence, 173 00:09:34,720 --> 00:09:37,600 Speaker 4: like maybe they have an office, maybe they don't. Maybe 174 00:09:37,600 --> 00:09:41,079 Speaker 4: they're just like an LLC that somebody created without much 175 00:09:41,120 --> 00:09:42,000 Speaker 4: real existence at all. 176 00:09:43,679 --> 00:09:46,400 Speaker 2: For a long time, it was impossible for reporters like 177 00:09:46,520 --> 00:09:48,560 Speaker 2: Eric and Zach to figure out the extent of the 178 00:09:48,600 --> 00:09:51,839 Speaker 2: problem or which companies were the worst offenders. 179 00:09:52,200 --> 00:09:56,960 Speaker 1: That data was never public and we had to file 180 00:09:57,080 --> 00:09:59,800 Speaker 1: a FOY lawsuit. So for the first time we're able 181 00:09:59,880 --> 00:10:03,560 Speaker 1: to say exactly how many companies are gaining the system, 182 00:10:04,800 --> 00:10:08,040 Speaker 1: and we were very surprised because we've found thousands and thousands 183 00:10:08,040 --> 00:10:12,560 Speaker 1: of them, and it became immediately clear that these staffing 184 00:10:12,600 --> 00:10:17,720 Speaker 1: companies have sometimes ninety nine percent one hundred percent of 185 00:10:17,800 --> 00:10:22,320 Speaker 1: their entries. Are these multiple entries as compared to a 186 00:10:22,720 --> 00:10:28,720 Speaker 1: regular company such as Apple, Google would usually have less 187 00:10:28,720 --> 00:10:29,760 Speaker 1: than five percent. 188 00:10:30,640 --> 00:10:34,240 Speaker 2: There are legitimate reasons for someone to have multiple applications 189 00:10:34,360 --> 00:10:37,559 Speaker 2: entered on their behalf, say if they have competing offers 190 00:10:37,600 --> 00:10:41,959 Speaker 2: from several companies to sponsor them, but those situations are uncommon. 191 00:10:42,520 --> 00:10:45,160 Speaker 2: So when Eric found these instances in which one hundred 192 00:10:45,240 --> 00:10:48,480 Speaker 2: percent of the company's applicants were being entered multiple times, 193 00:10:49,120 --> 00:10:50,200 Speaker 2: the stat was striking. 194 00:10:50,800 --> 00:10:53,880 Speaker 1: I thought there was a problem, but it was so 195 00:10:54,040 --> 00:10:57,679 Speaker 1: much worse than I imagined. And it turned out almost 196 00:10:57,720 --> 00:11:02,960 Speaker 1: half of all the vs that were approved last year 197 00:11:03,400 --> 00:11:09,160 Speaker 1: when you're either outsourcing or staffing companies, meaning for most 198 00:11:09,160 --> 00:11:13,000 Speaker 1: of the folks who study and live and work in 199 00:11:13,000 --> 00:11:16,920 Speaker 1: the US who have a job offer from one of 200 00:11:16,920 --> 00:11:21,880 Speaker 1: the top companies like Google and Tesla, they're losing out. 201 00:11:24,200 --> 00:11:27,920 Speaker 2: So Eric and Zach identified the biggest H one B cheaters. 202 00:11:28,400 --> 00:11:32,080 Speaker 2: The question was would anything be done to stop them? 203 00:11:32,320 --> 00:11:44,280 Speaker 2: That's after the break. A Bloomberg investigation found that about 204 00:11:44,320 --> 00:11:47,160 Speaker 2: half of the coveted H one B skilled worker visas 205 00:11:47,200 --> 00:11:50,040 Speaker 2: between twenty twenty and twenty twenty three were going to 206 00:11:50,120 --> 00:11:53,839 Speaker 2: outsourcing companies and staffing firms, and then an estimated one 207 00:11:53,920 --> 00:11:57,800 Speaker 2: in six involved the slippery tactic of submitting multiple lottery 208 00:11:57,920 --> 00:12:01,040 Speaker 2: entries for the same person. What's the impact of this 209 00:12:01,160 --> 00:12:04,720 Speaker 2: type of gaming of the system? Who exactly is this hurting? 210 00:12:05,240 --> 00:12:08,640 Speaker 4: I think the big picture is it's hurting the American economy. 211 00:12:09,160 --> 00:12:11,920 Speaker 2: According to a twenty twenty three Wharton School study, for 212 00:12:12,000 --> 00:12:15,280 Speaker 2: every ten H one B visas the top US multinational 213 00:12:15,280 --> 00:12:19,160 Speaker 2: companies lose out on, nine jobs are moved abroad. The 214 00:12:19,200 --> 00:12:22,680 Speaker 2: Federal Reserve Bank of Richmond estimated that reducing the number 215 00:12:22,720 --> 00:12:25,520 Speaker 2: of high skilled immigrant workers in the US by ten 216 00:12:25,600 --> 00:12:29,880 Speaker 2: percent would shrink the economy by about eighty six billion dollars. 217 00:12:30,200 --> 00:12:33,559 Speaker 2: So there's the economic toll, there's the toll on H 218 00:12:33,640 --> 00:12:36,640 Speaker 2: one B hopefuls who are competing in a lottery that's rigged, 219 00:12:37,280 --> 00:12:39,600 Speaker 2: and then there's the toll on the H one B 220 00:12:39,760 --> 00:12:43,560 Speaker 2: recipients whose futures are now tied to companies that skirt 221 00:12:43,559 --> 00:12:44,400 Speaker 2: the rules. 222 00:12:44,800 --> 00:12:49,720 Speaker 1: So I've interviewed a number of workers and formal workers 223 00:12:49,760 --> 00:12:53,120 Speaker 1: at these staffing companies, and what they told me was 224 00:12:53,320 --> 00:12:57,520 Speaker 1: they usually knew full wow that staffing companies pay them 225 00:12:57,880 --> 00:13:02,959 Speaker 1: very little, and there was no job security, and they 226 00:13:03,000 --> 00:13:07,040 Speaker 1: often had to sign contracts that forbid them from leaving 227 00:13:07,040 --> 00:13:12,360 Speaker 1: the company for years, and most equageously, they were often 228 00:13:12,400 --> 00:13:15,720 Speaker 1: asked to pay the lawyer fees and visa fees and 229 00:13:15,840 --> 00:13:18,439 Speaker 1: registration fees, which is not allowed. 230 00:13:19,160 --> 00:13:21,920 Speaker 2: Eric and Zach wanted to know what happened to the 231 00:13:21,920 --> 00:13:24,280 Speaker 2: companies that they found were bending the rules. 232 00:13:24,600 --> 00:13:27,960 Speaker 4: Now, some of the visa recipients have had their visas 233 00:13:28,000 --> 00:13:30,760 Speaker 4: taken away and have to be sent home or whatever. 234 00:13:31,240 --> 00:13:33,560 Speaker 4: But the companies themselves which offer were kind of the 235 00:13:33,600 --> 00:13:37,840 Speaker 4: masterminds of this don't really have any consequences that we 236 00:13:37,920 --> 00:13:41,200 Speaker 4: can see. And so what the government says in response 237 00:13:41,280 --> 00:13:45,040 Speaker 4: is essentially they don't have the authority to bar anyone 238 00:13:45,160 --> 00:13:49,160 Speaker 4: from the lottery, and so as long as people keep 239 00:13:49,200 --> 00:13:54,360 Speaker 4: submitting applications and there's nothing on the application that looks suspect, 240 00:13:54,400 --> 00:13:58,079 Speaker 4: they have to keep handing out visas to these companies. 241 00:13:58,520 --> 00:14:01,240 Speaker 2: Have you gotten comment from any of these companies, what 242 00:14:01,280 --> 00:14:02,719 Speaker 2: do they say about their practices. 243 00:14:03,080 --> 00:14:06,920 Speaker 4: We spoke to a representative of the staffing industry who 244 00:14:07,000 --> 00:14:10,320 Speaker 4: said that the laws are actually pretty vague and that 245 00:14:10,800 --> 00:14:14,600 Speaker 4: in his view, it wasn't really clear, especially during the 246 00:14:14,600 --> 00:14:17,360 Speaker 4: first couple of years of this new program, that it 247 00:14:17,440 --> 00:14:21,120 Speaker 4: was actually forbidden to collude with other companies to put 248 00:14:21,120 --> 00:14:25,160 Speaker 4: people's names in multiple times. And even after it kind 249 00:14:25,160 --> 00:14:28,200 Speaker 4: of became more clear that that wasn't allowed under the law, 250 00:14:28,720 --> 00:14:31,440 Speaker 4: the government may have not followed the proper procedures to 251 00:14:31,520 --> 00:14:33,960 Speaker 4: kind of make sure everyone is aware of that. And 252 00:14:34,040 --> 00:14:38,280 Speaker 4: so from the staffing industry's perspective, it wasn't so much 253 00:14:38,760 --> 00:14:42,800 Speaker 4: cheating as more just like they saw an opportunity in 254 00:14:42,840 --> 00:14:44,720 Speaker 4: the law and they took. 255 00:14:44,560 --> 00:14:49,800 Speaker 2: It that opportunity. No longer exists. Last year, the US 256 00:14:49,880 --> 00:14:53,160 Speaker 2: government made a significant change to the system that shifted 257 00:14:53,160 --> 00:14:54,440 Speaker 2: the dynamics of the lottery. 258 00:14:55,920 --> 00:15:00,440 Speaker 1: So last year the government introduced new rules so that 259 00:15:00,920 --> 00:15:05,400 Speaker 1: each candidate has an equal chance in the lottery. So 260 00:15:05,440 --> 00:15:10,560 Speaker 1: instead of selecting on the number of registrations submitted by employers, 261 00:15:11,200 --> 00:15:15,480 Speaker 1: each candidate, regardless of how many registrations they have, has 262 00:15:15,520 --> 00:15:21,200 Speaker 1: an equal chance. So that drastically removed the incentive to cheat. 263 00:15:21,880 --> 00:15:25,560 Speaker 1: That removed the incentive for staffing companies to collude and 264 00:15:25,640 --> 00:15:27,720 Speaker 1: submit multiple registrations. 265 00:15:27,520 --> 00:15:30,720 Speaker 2: And Eric says that change has had an immediate effect. 266 00:15:31,200 --> 00:15:34,880 Speaker 1: This year, according to government data, the number of multiple 267 00:15:34,880 --> 00:15:36,840 Speaker 1: registrations decline ninety percent. 268 00:15:37,560 --> 00:15:41,200 Speaker 2: Specific loopholes like these have been opening and closing for decades. 269 00:15:41,600 --> 00:15:44,240 Speaker 2: But a big takeaway of Erican Zac's reporting is that 270 00:15:44,280 --> 00:15:46,880 Speaker 2: the H one B program has fallen far short of 271 00:15:46,920 --> 00:15:47,720 Speaker 2: its initial goal. 272 00:15:48,120 --> 00:15:53,520 Speaker 4: Immigration is a very difficult issue for Washington. The last 273 00:15:53,520 --> 00:15:56,400 Speaker 4: time there was a real effort to reform the immigration 274 00:15:56,520 --> 00:15:59,160 Speaker 4: system was more than a decade ago, and it kind 275 00:15:59,160 --> 00:16:03,520 Speaker 4: of famously failed and collapsed. And up until this point, 276 00:16:04,520 --> 00:16:07,400 Speaker 4: even when there's been times of a lot of consensus 277 00:16:07,440 --> 00:16:11,240 Speaker 4: about fixing H one B, it's always been thought of 278 00:16:11,280 --> 00:16:14,200 Speaker 4: as something we have to resolve as part of this 279 00:16:14,280 --> 00:16:16,960 Speaker 4: bigger immigration deal, which means that in practice it will 280 00:16:16,960 --> 00:16:17,520 Speaker 4: never get done. 281 00:16:22,680 --> 00:16:25,760 Speaker 2: This is the Big Take from Bloomberg News. I'm Sarah Holder. 282 00:16:26,520 --> 00:16:29,440 Speaker 2: This episode was produced by David Fox. It was edited 283 00:16:29,440 --> 00:16:32,400 Speaker 2: by Aaron Edwards and Jason Grotto. It was fact checked 284 00:16:32,440 --> 00:16:36,440 Speaker 2: by Adrianna Tapia and mixed by Blake Maples. Our senior 285 00:16:36,480 --> 00:16:39,440 Speaker 2: producers are Kim Gettlelson and Naomi Shaven, and our senior 286 00:16:39,520 --> 00:16:43,760 Speaker 2: editor is Elizabeth Ponso. Nicole bumsterbor is Our executive producer. 287 00:16:44,080 --> 00:16:47,600 Speaker 2: Sage Bauman is Bloomberg's head of podcasts. Thanks so much 288 00:16:47,640 --> 00:16:50,520 Speaker 2: for listening. Please follow and review The Big Take wherever 289 00:16:50,560 --> 00:16:53,520 Speaker 2: you get your podcasts. It helps new listeners find the show. 290 00:16:54,360 --> 00:17:00,760 Speaker 2: We'll be back tomorrow