1 00:00:00,080 --> 00:00:03,200 Speaker 1: Welcome to Head of Money. I'm Joel and I am Matt, 2 00:00:03,200 --> 00:00:07,480 Speaker 1: and today we're talking degree downsides, credit bureau blunders, and 3 00:00:07,520 --> 00:00:29,440 Speaker 1: fluctuating fast food. You know what, buddy, this is our 4 00:00:29,560 --> 00:00:30,240 Speaker 1: Friday flight. 5 00:00:30,320 --> 00:00:33,960 Speaker 2: We're gonna share a sampling of the top personal finance 6 00:00:33,960 --> 00:00:36,600 Speaker 2: stories that we think you need to be paying attention from, 7 00:00:37,680 --> 00:00:39,440 Speaker 2: not just this past week, the past two weeks. 8 00:00:39,479 --> 00:00:40,760 Speaker 1: We were able to take a little bit of time 9 00:00:40,800 --> 00:00:43,120 Speaker 1: off there at the end of last. 10 00:00:43,040 --> 00:00:45,440 Speaker 2: Week, which means we weren't able to get around to 11 00:00:45,560 --> 00:00:49,960 Speaker 2: sharing some of the newsletter referral shout outs. Yeah, we 12 00:00:50,040 --> 00:00:53,480 Speaker 2: recently lowered some of some of the bars, the threshold 13 00:00:54,040 --> 00:00:56,280 Speaker 2: that was required in order to receive some of the 14 00:00:56,320 --> 00:00:59,360 Speaker 2: different rewards that are available. 15 00:00:58,880 --> 00:01:02,160 Speaker 1: To much literally cash money sent to you Vivenmo for real, 16 00:01:02,280 --> 00:01:04,759 Speaker 1: no scam. It's a beer on us, a beer on us. 17 00:01:04,959 --> 00:01:07,560 Speaker 1: And then the covetedt had the money. Socks those are 18 00:01:07,800 --> 00:01:10,319 Speaker 1: that's what people really want. It only takes twenty referrals. 19 00:01:10,440 --> 00:01:13,200 Speaker 1: Did we have it at like thirty thirty five? It 20 00:01:14,160 --> 00:01:16,200 Speaker 1: was too high of a bar to achieve. 21 00:01:16,360 --> 00:01:17,959 Speaker 2: And you know what, We've got a whole box of 22 00:01:18,000 --> 00:01:20,760 Speaker 2: these socks sitting there wrapped in They're soft, fancy, little 23 00:01:20,959 --> 00:01:22,600 Speaker 2: plastic and we want to get some of those out 24 00:01:22,600 --> 00:01:25,760 Speaker 2: to folks we haven't even gotten well, I think there's 25 00:01:25,800 --> 00:01:27,520 Speaker 2: a couple folks who have gotten pretty close to this. 26 00:01:27,600 --> 00:01:30,160 Speaker 2: But a virtual beer hang I'm looking forward to the 27 00:01:30,160 --> 00:01:32,120 Speaker 2: first one. We do pretty sure Brendan is gonna be 28 00:01:32,160 --> 00:01:32,880 Speaker 2: the first time to get there. 29 00:01:33,160 --> 00:01:35,399 Speaker 1: He's so close. Someone's gonna get there at some point. Yeah, Well, 30 00:01:35,800 --> 00:01:36,880 Speaker 1: to hang out with you for a little. 31 00:01:36,720 --> 00:01:38,800 Speaker 2: Bit and have a beer exactly a little zoom beer, 32 00:01:38,920 --> 00:01:40,280 Speaker 2: you know, like sort of like it was like back 33 00:01:40,280 --> 00:01:41,080 Speaker 2: in the pandemic days. 34 00:01:41,080 --> 00:01:43,200 Speaker 1: It was like a virtual happy hour. Unless you actually 35 00:01:43,200 --> 00:01:44,280 Speaker 1: want to fly in here, we'll do in person. 36 00:01:44,280 --> 00:01:46,720 Speaker 2: I guess, hey, if you do that, beers are definitely 37 00:01:46,800 --> 00:01:48,960 Speaker 2: on us. But we want to make sure that we 38 00:01:49,160 --> 00:01:52,000 Speaker 2: share a few folks who shared the newsletter with their friends, 39 00:01:52,360 --> 00:01:56,160 Speaker 2: and a big thanks to Emmy's mom, Austin M. V. 40 00:01:56,520 --> 00:02:00,280 Speaker 1: Mooney, Kyle M. Eighty eight and Hassan. Yeah, we all 41 00:02:00,280 --> 00:02:03,120 Speaker 1: shared it with at least two folks, which means you're committed. 42 00:02:03,200 --> 00:02:05,480 Speaker 1: And by the way, how to Money Yeah host letter 43 00:02:05,520 --> 00:02:08,240 Speaker 1: podcast and we are so close to crossing ten thousand 44 00:02:08,320 --> 00:02:10,400 Speaker 1: subscribers to the How Money newsletter, So if you've been 45 00:02:10,440 --> 00:02:12,640 Speaker 1: reading it, you've been getting value. Share it with somebody, 46 00:02:12,720 --> 00:02:14,280 Speaker 1: you might get a shout out, you might even get 47 00:02:14,720 --> 00:02:16,519 Speaker 1: free money. But also you'll be helping us, you know, 48 00:02:16,600 --> 00:02:20,200 Speaker 1: cross that coveted five figure mark of people reading the newsletter. 49 00:02:20,240 --> 00:02:22,960 Speaker 1: So it's our goal to send out helpful information every Tuesday. 50 00:02:22,960 --> 00:02:24,400 Speaker 1: You can sign up at how to money dot com 51 00:02:24,400 --> 00:02:26,480 Speaker 1: slash newsletter. But Matt, let's move on. Let's get to 52 00:02:26,520 --> 00:02:28,720 Speaker 1: the Friday flight. Let's get to the stories, the sampling 53 00:02:28,720 --> 00:02:30,480 Speaker 1: of stories we found interesting this week in the personal 54 00:02:30,560 --> 00:02:32,680 Speaker 1: finance space. And like you said, we were out of 55 00:02:32,680 --> 00:02:34,360 Speaker 1: town last week. We didn't have a chance to comment 56 00:02:34,639 --> 00:02:36,560 Speaker 1: on what was kind of a big story in the 57 00:02:36,800 --> 00:02:39,920 Speaker 1: financial space, like in like the stodgy financial space, the 58 00:02:39,960 --> 00:02:43,359 Speaker 1: banking space, the Capital One, the big bank space, takeover 59 00:02:43,520 --> 00:02:47,919 Speaker 1: of Discover, that potential merger. Right, And you might think, actually, 60 00:02:47,960 --> 00:02:50,919 Speaker 1: when we talk about our favorite online banks, Discover and 61 00:02:51,200 --> 00:02:53,040 Speaker 1: Capital One both come up. Yeah, we like them both. 62 00:02:53,120 --> 00:02:55,080 Speaker 1: They're both too, they're two of the best online banks 63 00:02:55,080 --> 00:02:57,080 Speaker 1: you can choose. And so two of our favorite online 64 00:02:57,120 --> 00:02:59,239 Speaker 1: banks coming together. This is a love story, a match 65 00:02:59,240 --> 00:03:01,880 Speaker 1: made in heaven. Right, We're we're super enthusiastic about this 66 00:03:03,080 --> 00:03:05,920 Speaker 1: maybe maybe not though, So there's a few things to 67 00:03:05,960 --> 00:03:09,000 Speaker 1: really talk about here. One is going to reduce competition 68 00:03:09,080 --> 00:03:11,720 Speaker 1: in the banking sector, right Economics one oh one tells 69 00:03:11,800 --> 00:03:15,480 Speaker 1: us that reduce competition isn't great for consumers. And the 70 00:03:15,800 --> 00:03:19,320 Speaker 1: bigger banks seem to come with smaller brains, kind of 71 00:03:19,320 --> 00:03:22,120 Speaker 1: like dinosaurs, Matt, you know, the biggest dinosaurs, the bigger. 72 00:03:23,320 --> 00:03:24,679 Speaker 1: It's true. We talked about like the big three or 73 00:03:24,680 --> 00:03:28,160 Speaker 1: four banks that they have a massive percentage of deposits 74 00:03:28,160 --> 00:03:31,760 Speaker 1: in this country, and they are tree consumers the worst. 75 00:03:31,760 --> 00:03:35,119 Speaker 1: It's the smaller, medium sized banks that do a lot 76 00:03:35,160 --> 00:03:38,760 Speaker 1: better by their customers. And so, yeah, I don't love 77 00:03:39,160 --> 00:03:41,920 Speaker 1: reducing competition and taking two great banks and maybe making 78 00:03:41,920 --> 00:03:45,560 Speaker 1: it into one mediocre bank. So yeah, at least on 79 00:03:45,600 --> 00:03:48,240 Speaker 1: the consumer banking side, this probably isn't a great thing 80 00:03:48,240 --> 00:03:49,840 Speaker 1: for the American public. But there's even more of the 81 00:03:49,880 --> 00:03:50,800 Speaker 1: deal than that, I will. 82 00:03:50,640 --> 00:03:53,080 Speaker 2: Say, though, Capital One they did pinky promise to maintain 83 00:03:53,320 --> 00:03:55,880 Speaker 2: the Discover credit cards, so at least from a credit 84 00:03:55,920 --> 00:03:58,360 Speaker 2: if you're a huge fan of your what is it 85 00:03:58,400 --> 00:04:01,440 Speaker 2: the discover it card or literally I think Discover was 86 00:04:01,480 --> 00:04:03,480 Speaker 2: my first credit card when I was a teenager. This 87 00:04:03,520 --> 00:04:05,400 Speaker 2: is back when you could get your own credit card 88 00:04:05,400 --> 00:04:07,520 Speaker 2: as a don't even have to be eighteen years old. 89 00:04:07,800 --> 00:04:10,400 Speaker 1: Well, Discovery is actually the only We've talked about this before. 90 00:04:10,440 --> 00:04:13,680 Speaker 1: They're the only bank that has a cash back debit card. 91 00:04:13,760 --> 00:04:15,920 Speaker 1: Usually you don't get paid anything spending with your debit card, 92 00:04:15,960 --> 00:04:17,920 Speaker 1: but True Discovers the only one that makes that possible. 93 00:04:17,960 --> 00:04:20,440 Speaker 2: But then the other side of the coin is that 94 00:04:20,480 --> 00:04:23,960 Speaker 2: the merger could actually create more competition on the credit 95 00:04:23,960 --> 00:04:28,200 Speaker 2: card payments front, posing a potential threat to the duopoly 96 00:04:28,320 --> 00:04:29,600 Speaker 2: of Visa and Master. 97 00:04:29,680 --> 00:04:31,359 Speaker 1: Can I want to explain maybe what a duopoly is. 98 00:04:31,520 --> 00:04:35,880 Speaker 1: Everyone knows what monopoly. Duopoly to competing against each other, 99 00:04:35,920 --> 00:04:37,960 Speaker 1: Matt doesn't have the same impact of driving down prices. 100 00:04:38,000 --> 00:04:40,640 Speaker 2: Well, just the fact that they can go into cahoots 101 00:04:40,680 --> 00:04:43,640 Speaker 2: and basically agree without agreeing. Yeah, it's a week week, 102 00:04:43,680 --> 00:04:46,440 Speaker 2: not situation. So what it is they're going to charge folks? 103 00:04:46,480 --> 00:04:48,480 Speaker 2: And these banks make a ton of money on the 104 00:04:48,520 --> 00:04:53,880 Speaker 2: transaction fees that they charge different small businesses. 105 00:04:54,120 --> 00:04:57,400 Speaker 1: And that is large. It contributes to a greater expense. 106 00:04:57,120 --> 00:05:00,240 Speaker 2: For everyone, especially yeah, especially for We heard a lot 107 00:05:00,240 --> 00:05:02,080 Speaker 2: about this when it came to restaurants, which is why 108 00:05:02,080 --> 00:05:05,520 Speaker 2: so many small businesses, especially restaurants, are charging much less 109 00:05:05,839 --> 00:05:09,160 Speaker 2: if you skip credit cards altogether, and this could potentially 110 00:05:09,680 --> 00:05:12,520 Speaker 2: result in lower swipe fees faced by businesses, which would 111 00:05:12,640 --> 00:05:16,280 Speaker 2: end up helping us consumers. So it's tough to know 112 00:05:16,720 --> 00:05:18,680 Speaker 2: which way the cookie is going to crumble. It makes 113 00:05:18,720 --> 00:05:22,039 Speaker 2: the domino effect of this deal harder to decipher and 114 00:05:22,080 --> 00:05:24,240 Speaker 2: to sort of look into the tea leaves and figure 115 00:05:24,279 --> 00:05:25,520 Speaker 2: out what's actually going to happen. 116 00:05:25,640 --> 00:05:26,120 Speaker 1: We don't know. 117 00:05:26,760 --> 00:05:28,880 Speaker 2: But plus, there's a solid chance that this deal doesn't 118 00:05:28,880 --> 00:05:32,960 Speaker 2: even actually come to fruition because of the political. 119 00:05:32,480 --> 00:05:34,600 Speaker 1: Climate right now. It's not all that open to big 120 00:05:34,680 --> 00:05:37,719 Speaker 1: deals like this happening, to these deals taking place in 121 00:05:37,720 --> 00:05:38,240 Speaker 1: the first place. 122 00:05:38,320 --> 00:05:40,720 Speaker 2: Yeah, so we wanted to cover it because they're two 123 00:05:40,880 --> 00:05:43,880 Speaker 2: huge names. They're companies that we both do business with, 124 00:05:44,160 --> 00:05:46,719 Speaker 2: companies that we even recommend. But we'll see if this 125 00:05:46,760 --> 00:05:47,640 Speaker 2: actually comes to fruition. 126 00:05:47,720 --> 00:05:50,039 Speaker 1: Yeah, it is interesting that the political climate might not 127 00:05:50,080 --> 00:05:52,320 Speaker 1: favor this deal going through it. And it's also kind 128 00:05:52,320 --> 00:05:54,560 Speaker 1: of fascinating that in one sense they might be less 129 00:05:54,560 --> 00:05:56,960 Speaker 1: competition in the retail banking space, but in the other sense, 130 00:05:56,960 --> 00:06:00,400 Speaker 1: in the payment processing space, there could be more petition. 131 00:06:00,480 --> 00:06:02,400 Speaker 1: So is it a win for zoomers, is it not. 132 00:06:02,800 --> 00:06:05,480 Speaker 1: That's like the regulars are going to weigh in on that, 133 00:06:05,800 --> 00:06:07,240 Speaker 1: But I think it could be a bit of both, 134 00:06:07,240 --> 00:06:09,800 Speaker 1: which makes us a tough one to figure out exactly exactly. 135 00:06:09,880 --> 00:06:12,520 Speaker 1: All right, man, let's talk about careers and college for 136 00:06:12,560 --> 00:06:14,960 Speaker 1: a second. A new study of more than ten million people, 137 00:06:14,960 --> 00:06:17,520 Speaker 1: so it's really throwing not like a thousand people it 138 00:06:17,640 --> 00:06:20,039 Speaker 1: questioned on just a quick phone call. It found that 139 00:06:20,120 --> 00:06:23,000 Speaker 1: roughly fifty percent of college graduates end up in a 140 00:06:23,080 --> 00:06:25,600 Speaker 1: job that didn't require the degree that they worked really 141 00:06:25,640 --> 00:06:28,279 Speaker 1: hard to get. And I feel like this reveals a lot. 142 00:06:28,720 --> 00:06:30,560 Speaker 1: You know, one of the most important things that reveals 143 00:06:30,680 --> 00:06:33,279 Speaker 1: is just how important your first job is. Right, it 144 00:06:33,279 --> 00:06:35,480 Speaker 1: doesn't have to pay a bundle, but if it's outside 145 00:06:35,480 --> 00:06:37,880 Speaker 1: of your intended career path, it could have long lasting 146 00:06:37,880 --> 00:06:39,760 Speaker 1: effects on where you end up. This piece in the 147 00:06:39,800 --> 00:06:42,800 Speaker 1: Wall Street Journal talking about this new study revealed a 148 00:06:42,839 --> 00:06:44,880 Speaker 1: lot of individuals who were like, Oh, I took the 149 00:06:44,880 --> 00:06:46,800 Speaker 1: first job because I couldn't find something in my career, 150 00:06:47,000 --> 00:06:48,640 Speaker 1: and then it just I just kind of ended up 151 00:06:48,640 --> 00:06:51,000 Speaker 1: staying in that place, or it took me off of 152 00:06:51,000 --> 00:06:53,080 Speaker 1: that career path I was hoping to get on. This 153 00:06:53,560 --> 00:06:56,200 Speaker 1: reduces pay and job satisfaction for a whole lot of 154 00:06:56,200 --> 00:06:59,160 Speaker 1: folks too. And I would say this, like, the biggest 155 00:06:59,160 --> 00:07:01,440 Speaker 1: finding from the study that I found most asking is 156 00:07:01,480 --> 00:07:03,359 Speaker 1: it to help ensure that you end up working in 157 00:07:03,400 --> 00:07:05,880 Speaker 1: your chosen field. The biggest way to do that is 158 00:07:05,920 --> 00:07:09,440 Speaker 1: to get an internship, even if that internship I love internships. Yeah, 159 00:07:09,720 --> 00:07:12,440 Speaker 1: Like this is like we say great things about internships 160 00:07:12,480 --> 00:07:14,880 Speaker 1: all the time, even and I know some people really 161 00:07:15,120 --> 00:07:18,560 Speaker 1: hate the idea of an unpaid internship. And I would 162 00:07:18,560 --> 00:07:20,960 Speaker 1: say go for the unpaid internship even too, because that 163 00:07:21,040 --> 00:07:23,360 Speaker 1: is actually what's going to lead to the connections, the 164 00:07:23,480 --> 00:07:26,000 Speaker 1: job history. It's essentially as the pathway the connection and 165 00:07:26,040 --> 00:07:28,200 Speaker 1: the experience you may need to get in the front door. Matt. 166 00:07:28,200 --> 00:07:30,880 Speaker 1: I had an internship in a completely unpaid internship for 167 00:07:30,920 --> 00:07:33,040 Speaker 1: months when I was a senior in college. But it 168 00:07:33,120 --> 00:07:35,760 Speaker 1: led to me being in getting the kind of job 169 00:07:35,800 --> 00:07:37,680 Speaker 1: that I wanted to get, and so I had that 170 00:07:37,760 --> 00:07:39,920 Speaker 1: first right job. Even if it's starting on the bottom 171 00:07:39,960 --> 00:07:42,480 Speaker 1: of the tone pole, it's crucial to future decades of 172 00:07:42,520 --> 00:07:44,760 Speaker 1: success for so many people. I think these are kind 173 00:07:44,800 --> 00:07:47,240 Speaker 1: of sobering statistics about how a lot of people getting 174 00:07:47,240 --> 00:07:49,600 Speaker 1: a college degree don't end up using that college degree, 175 00:07:49,680 --> 00:07:50,880 Speaker 1: but I think there are ways not to be on 176 00:07:50,920 --> 00:07:52,040 Speaker 1: the downside of the statistic. 177 00:07:52,160 --> 00:07:54,360 Speaker 2: Sure, sure, yeah, I guess The one thing I didn't 178 00:07:54,360 --> 00:07:56,040 Speaker 2: like about the article is that they seem to focus 179 00:07:56,080 --> 00:07:58,960 Speaker 2: on a few specific anecdotes about folks who got stuck 180 00:07:59,040 --> 00:08:00,640 Speaker 2: in a job, like the first job that they took 181 00:08:00,640 --> 00:08:03,320 Speaker 2: out of college, basically because I think that there is 182 00:08:03,440 --> 00:08:06,320 Speaker 2: totally a way to get out of a job that 183 00:08:06,480 --> 00:08:08,880 Speaker 2: you find yourself in and you're just kind of like, eh, 184 00:08:09,080 --> 00:08:11,400 Speaker 2: not really loving this or actually this, I am not 185 00:08:11,520 --> 00:08:12,320 Speaker 2: using my degree. 186 00:08:12,560 --> 00:08:13,840 Speaker 1: You're less stuck than you think you are. 187 00:08:14,000 --> 00:08:16,280 Speaker 2: You are like, we have more control as individuals than 188 00:08:16,320 --> 00:08:18,640 Speaker 2: I think folks give themselves credit for. 189 00:08:18,720 --> 00:08:19,840 Speaker 1: And it's going to take a. 190 00:08:19,840 --> 00:08:21,640 Speaker 2: Little bit of like creativity, it's going to take a 191 00:08:21,640 --> 00:08:24,640 Speaker 2: little bit of initiative. It's going to take looking at 192 00:08:24,680 --> 00:08:27,480 Speaker 2: problems differently. That's the kind of person that you're going 193 00:08:27,560 --> 00:08:29,760 Speaker 2: to hire, even though they don't have the experience, even 194 00:08:29,800 --> 00:08:31,640 Speaker 2: though their first job was, oh, what's this thing that 195 00:08:31,680 --> 00:08:35,320 Speaker 2: you were in Walgreens pharmacy? No, No, I was actually 196 00:08:35,360 --> 00:08:36,440 Speaker 2: just like working the register. 197 00:08:36,600 --> 00:08:36,760 Speaker 1: Yeah. 198 00:08:36,800 --> 00:08:38,800 Speaker 2: I think that's totally fine, but it might just take 199 00:08:38,800 --> 00:08:42,080 Speaker 2: a little bit of legwork. You can't just you. You 200 00:08:42,120 --> 00:08:44,840 Speaker 2: can't just like follow everyone else. And like speaking to 201 00:08:44,920 --> 00:08:46,760 Speaker 2: the fact of whether or not you're going to get 202 00:08:46,880 --> 00:08:48,719 Speaker 2: land a great job straight out of college, I think 203 00:08:48,720 --> 00:08:51,560 Speaker 2: that's another huge takeaway other than like the first job 204 00:08:51,640 --> 00:08:54,800 Speaker 2: is thinking through that and it's just identifying and knowing 205 00:08:54,880 --> 00:08:57,280 Speaker 2: that just because you go to college and get a degree, 206 00:08:57,400 --> 00:09:00,680 Speaker 2: get good grades, more knowledge, that doesn't necessarily mean you're 207 00:09:00,679 --> 00:09:04,840 Speaker 2: going to land that amazingly paying job in the industry 208 00:09:04,960 --> 00:09:07,720 Speaker 2: that you want. Like it's just the standard default option. 209 00:09:07,800 --> 00:09:09,720 Speaker 2: It's not like this conveyor belt. It's not like a 210 00:09:10,320 --> 00:09:12,839 Speaker 2: like a moving sidewalk out of airport and it's just 211 00:09:12,880 --> 00:09:14,760 Speaker 2: gonna boo spit you out where you want to be 212 00:09:15,040 --> 00:09:17,680 Speaker 2: perfectly and all magically. Like, there are different things that 213 00:09:17,760 --> 00:09:19,400 Speaker 2: you have to do to stand out, And like you said, 214 00:09:19,559 --> 00:09:22,000 Speaker 2: I think internships are a huge way to do that, 215 00:09:22,120 --> 00:09:24,280 Speaker 2: and it's great for multiple reasons because it helps you 216 00:09:24,360 --> 00:09:26,720 Speaker 2: to get a taste, like a sampling of the work 217 00:09:26,720 --> 00:09:28,920 Speaker 2: that you might be doing. So for you as an individual, 218 00:09:29,520 --> 00:09:31,800 Speaker 2: you're like, oh, well, maybe I didn't like that work. Well, 219 00:09:31,840 --> 00:09:34,080 Speaker 2: what better way to get a feel for that than 220 00:09:34,120 --> 00:09:38,280 Speaker 2: actually having gotten multiple years of schooling paying for a degree, 221 00:09:38,400 --> 00:09:39,600 Speaker 2: and then you're kind of like, well, shoot, I don't 222 00:09:39,600 --> 00:09:41,360 Speaker 2: want to do this anymore. Yeah, like the sooner the better. 223 00:09:42,200 --> 00:09:44,080 Speaker 1: Just to figure that out, that the advanced degree is 224 00:09:44,120 --> 00:09:46,040 Speaker 1: gonna equate to more money, and that's not always a case. 225 00:09:46,080 --> 00:09:47,240 Speaker 1: You need to look into that on the front end. 226 00:09:47,200 --> 00:09:49,760 Speaker 1: I've known multiple people who go through and get like 227 00:09:49,920 --> 00:09:51,719 Speaker 1: at their master's degree and then oh, wait, a say, 228 00:09:51,800 --> 00:09:53,520 Speaker 1: I don't know, I'm not getting paid much more for this. 229 00:09:53,559 --> 00:09:55,080 Speaker 1: I thought I thought was going to result in like 230 00:09:55,120 --> 00:09:58,240 Speaker 1: significant income increases. Maybe maybe not right. 231 00:09:58,280 --> 00:09:59,560 Speaker 2: And that's one of the things you can learn with 232 00:09:59,559 --> 00:10:01,480 Speaker 2: an INTERNI as you're there around other folks who are 233 00:10:01,480 --> 00:10:03,960 Speaker 2: in the industry and you're like, oh, it might take 234 00:10:04,000 --> 00:10:05,920 Speaker 2: a little bit to get up to this conversational point 235 00:10:06,000 --> 00:10:08,280 Speaker 2: to say, hell, how much are you making? But I 236 00:10:08,320 --> 00:10:11,680 Speaker 2: love that it allows students college hopefully soon to be 237 00:10:11,800 --> 00:10:14,319 Speaker 2: college grads, the ability to get a taste of that work. 238 00:10:14,559 --> 00:10:17,600 Speaker 2: But then obviously you got the head start advantage of 239 00:10:17,640 --> 00:10:20,240 Speaker 2: an internship as well, because if you are in a 240 00:10:20,280 --> 00:10:21,800 Speaker 2: field that you want to be in, man, what a 241 00:10:21,840 --> 00:10:24,679 Speaker 2: great way just to basically get your foot in the door. 242 00:10:24,720 --> 00:10:25,920 Speaker 1: I think what you're saying too, is to be able 243 00:10:25,920 --> 00:10:30,040 Speaker 1: to bob and weave in kind of today's work climates. 244 00:10:30,200 --> 00:10:32,920 Speaker 1: And everyone knows this, right that people the jobs don't 245 00:10:33,000 --> 00:10:35,079 Speaker 1: last as long you're not necessarily employed by the same 246 00:10:35,120 --> 00:10:37,160 Speaker 1: employer for ten, twenty thirty years, and so. 247 00:10:37,480 --> 00:10:40,040 Speaker 2: It's going to require some of that resiliency in some 248 00:10:40,120 --> 00:10:42,480 Speaker 2: of that creativity that comes with not only switching jobs, 249 00:10:42,480 --> 00:10:44,360 Speaker 2: but switching even careers in industries. 250 00:10:44,400 --> 00:10:46,719 Speaker 1: Yeah, exactly. Yeah, And I think this also calls into 251 00:10:46,720 --> 00:10:48,600 Speaker 1: the question, and we've talked about this at different times 252 00:10:48,640 --> 00:10:50,839 Speaker 1: on the podcast too, the value of a college degree. 253 00:10:50,880 --> 00:10:53,040 Speaker 1: Has the value of a college degree diminished? I think 254 00:10:53,280 --> 00:10:56,199 Speaker 1: it's a nuanced conversation. But when you look at the 255 00:10:56,240 --> 00:10:59,800 Speaker 1: overall stats, the average college grad makes a million dollars 256 00:11:00,120 --> 00:11:01,800 Speaker 1: or over the course of a lifetime than the average 257 00:11:01,840 --> 00:11:03,920 Speaker 1: hig school grads a lot of money. That is telling, right, 258 00:11:04,400 --> 00:11:06,760 Speaker 1: but that also diminishes if you end up with the 259 00:11:06,800 --> 00:11:09,240 Speaker 1: wrong degree for the career that you want. But the 260 00:11:09,280 --> 00:11:10,920 Speaker 1: stats also bear out that even if you end up 261 00:11:11,000 --> 00:11:13,760 Speaker 1: underemployed with a college degree, you'll still earn twenty five 262 00:11:13,800 --> 00:11:16,600 Speaker 1: percent more than the average highchool graduate. Still, we would 263 00:11:16,600 --> 00:11:20,319 Speaker 1: say maybe not a full mill that's pretty good yeah, 264 00:11:20,520 --> 00:11:22,800 Speaker 1: as premium. So much of the value proposition depends on 265 00:11:22,800 --> 00:11:25,240 Speaker 1: what you study and what career path you want to take, 266 00:11:25,480 --> 00:11:28,120 Speaker 1: and then how much time and money you spend acquiring 267 00:11:28,160 --> 00:11:30,439 Speaker 1: that degree, because there are a lot of degrees that 268 00:11:30,480 --> 00:11:33,040 Speaker 1: people are spending six figures matt to get and those 269 00:11:33,040 --> 00:11:36,479 Speaker 1: degrees just don't pan out in terms of a significantly 270 00:11:36,520 --> 00:11:38,160 Speaker 1: higher salary. And then there are other people who are 271 00:11:38,200 --> 00:11:42,200 Speaker 1: just cut out for trade school, for entrepreneurship, for other things, 272 00:11:42,200 --> 00:11:44,400 Speaker 1: where college just isn't going to be as much of 273 00:11:44,400 --> 00:11:45,800 Speaker 1: a boon to their ultimate earnings. 274 00:11:45,840 --> 00:11:49,040 Speaker 2: Totally, I think it depends too on who you're asking, 275 00:11:49,200 --> 00:11:51,880 Speaker 2: or like where that person is, like what stage of 276 00:11:51,880 --> 00:11:53,240 Speaker 2: life that person is in, because I would like I 277 00:11:53,240 --> 00:11:55,600 Speaker 2: would have said in my twenties and early thirties, oh 278 00:11:55,600 --> 00:11:57,960 Speaker 2: my gosh, yeah, college total waste of time. I'm not 279 00:11:58,120 --> 00:12:00,000 Speaker 2: doing something that I studied in school. 280 00:12:01,280 --> 00:12:02,280 Speaker 1: But I don't know. 281 00:12:02,400 --> 00:12:04,320 Speaker 2: The older you get, you kind of realize, oh, there's 282 00:12:04,320 --> 00:12:09,000 Speaker 2: a more general knowledge. There's more formation taking place in 283 00:12:09,040 --> 00:12:11,360 Speaker 2: college than I think you give yourself credit for, Like 284 00:12:11,400 --> 00:12:13,959 Speaker 2: when you are in your twenties and now that I've 285 00:12:13,960 --> 00:12:16,280 Speaker 2: gotten older, I'm like, oh no, that was actually really 286 00:12:16,280 --> 00:12:16,680 Speaker 2: good for me. 287 00:12:17,480 --> 00:12:18,120 Speaker 1: To be there. 288 00:12:18,440 --> 00:12:20,440 Speaker 2: So I think a lot of it as to your 289 00:12:20,480 --> 00:12:22,680 Speaker 2: opinion and how you feel and how you think about 290 00:12:22,679 --> 00:12:25,240 Speaker 2: your degree. Aside from the numbers, it also I think 291 00:12:25,679 --> 00:12:28,640 Speaker 2: matters where you are in life, and that changes over time. Yeah, 292 00:12:28,679 --> 00:12:31,560 Speaker 2: but dude, let's talk about the credit bureaus credit scores 293 00:12:31,600 --> 00:12:35,079 Speaker 2: in particular, because for the past three years, the number 294 00:12:35,080 --> 00:12:39,520 Speaker 2: one complaint that the CFPB gets is credit report mistakes, 295 00:12:40,320 --> 00:12:43,920 Speaker 2: and the problem has gotten pretty bad. Complaints they have 296 00:12:44,000 --> 00:12:47,440 Speaker 2: tripled in just two years. Five hundred thousand folks they 297 00:12:47,440 --> 00:12:50,559 Speaker 2: have filed a complaint just last year, and there are 298 00:12:50,559 --> 00:12:54,400 Speaker 2: tens of millions more who are being impacted by faulty 299 00:12:54,520 --> 00:12:57,200 Speaker 2: incorrect information on their reports, but they just haven't filed 300 00:12:57,200 --> 00:13:00,360 Speaker 2: a complaint, or they're just completely unaware because they're just 301 00:13:00,400 --> 00:13:02,280 Speaker 2: cruising along, living life, doing their thing. 302 00:13:02,320 --> 00:13:05,040 Speaker 1: Yeah, it's amazing to think how how much complaints of skyrocketed, 303 00:13:05,040 --> 00:13:06,600 Speaker 1: and yet there's still a lot of people who don't 304 00:13:06,600 --> 00:13:07,880 Speaker 1: pay a take on the credit store. They don't know 305 00:13:07,920 --> 00:13:09,120 Speaker 1: what's on their credit report exactly. 306 00:13:09,200 --> 00:13:12,679 Speaker 2: Yeah, So basically, something is on your credit report that 307 00:13:12,840 --> 00:13:16,199 Speaker 2: shouldn't be experienced. They settled a class action lawsuit late 308 00:13:16,280 --> 00:13:19,360 Speaker 2: last year for twenty two million dollars for ruining the 309 00:13:19,400 --> 00:13:21,760 Speaker 2: credit report of a ton of their customers. But of 310 00:13:22,080 --> 00:13:24,960 Speaker 2: course this is a settlement, which means they admitted to 311 00:13:25,000 --> 00:13:29,280 Speaker 2: no wrongdoing, which is pretty classic and this problem that's just. 312 00:13:29,200 --> 00:13:31,000 Speaker 1: When people pay money and then they're like, but we 313 00:13:31,040 --> 00:13:33,360 Speaker 1: don't we didn't do anything wrong, no admission of guilt. 314 00:13:33,440 --> 00:13:34,840 Speaker 1: Then why did you pay the twenty two mel If 315 00:13:34,880 --> 00:13:36,280 Speaker 1: you don't feel like you did anything wrong. That's how 316 00:13:36,280 --> 00:13:36,840 Speaker 1: our justice is. 317 00:13:38,480 --> 00:13:40,120 Speaker 2: But the problem has gotten out of hand because of 318 00:13:40,160 --> 00:13:43,080 Speaker 2: the way the credit bureaus approach any sort of complaint 319 00:13:43,440 --> 00:13:44,920 Speaker 2: is kind of like poor. 320 00:13:44,720 --> 00:13:45,480 Speaker 1: Salt in the wound. 321 00:13:45,920 --> 00:13:48,400 Speaker 2: They now have an automated system that handles the first 322 00:13:48,520 --> 00:13:51,200 Speaker 2: round of disputes that get filed, and of course it 323 00:13:51,240 --> 00:13:53,280 Speaker 2: finds that your dispute has no merit. 324 00:13:53,120 --> 00:13:55,760 Speaker 1: E basically every time, even though it actually does. The 325 00:13:55,800 --> 00:13:56,360 Speaker 1: tree is. 326 00:13:56,400 --> 00:13:59,880 Speaker 2: Roughly twenty five percent of credit reports contain an air, 327 00:14:00,880 --> 00:14:03,679 Speaker 2: So we think this is worth putting on your putting 328 00:14:03,679 --> 00:14:06,319 Speaker 2: on your radar. And the big three bureaus, they're really 329 00:14:06,480 --> 00:14:09,080 Speaker 2: bad at their jobs. Personally, I don't think that any 330 00:14:09,160 --> 00:14:13,079 Speaker 2: additional government oversight or any additional regulation is going to 331 00:14:13,400 --> 00:14:14,520 Speaker 2: bring much result. 332 00:14:14,559 --> 00:14:15,079 Speaker 1: I feel like the. 333 00:14:15,040 --> 00:14:17,560 Speaker 2: Government can barely keep the lights on without passing short 334 00:14:17,600 --> 00:14:19,920 Speaker 2: term spending bills, and they're just kicking the can down 335 00:14:19,960 --> 00:14:22,480 Speaker 2: their road, which makes me think, well, okay, well, like, 336 00:14:22,560 --> 00:14:25,640 Speaker 2: what are the actual alternatives. This isn't something we talk 337 00:14:25,800 --> 00:14:31,200 Speaker 2: much about, but having loans, like specifically mortgages manually underwritten 338 00:14:31,560 --> 00:14:35,640 Speaker 2: is totally an alternative option. I had my very first 339 00:14:35,680 --> 00:14:39,880 Speaker 2: mortgage manually underwritten, and honestly, pretty much every mortgage like 340 00:14:39,920 --> 00:14:42,320 Speaker 2: for investment properties as well, because I'm self employed and 341 00:14:42,920 --> 00:14:45,320 Speaker 2: you know, if you have irregular sources of income, they 342 00:14:45,360 --> 00:14:47,600 Speaker 2: want to know all the information on you before they're like, 343 00:14:47,640 --> 00:14:49,800 Speaker 2: oh yeah, yeahh we'll give you, We'll give you a loan. 344 00:14:50,080 --> 00:14:53,120 Speaker 2: But this is something that the folks over at Ramsey 345 00:14:53,160 --> 00:14:55,600 Speaker 2: they talk about this all the time, and I think 346 00:14:55,600 --> 00:14:58,160 Speaker 2: I'm going to find myself kind of barking up this 347 00:14:58,200 --> 00:15:00,840 Speaker 2: tree a lot more because it is an alternative option, 348 00:15:00,880 --> 00:15:02,880 Speaker 2: and it's honestly the one that seems the most viable 349 00:15:03,440 --> 00:15:05,960 Speaker 2: as opposed to waving a magical wand and fixing the 350 00:15:05,960 --> 00:15:09,360 Speaker 2: system that seems to be broken and does not seem 351 00:15:09,400 --> 00:15:11,760 Speaker 2: like there is anybody that's going to hold them accountable. 352 00:15:11,800 --> 00:15:13,720 Speaker 1: Yeah, it's a shame. I mean that's what the CFPB 353 00:15:13,920 --> 00:15:15,800 Speaker 1: is supposed to be. They're supposed to be there to 354 00:15:15,880 --> 00:15:18,960 Speaker 1: kind of help consumers and keep these financial institutions hold 355 00:15:19,000 --> 00:15:20,680 Speaker 1: them accountable. I have less and less hope of that 356 00:15:20,720 --> 00:15:23,160 Speaker 1: actually happened. Yeah, that's that's my problem. In an ideal world, 357 00:15:23,200 --> 00:15:25,200 Speaker 1: the credit score and the credit report would be a 358 00:15:26,360 --> 00:15:30,280 Speaker 1: reflection of our financial prowess and kind of how we've 359 00:15:30,320 --> 00:15:34,520 Speaker 1: done handling debt, because that helps lenders understand pretty quickly 360 00:15:34,880 --> 00:15:37,520 Speaker 1: how we're going to handle alone that they might give 361 00:15:37,600 --> 00:15:40,120 Speaker 1: us right Totally, that can help a mortgage lender feel 362 00:15:40,120 --> 00:15:42,880 Speaker 1: really comfortable. I'm surprised that these businesses that are buying 363 00:15:42,920 --> 00:15:45,360 Speaker 1: credit scores from these bureaus aren't pushing back and saying, 364 00:15:45,360 --> 00:15:48,360 Speaker 1: what you guys are selling us completely inaccurate information that 365 00:15:48,400 --> 00:15:50,720 Speaker 1: you would think that would be frustrating for them because 366 00:15:50,760 --> 00:15:53,040 Speaker 1: it's harder to verify when something like twenty twenty five 367 00:15:53,040 --> 00:15:55,360 Speaker 1: percent of these credit bureaus contain a mistake. Totally, the 368 00:15:55,640 --> 00:15:57,880 Speaker 1: bureaus aren't doing the job for the businesses they're supposed 369 00:15:57,880 --> 00:15:59,520 Speaker 1: to serve. That's a crappy product, and who ends up 370 00:15:59,560 --> 00:16:01,040 Speaker 1: in the who ens up getting screwed in the middle. 371 00:16:01,040 --> 00:16:04,880 Speaker 1: It's every single consumer out there who has who's impacted 372 00:16:04,880 --> 00:16:06,880 Speaker 1: by credit reports that aren't accurate. 373 00:16:06,960 --> 00:16:09,880 Speaker 2: Hey, here's a here's a potential silver lining. Maybe this 374 00:16:09,960 --> 00:16:12,640 Speaker 2: is where buy now, Pay later comes to the rescue 375 00:16:12,840 --> 00:16:17,520 Speaker 2: of consumers, the ability to provide perhaps better information as 376 00:16:17,560 --> 00:16:21,120 Speaker 2: they're maybe creating their own databases. Yeah maybe you never know. 377 00:16:21,160 --> 00:16:21,400 Speaker 2: I'm not. 378 00:16:21,520 --> 00:16:25,040 Speaker 1: I'm also not counting on that actually coming to fruition. Yeah, yeah, 379 00:16:25,200 --> 00:16:26,960 Speaker 1: I know. It's it's just tough and I think like 380 00:16:27,000 --> 00:16:29,000 Speaker 1: the well, the other thing to do is to keep 381 00:16:29,000 --> 00:16:31,000 Speaker 1: an eye on your credit report and on your credit score. 382 00:16:31,080 --> 00:16:33,720 Speaker 1: And your score is a reflection essentially of what's on 383 00:16:33,760 --> 00:16:35,960 Speaker 1: your report. So if you see your score drop thirty 384 00:16:35,960 --> 00:16:37,560 Speaker 1: forty points and you're like, wait a second, I paid 385 00:16:37,560 --> 00:16:39,520 Speaker 1: everything on time, nothing changed, Well that's going on there. 386 00:16:39,640 --> 00:16:41,240 Speaker 1: Dig into your credit report. You can find it for 387 00:16:41,240 --> 00:16:44,440 Speaker 1: free at annual credit report dot com. If you keep 388 00:16:44,480 --> 00:16:47,920 Speaker 1: tabs on that, you have the ability then to file 389 00:16:47,920 --> 00:16:49,880 Speaker 1: a dispute, to ramp things up, to file a complaint 390 00:16:49,880 --> 00:16:53,760 Speaker 1: with the CFPB. Then if the credit utters don't respond 391 00:16:53,960 --> 00:16:56,360 Speaker 1: in a helpful way once you file that complaint, which 392 00:16:56,360 --> 00:16:59,160 Speaker 1: they probably won't. So but this is this is it 393 00:16:59,240 --> 00:17:01,000 Speaker 1: sucks that this is burden that we take on us 394 00:17:01,000 --> 00:17:02,680 Speaker 1: because they're really bad at their jobs. But it is 395 00:17:02,720 --> 00:17:04,680 Speaker 1: kind of the burden that we bear because the credit 396 00:17:04,720 --> 00:17:07,440 Speaker 1: score and the credit report are so integral to how 397 00:17:07,840 --> 00:17:11,520 Speaker 1: we function in the modern era. I'm sinking at manual underwriting. Yeah, 398 00:17:11,520 --> 00:17:13,760 Speaker 1: but what if your credit score gets screwed by forty 399 00:17:13,800 --> 00:17:15,640 Speaker 1: points and you're a renter and you're trying to apply 400 00:17:15,680 --> 00:17:17,520 Speaker 1: to rent a new place, Well, then you have the 401 00:17:17,600 --> 00:17:20,199 Speaker 1: job explained to that that landlord. Hey, guess what, I 402 00:17:20,240 --> 00:17:22,000 Speaker 1: promise my credit score is actually better than this more 403 00:17:22,040 --> 00:17:23,680 Speaker 1: hoops to jump through. Yeah, and it's just. 404 00:17:24,080 --> 00:17:26,640 Speaker 2: But I will say, landlords will actually take a look 405 00:17:26,640 --> 00:17:27,840 Speaker 2: at the will. 406 00:17:27,920 --> 00:17:29,080 Speaker 1: Yeah, some well exactly. 407 00:17:29,160 --> 00:17:31,119 Speaker 2: I mean I know that I would like I currently 408 00:17:31,119 --> 00:17:32,840 Speaker 2: have currently have renters who had. 409 00:17:32,600 --> 00:17:34,440 Speaker 1: A really rough credit score, but. 410 00:17:34,400 --> 00:17:37,840 Speaker 2: They explained their situation this kind of the financial hardship 411 00:17:37,840 --> 00:17:40,040 Speaker 2: they experienced in the past where they are currently and 412 00:17:40,160 --> 00:17:42,000 Speaker 2: I got to see all. You know that there's a 413 00:17:42,040 --> 00:17:44,119 Speaker 2: lot of corporate landlords aren't as nice as here one 414 00:17:44,160 --> 00:17:44,640 Speaker 2: hundred percent. 415 00:17:44,720 --> 00:17:45,080 Speaker 1: I get that. 416 00:17:45,200 --> 00:17:47,000 Speaker 2: Yeah, I guess I can. I can't also wave my 417 00:17:47,040 --> 00:17:50,560 Speaker 2: wand and expect that corporations are also going to go 418 00:17:50,640 --> 00:17:52,840 Speaker 2: through the additional steps required as opposed to just simply 419 00:17:52,920 --> 00:17:53,879 Speaker 2: looking at a credit score. 420 00:17:53,960 --> 00:17:55,840 Speaker 1: So I guess that there's a bunch of different takeaways 421 00:17:55,840 --> 00:17:58,360 Speaker 1: from this. One to credit bureau suck, and two you've 422 00:17:58,400 --> 00:18:00,800 Speaker 1: got to watch your own back. And you can get 423 00:18:00,840 --> 00:18:03,800 Speaker 1: your free credit report. There's one place, the federally section 424 00:18:03,880 --> 00:18:06,159 Speaker 1: site Annual Credit Report dot com, and sign up for 425 00:18:06,160 --> 00:18:08,560 Speaker 1: at sight maybe like credit Karma, or maybe log in 426 00:18:08,600 --> 00:18:11,200 Speaker 1: once a month to check your if your credit card 427 00:18:11,200 --> 00:18:13,480 Speaker 1: allows you to get a visual on that credit score, 428 00:18:13,560 --> 00:18:15,679 Speaker 1: just follow it roughly, loosely. You don't need to be 429 00:18:15,680 --> 00:18:17,760 Speaker 1: obsessed with it, but just kind of knowing generally where 430 00:18:17,800 --> 00:18:19,359 Speaker 1: it is and if there is some sort of a 431 00:18:19,359 --> 00:18:21,800 Speaker 1: sudden drop that allows you that'll alert you to something 432 00:18:21,840 --> 00:18:23,040 Speaker 1: going wrong, something that's amiss. 433 00:18:23,080 --> 00:18:25,400 Speaker 2: But we've got more stories to get to, including we've 434 00:18:25,400 --> 00:18:29,120 Speaker 2: got just a fascinating scam. And you're probably thinking, oh, 435 00:18:29,119 --> 00:18:30,959 Speaker 2: I don't care about scams. No, no, no, this is 436 00:18:31,040 --> 00:18:33,600 Speaker 2: this is a really really good scam. Or share it 437 00:18:33,640 --> 00:18:34,919 Speaker 2: hit somebody that you would normally not. 438 00:18:34,960 --> 00:18:36,359 Speaker 1: Think it would. I know, I know, we'll get to 439 00:18:36,400 --> 00:18:46,360 Speaker 1: that more right after this. All right, Matt, we're back. 440 00:18:46,400 --> 00:18:49,840 Speaker 1: The Friday flight continues. More personal finance goodness to get 441 00:18:49,840 --> 00:18:52,040 Speaker 1: to on this episode, we always got to get to 442 00:18:52,080 --> 00:18:55,240 Speaker 1: the ludicrous headline of the week. This one comes from 443 00:18:55,320 --> 00:18:57,720 Speaker 1: The New Yorker and here's what the headline reads. The 444 00:18:57,800 --> 00:18:59,800 Speaker 1: day I put fifty thousand dollars into a shoe box 445 00:18:59,800 --> 00:19:01,720 Speaker 1: and hey it to a stranger. I never thought I 446 00:19:01,760 --> 00:19:04,399 Speaker 1: was the kind of person to fall for a scam. 447 00:19:04,560 --> 00:19:06,960 Speaker 1: Whoa man? This art. Everyone should read this article fIF 448 00:19:06,960 --> 00:19:10,880 Speaker 1: two thousand dollars. It's fascinating and it's ludicrous on many 449 00:19:10,880 --> 00:19:14,680 Speaker 1: fronts too. First, the story itself just incredible. You've you've 450 00:19:14,680 --> 00:19:17,680 Speaker 1: got to read it. It's a longer, more meandering scam 451 00:19:17,800 --> 00:19:19,600 Speaker 1: it which is kind of makes it so interestingly. Then 452 00:19:19,640 --> 00:19:22,679 Speaker 1: the scammers are less directive and more just kind of 453 00:19:22,680 --> 00:19:25,160 Speaker 1: going with the flow as they call this person and 454 00:19:25,359 --> 00:19:27,360 Speaker 1: that are trying to get them to cough over some money. 455 00:19:27,520 --> 00:19:30,080 Speaker 2: It's it's like a case study and how to scam people. 456 00:19:30,119 --> 00:19:32,439 Speaker 1: Yeah, honestly, it really is. And like it's good. You know, 457 00:19:32,480 --> 00:19:33,840 Speaker 1: like there's hackers now that we're encouraging. 458 00:19:33,880 --> 00:19:36,560 Speaker 2: There's white hat hackers and black hat hackers or whatever, 459 00:19:36,600 --> 00:19:39,320 Speaker 2: and so like like you hire hackers, like an organization 460 00:19:39,359 --> 00:19:42,760 Speaker 2: will or a company to try to penetrate your cybersecurity, 461 00:19:43,000 --> 00:19:45,560 Speaker 2: to let you know how did you can improve read 462 00:19:45,600 --> 00:19:48,959 Speaker 2: this story so that you can learn from this individual's mistake. 463 00:19:49,000 --> 00:19:51,840 Speaker 1: That's right. That way you can learn just how freaking 464 00:19:51,880 --> 00:19:53,439 Speaker 1: good they are. Yeah, So it starts off with like 465 00:19:53,480 --> 00:19:56,600 Speaker 1: a fake Amazon employee giving you a call attempting to 466 00:19:56,720 --> 00:20:00,640 Speaker 1: verify account activity that's fraudulent, and like, in this case, 467 00:20:00,720 --> 00:20:02,760 Speaker 1: there was no account activity that was fraudulent, but she's like, oh, 468 00:20:02,760 --> 00:20:05,000 Speaker 1: they've opened up another account in your name, And then 469 00:20:05,240 --> 00:20:08,040 Speaker 1: the person who got scam is like what so yeah, 470 00:20:08,080 --> 00:20:10,879 Speaker 1: then that Amazon employee connects the person who wrote this 471 00:20:10,960 --> 00:20:13,280 Speaker 1: article to someone at the CIA because this kind of 472 00:20:13,280 --> 00:20:17,199 Speaker 1: fraud is apparently happening regularly. And then it ends up 473 00:20:17,240 --> 00:20:20,840 Speaker 1: matt with the writer handing over so sadly fifty thousand 474 00:20:20,880 --> 00:20:22,840 Speaker 1: dollars in cash that she put in a shoe box 475 00:20:23,400 --> 00:20:26,160 Speaker 1: to what she thought was an undercover CIA agent. Pretty 476 00:20:26,200 --> 00:20:28,840 Speaker 1: horrifying stuff. It's again, it's worth the read. It's a 477 00:20:28,840 --> 00:20:32,000 Speaker 1: complex scam, but it's just crazy to think that scams 478 00:20:32,000 --> 00:20:33,040 Speaker 1: have gotten this good. 479 00:20:33,080 --> 00:20:37,919 Speaker 2: Okay, So the other ridiculous, ludicrous part of this article 480 00:20:38,320 --> 00:20:41,639 Speaker 2: is that the person wasn't just any writer. It happened 481 00:20:41,640 --> 00:20:44,080 Speaker 2: to be. And I'll share a name because obviously she 482 00:20:44,160 --> 00:20:45,040 Speaker 2: published this herself. 483 00:20:45,119 --> 00:20:45,280 Speaker 1: Yeah. 484 00:20:45,280 --> 00:20:46,480 Speaker 2: I don't know how to say her last name, but 485 00:20:46,520 --> 00:20:49,200 Speaker 2: her Charlotte's cows. I guess this is how you pronounce 486 00:20:49,200 --> 00:20:52,280 Speaker 2: her name. She's the financial advice columnist for The New Yorker. 487 00:20:52,480 --> 00:20:53,639 Speaker 1: She writes for the New York Times. 488 00:20:53,720 --> 00:20:57,000 Speaker 2: Man, I certainly feel for her and felt terrible while 489 00:20:57,080 --> 00:21:01,320 Speaker 2: reading this awful documentation of what she went through. But man, 490 00:21:01,359 --> 00:21:03,400 Speaker 2: there are so many points along the way that red 491 00:21:03,400 --> 00:21:05,600 Speaker 2: flags should have been going off, Like I would just 492 00:21:05,640 --> 00:21:08,840 Speaker 2: hope that someone with her level of money, experienced and 493 00:21:09,000 --> 00:21:12,159 Speaker 2: sophistication wouldn't have fallen for a scam like this. But 494 00:21:12,240 --> 00:21:16,480 Speaker 2: it also reveals how good these gamers have gotten, and 495 00:21:16,600 --> 00:21:20,240 Speaker 2: they're not just targeting the elderly. They often end up 496 00:21:20,600 --> 00:21:23,399 Speaker 2: conning millennials and gen zers out there, So we want 497 00:21:23,480 --> 00:21:26,399 Speaker 2: folks to be careful. This is something that can Like 498 00:21:26,440 --> 00:21:28,280 Speaker 2: if it can happen to someone who eats and breeze money, 499 00:21:28,320 --> 00:21:31,679 Speaker 2: I think it can happen to almost anyone. They slowly 500 00:21:32,040 --> 00:21:35,560 Speaker 2: tightened the I mean, man, it was so steady and 501 00:21:35,640 --> 00:21:38,800 Speaker 2: incremental and like they were slowly removing her from reality 502 00:21:39,119 --> 00:21:41,080 Speaker 2: and placing her in a reality that. 503 00:21:41,000 --> 00:21:43,200 Speaker 1: They had created, and before you know, it almost broke 504 00:21:43,240 --> 00:21:45,960 Speaker 1: her brain. It was crazy, Yeah, it was, Oh man, 505 00:21:46,040 --> 00:21:49,720 Speaker 1: it was it was like psychological terrorism. Yes, yeah, so 506 00:21:49,800 --> 00:21:52,000 Speaker 1: you have to read link to it in the show 507 00:21:52,000 --> 00:21:55,560 Speaker 1: notes and hopefully it's it's just a sad case, but 508 00:21:55,600 --> 00:21:57,919 Speaker 1: it's hopefully enlightening as well, and just these are the 509 00:21:58,000 --> 00:22:00,199 Speaker 1: kinds of ways scammers can get to you. Now, you 510 00:22:00,240 --> 00:22:02,000 Speaker 1: might think you're not susceptible. I think most of us 511 00:22:02,040 --> 00:22:02,800 Speaker 1: would like to think that. 512 00:22:03,040 --> 00:22:05,240 Speaker 2: But if that's what I thought before reading this article, 513 00:22:05,440 --> 00:22:06,720 Speaker 2: but then as I was reading through it, I was. 514 00:22:06,720 --> 00:22:07,840 Speaker 1: Like, oh, oh that's good. 515 00:22:08,000 --> 00:22:10,520 Speaker 2: Oh oh man, And I would like to think that 516 00:22:10,560 --> 00:22:12,560 Speaker 2: I wouldn't also fall for something like this, but. 517 00:22:12,480 --> 00:22:14,960 Speaker 1: I could totally see how she did for sure. Yeah, 518 00:22:15,040 --> 00:22:16,800 Speaker 1: so all right, let's move on, Matete, let's talk about 519 00:22:16,840 --> 00:22:19,760 Speaker 1: dynamic pricing. We titled this one Fluctuating fast Food. We 520 00:22:19,760 --> 00:22:22,199 Speaker 1: also could have called it frosty Foibles. I think because 521 00:22:22,520 --> 00:22:26,399 Speaker 1: this is a Wendy's maneuver, and the thing is, dynamic 522 00:22:26,400 --> 00:22:29,080 Speaker 1: pricing has been around for a long time. Basically, Wendy's 523 00:22:29,119 --> 00:22:30,840 Speaker 1: is now saying we're going to jump into the dynamic 524 00:22:30,920 --> 00:22:34,159 Speaker 1: pricing Sphere and Amazon, for instance, the price of the 525 00:22:34,200 --> 00:22:36,040 Speaker 1: item that you want to buy could change dozens of 526 00:22:36,040 --> 00:22:40,040 Speaker 1: times in a single day. Airfare similar price machinations, like 527 00:22:40,119 --> 00:22:42,560 Speaker 1: so you might try to book something in the morning 528 00:22:42,640 --> 00:22:44,800 Speaker 1: and go back later that day and the flight now 529 00:22:44,800 --> 00:22:47,679 Speaker 1: cost one hundred and fifty bucks more. That's dynamic pricing 530 00:22:47,720 --> 00:22:51,080 Speaker 1: at its best or worst. I guess ride sharing, right, 531 00:22:51,160 --> 00:22:53,360 Speaker 1: those costs vary depending on when you book. Two. There's 532 00:22:53,600 --> 00:22:56,560 Speaker 1: surge pricing, right that Uber has become so famous for. Well, 533 00:22:56,840 --> 00:22:59,720 Speaker 1: fast food is apparently getting on this trend, specifically Wendy's. 534 00:22:59,720 --> 00:23:02,560 Speaker 1: They say they're going to pilot fast food surge pricing 535 00:23:02,880 --> 00:23:05,960 Speaker 1: a la Uber next year. So your burger and fries 536 00:23:05,960 --> 00:23:08,800 Speaker 1: maybe cost three bucks at eleven am or four dollars 537 00:23:08,800 --> 00:23:11,000 Speaker 1: and fifty cents at noon. It just depends. You don't 538 00:23:11,040 --> 00:23:13,280 Speaker 1: know what it's going to be when you walk in there. Matt, 539 00:23:13,280 --> 00:23:15,000 Speaker 1: I actually think it's a bad idea for Wendy's. I 540 00:23:15,000 --> 00:23:18,159 Speaker 1: think dynamic pricing seems terrible. It works really well for 541 00:23:18,200 --> 00:23:20,760 Speaker 1: some industries. I don't see it working terribly well in 542 00:23:20,800 --> 00:23:22,560 Speaker 1: the fast food game. Like, I could see this being 543 00:23:22,600 --> 00:23:25,399 Speaker 1: far more confusing for consumers who want to know what 544 00:23:25,400 --> 00:23:26,840 Speaker 1: their meal is going to cost before they head to 545 00:23:26,840 --> 00:23:29,320 Speaker 1: the restaurant. I think there are potentially better ways to 546 00:23:29,400 --> 00:23:31,479 Speaker 1: skin this cat for them as a whole. I think 547 00:23:31,560 --> 00:23:34,440 Speaker 1: dynamic pricing is actually a good thing for savvy consumers 548 00:23:34,560 --> 00:23:36,600 Speaker 1: who are willing to pivot, willing to change their habits, 549 00:23:36,640 --> 00:23:38,800 Speaker 1: willing to shop around. But in the case of fast food, 550 00:23:38,800 --> 00:23:40,760 Speaker 1: I just don't see Wendy's like making out like a 551 00:23:40,800 --> 00:23:41,280 Speaker 1: bandit with this. 552 00:23:41,440 --> 00:23:43,520 Speaker 2: Yeah, if you can zag while everyone else is zigging, 553 00:23:43,640 --> 00:23:47,600 Speaker 2: that's when dynamic pricing, just like with just like with airfare, 554 00:23:47,760 --> 00:23:49,919 Speaker 2: if you can travel when everybody else isn't traveling, all right, 555 00:23:49,960 --> 00:23:52,399 Speaker 2: well you have the potential to totally snagg it. 556 00:23:52,480 --> 00:23:54,080 Speaker 1: Or do they just did like a generic ten percent 557 00:23:54,119 --> 00:23:55,800 Speaker 1: discount during those off peak hours. 558 00:23:56,359 --> 00:23:58,760 Speaker 2: Yeah, it's just a different way of skinning the Cat's 559 00:23:59,040 --> 00:24:02,720 Speaker 2: way is not how they're going about it. It's counter 560 00:24:02,840 --> 00:24:04,880 Speaker 2: to I think what people think of with fast food. 561 00:24:04,920 --> 00:24:06,200 Speaker 2: Like when you get fast food, you want it to 562 00:24:06,240 --> 00:24:08,440 Speaker 2: be quick and what else. 563 00:24:08,480 --> 00:24:12,040 Speaker 1: Pretty cheap. You want it to be affordable, also terribly unhealthy. 564 00:24:11,600 --> 00:24:14,120 Speaker 2: And when you don't know what's gonna what it's gonna 565 00:24:14,160 --> 00:24:16,000 Speaker 2: cost you when you go out to grab a quick 566 00:24:16,080 --> 00:24:18,359 Speaker 2: lunch I feel like that's gonna it's gonna backfire. Like 567 00:24:18,400 --> 00:24:21,399 Speaker 2: it makes me think about right after college, before I 568 00:24:21,480 --> 00:24:25,680 Speaker 2: knew anything about cooking food at home and eating affordably, though, 569 00:24:25,680 --> 00:24:28,760 Speaker 2: I was still watching my budget a decent bit, and 570 00:24:28,800 --> 00:24:30,800 Speaker 2: because of that, I knew exactly what it would cost 571 00:24:30,800 --> 00:24:33,919 Speaker 2: me to go to the local McDonald's and I wouldn't 572 00:24:33,920 --> 00:24:35,960 Speaker 2: get a little side salid. I would get a cheeseburger 573 00:24:36,000 --> 00:24:38,560 Speaker 2: and i'd get a yogurt parfe. Now that sounds like 574 00:24:38,560 --> 00:24:39,480 Speaker 2: a really healthy McDonald's. 575 00:24:39,800 --> 00:24:40,400 Speaker 1: It's not too bad. 576 00:24:41,480 --> 00:24:43,679 Speaker 2: But also I know now that that's still a very 577 00:24:43,720 --> 00:24:46,400 Speaker 2: expensive way of eating lunch versus what we do these days. 578 00:24:46,440 --> 00:24:47,680 Speaker 1: Or do you want to tell people what you used 579 00:24:47,680 --> 00:24:50,080 Speaker 1: to do in college at the food court at the 580 00:24:50,160 --> 00:24:51,200 Speaker 1: college campus food court? 581 00:24:51,359 --> 00:24:54,800 Speaker 2: We okay, So the meal plan at UGA is pretty 582 00:24:54,880 --> 00:24:57,600 Speaker 2: dang expensive. And I lived off campus even though we 583 00:24:57,640 --> 00:25:00,320 Speaker 2: were we live very very close to campus technically, like 584 00:25:00,359 --> 00:25:01,800 Speaker 2: in the dorm, didn't make sense to pay. 585 00:25:01,640 --> 00:25:02,320 Speaker 1: For the meal plan. 586 00:25:02,520 --> 00:25:05,440 Speaker 2: However, it's like a buffet when you go there, and 587 00:25:05,480 --> 00:25:08,240 Speaker 2: so I drop twelve bucks, which is pretty expensive for 588 00:25:08,280 --> 00:25:09,919 Speaker 2: a college student. But I would sit there for multiple 589 00:25:09,920 --> 00:25:11,520 Speaker 2: meals and just eat all day long. 590 00:25:11,640 --> 00:25:13,879 Speaker 1: You just like literally hang out, take all your meetings 591 00:25:13,920 --> 00:25:15,439 Speaker 1: in there, do all your studying in there, and just 592 00:25:15,480 --> 00:25:15,760 Speaker 1: have like. 593 00:25:15,800 --> 00:25:19,359 Speaker 2: Bright dinner Snelling Thursdays is what we called it, because 594 00:25:19,400 --> 00:25:20,960 Speaker 2: all this is going to be there and everyone would 595 00:25:20,960 --> 00:25:21,280 Speaker 2: come by. 596 00:25:21,440 --> 00:25:22,280 Speaker 1: Love it. The body. 597 00:25:22,320 --> 00:25:24,840 Speaker 2: It is incredible because the way it works, you eat 598 00:25:24,880 --> 00:25:26,960 Speaker 2: all this food and it stores it in your body. 599 00:25:27,040 --> 00:25:28,920 Speaker 2: That's just that's the way fat works. You know, the 600 00:25:29,480 --> 00:25:31,159 Speaker 2: fat and the vitem is of the new also with 601 00:25:31,200 --> 00:25:34,480 Speaker 2: the nutrients. Anyway, all that being said, going back to McDonald's, 602 00:25:34,560 --> 00:25:36,040 Speaker 2: I think I would have been far less likely to 603 00:25:36,040 --> 00:25:37,320 Speaker 2: do that if I didn't know what the price was 604 00:25:37,359 --> 00:25:39,160 Speaker 2: going to be. So I don't like, like you said, 605 00:25:39,160 --> 00:25:41,920 Speaker 2: I like your approach to it. Offer a discount on 606 00:25:41,960 --> 00:25:45,119 Speaker 2: some of those off peak dining outs and hours. 607 00:25:44,840 --> 00:25:46,440 Speaker 1: When you serve a consumers. They hate the idea of 608 00:25:46,480 --> 00:25:48,080 Speaker 1: surch pricing. I think again, it makes sense for a 609 00:25:48,119 --> 00:25:51,000 Speaker 1: lot of businesses, but just there's a better week. Yeah, totally. 610 00:25:51,080 --> 00:25:53,520 Speaker 2: And the fact is CEO Kirk Tanner he was a 611 00:25:53,520 --> 00:25:56,040 Speaker 2: little upset. He made it clear that he didn't actually 612 00:25:56,080 --> 00:25:59,960 Speaker 2: say surge pricing, so okay, but he definitely did talk 613 00:26:00,040 --> 00:26:03,640 Speaker 2: about it as dynamic pricing, which sounds kind of similar. 614 00:26:04,000 --> 00:26:04,639 Speaker 1: But Okay. 615 00:26:04,840 --> 00:26:08,800 Speaker 2: We occasionally rail about the subscription economy that we're living in, 616 00:26:09,280 --> 00:26:11,640 Speaker 2: and there are obviously some nice things about it, right, 617 00:26:11,680 --> 00:26:15,360 Speaker 2: you can cancel whatever you want. You can then, oh, actually, 618 00:26:15,400 --> 00:26:17,320 Speaker 2: I see new shows coming. I'm gonna go ahead and 619 00:26:17,320 --> 00:26:21,560 Speaker 2: rejoin Netflix. Squad Game season two. Yeah, it often means 620 00:26:21,560 --> 00:26:24,640 Speaker 2: that we're able to remove an expensive upfront cost by 621 00:26:24,760 --> 00:26:28,320 Speaker 2: being strategic. But even still, recurring subscriptions are easy to 622 00:26:28,359 --> 00:26:32,200 Speaker 2: forget about. They cost the average American two hundred and 623 00:26:32,280 --> 00:26:35,280 Speaker 2: nineteen dollars a month. The subscriptions that we forget about, 624 00:26:35,600 --> 00:26:38,600 Speaker 2: and even though we're getting something in return, because of 625 00:26:38,640 --> 00:26:41,160 Speaker 2: the nature of the model, we often forget that even 626 00:26:41,200 --> 00:26:44,280 Speaker 2: what we're subscribed to, which means we underestimate how many 627 00:26:44,320 --> 00:26:48,640 Speaker 2: dollars we're actually wasting. But there is another subscription attempting 628 00:26:48,640 --> 00:26:51,439 Speaker 2: to siphon money from us every single month, and that 629 00:26:51,600 --> 00:26:55,920 Speaker 2: is the local car wash. Bloomberg, they read about the 630 00:26:55,960 --> 00:26:59,720 Speaker 2: proliferation of car washes recently. There's a new one on 631 00:26:59,800 --> 00:27:02,280 Speaker 2: our our route to school. That is, the girls are like, 632 00:27:02,280 --> 00:27:04,200 Speaker 2: that's gonna be a new car wash. I hate that 633 00:27:04,240 --> 00:27:06,760 Speaker 2: they're looking all over the place that they're looking forward 634 00:27:06,760 --> 00:27:09,960 Speaker 2: to it and so instead of paying like four or five, 635 00:27:10,080 --> 00:27:12,359 Speaker 2: six seven bucks for a wash, they want you to 636 00:27:12,359 --> 00:27:14,240 Speaker 2: fork over twenty dollars a month. 637 00:27:14,960 --> 00:27:17,680 Speaker 1: Or more or yeah, or thirty five forty. 638 00:27:17,800 --> 00:27:19,800 Speaker 2: And I'm not gonna I'm not gonna completely hate on 639 00:27:20,840 --> 00:27:23,760 Speaker 2: the subscription car wash in particular, if you really like 640 00:27:23,800 --> 00:27:26,359 Speaker 2: having a shiny car, you know, looking off fresh, that's fine. 641 00:27:26,400 --> 00:27:28,600 Speaker 2: If that's your craft beer equivalent. You spend a lot 642 00:27:28,640 --> 00:27:30,800 Speaker 2: of money on your car. If you park outside and 643 00:27:30,840 --> 00:27:33,199 Speaker 2: it's pollen season and you got all the tree bits 644 00:27:33,359 --> 00:27:36,240 Speaker 2: falling getting caught in your air intake, I get that. 645 00:27:36,359 --> 00:27:38,960 Speaker 2: That's that's annoying, But we just want to make sure 646 00:27:39,119 --> 00:27:41,879 Speaker 2: that you are being careful for what it is that 647 00:27:41,920 --> 00:27:42,800 Speaker 2: you're subscribing to. 648 00:27:42,840 --> 00:27:45,240 Speaker 1: Especially Yeah, because it's Bloomberg article is talking about how 649 00:27:45,359 --> 00:27:48,240 Speaker 1: many car washes are being opened and everywhere. Private equity 650 00:27:48,280 --> 00:27:50,840 Speaker 1: investors are in on the deal. One of my best 651 00:27:50,840 --> 00:27:52,800 Speaker 1: friends from childhood, mat his dad has had a car 652 00:27:52,920 --> 00:27:55,440 Speaker 1: wash for years, and I'm sure he's done quite well 653 00:27:55,480 --> 00:27:58,320 Speaker 1: with it because and then if you opt to sell it, man, 654 00:27:58,359 --> 00:27:59,720 Speaker 1: there's a lot of money in that game too. I 655 00:27:59,760 --> 00:28:02,600 Speaker 1: get it, But who's paying the price for that though, 656 00:28:02,640 --> 00:28:05,359 Speaker 1: who's making the private equity equity investors. Rich is the 657 00:28:05,400 --> 00:28:07,399 Speaker 1: people who have the thirty five dollars a month car 658 00:28:07,400 --> 00:28:10,399 Speaker 1: watch subscription and who aren't using it. Yeah, especially if 659 00:28:10,400 --> 00:28:11,920 Speaker 1: you're not using it. But if you go on twice 660 00:28:11,920 --> 00:28:13,960 Speaker 1: a month, I don't know. Maybe it's better to either 661 00:28:14,040 --> 00:28:16,280 Speaker 1: pay when you do go or wash your car home. 662 00:28:16,440 --> 00:28:19,160 Speaker 1: Just saying, but let's talk. Let's keep talking about cars 663 00:28:19,160 --> 00:28:22,160 Speaker 1: and subscriptions. There's one subscription that could end up potentially 664 00:28:22,200 --> 00:28:24,679 Speaker 1: saving you money, and that is if you opted for 665 00:28:24,760 --> 00:28:27,399 Speaker 1: a car subscription instead of owning an extra set of 666 00:28:27,400 --> 00:28:30,679 Speaker 1: expensive wheels or not, maybe subscribe and reduce your overall 667 00:28:30,760 --> 00:28:34,560 Speaker 1: cost of car ownership. Ownership of appreciating assets. We talked 668 00:28:34,560 --> 00:28:36,680 Speaker 1: about that that's a really good thing. When you own 669 00:28:36,840 --> 00:28:39,280 Speaker 1: assets that go up in value, this is wonderful. This 670 00:28:39,320 --> 00:28:41,400 Speaker 1: is increasing your net worth. But when you own assets 671 00:28:41,600 --> 00:28:45,880 Speaker 1: that depreciate regularly and substantially, that's another thing. And stats 672 00:28:45,880 --> 00:28:48,840 Speaker 1: find that we're only in our car driving between three 673 00:28:48,880 --> 00:28:50,480 Speaker 1: to five percent of the time. Anyway, most of the 674 00:28:50,520 --> 00:28:52,320 Speaker 1: time the car is sitting idle, whether it's in the 675 00:28:52,360 --> 00:28:55,200 Speaker 1: parking lot of work, whether it's in the driveway or 676 00:28:55,240 --> 00:28:57,560 Speaker 1: the parking lot of your apartment complex. Wherever it is right, 677 00:28:58,000 --> 00:29:00,920 Speaker 1: and work from home and hybrid work has reduced the 678 00:29:01,000 --> 00:29:03,400 Speaker 1: need for a lot of folks to constantly have access 679 00:29:03,440 --> 00:29:06,360 Speaker 1: to their own specific vehicle that they own that they're 680 00:29:06,360 --> 00:29:09,080 Speaker 1: in charge of. And there's startups like finn out of 681 00:29:09,120 --> 00:29:12,040 Speaker 1: Germany that are trying to normalize the car subscription model, 682 00:29:12,080 --> 00:29:14,840 Speaker 1: which includes the cost of insurance and repairs. I think 683 00:29:14,840 --> 00:29:16,680 Speaker 1: this is kind of cool, Matt, even though it might 684 00:29:16,680 --> 00:29:18,520 Speaker 1: not save everybody money, but it's at least something worth 685 00:29:18,520 --> 00:29:18,960 Speaker 1: looking into. 686 00:29:19,480 --> 00:29:22,080 Speaker 2: Yeah, yeah, I think what's great about this is that 687 00:29:22,920 --> 00:29:25,880 Speaker 2: we're trying to point folks to thinking about things that 688 00:29:25,920 --> 00:29:29,200 Speaker 2: traditionally might not be something that you'd be in favor of. 689 00:29:29,440 --> 00:29:31,200 Speaker 1: But it comes down to like what the numbers. Yeah, 690 00:29:31,240 --> 00:29:32,160 Speaker 1: but then you know, like crunch the. 691 00:29:32,160 --> 00:29:33,680 Speaker 2: Numbers, see if it makes sense for you, Because I 692 00:29:33,720 --> 00:29:37,240 Speaker 2: think they're talking about how it's technically it's more expensive 693 00:29:37,240 --> 00:29:40,000 Speaker 2: even than leasing a vehicle, but it also comes with 694 00:29:40,080 --> 00:29:43,440 Speaker 2: much much shorter subscription windows, so maybe subscribe for a 695 00:29:43,440 --> 00:29:45,560 Speaker 2: month and so yeah, like, technically it might be more expensive, 696 00:29:45,600 --> 00:29:47,160 Speaker 2: but if it's over a shorter period of time and 697 00:29:47,160 --> 00:29:49,040 Speaker 2: that means you're spending less money overall, well then it 698 00:29:49,080 --> 00:29:51,480 Speaker 2: could be a smart way of going about it, and 699 00:29:51,560 --> 00:29:54,760 Speaker 2: especially like they're trying to get folks to try out evs. 700 00:29:54,920 --> 00:29:58,200 Speaker 2: And I do like the idea of knowing what you're 701 00:29:58,200 --> 00:30:00,600 Speaker 2: getting into before you make a purchase. But that's also 702 00:30:00,640 --> 00:30:03,440 Speaker 2: something that you can do via something like Touro or 703 00:30:03,560 --> 00:30:05,240 Speaker 2: via a zip car. Like literally, Kate and I did 704 00:30:05,280 --> 00:30:07,240 Speaker 2: that out in Colorado last year. We rented a Tesla. 705 00:30:07,720 --> 00:30:09,880 Speaker 2: I was able to scratch my ev itch, get a 706 00:30:09,880 --> 00:30:12,680 Speaker 2: feel for it and avoided paying tons of money. And 707 00:30:12,680 --> 00:30:14,200 Speaker 2: I don't think I would have gone out and bought 708 00:30:14,240 --> 00:30:15,880 Speaker 2: a Tesla, but I was able to try that out 709 00:30:15,880 --> 00:30:16,960 Speaker 2: in I think a. 710 00:30:16,920 --> 00:30:18,000 Speaker 1: More affordable way. 711 00:30:18,400 --> 00:30:22,240 Speaker 2: But it's worth considering because we're not principally against something 712 00:30:22,320 --> 00:30:24,320 Speaker 2: like this. It comes down to how does it work 713 00:30:24,360 --> 00:30:26,280 Speaker 2: for you and how does it work out for your 714 00:30:26,280 --> 00:30:28,040 Speaker 2: personal financial situation. 715 00:30:28,160 --> 00:30:30,840 Speaker 1: Yeah, when you look at Finn's website, their most expensive 716 00:30:31,360 --> 00:30:33,400 Speaker 1: monthly model is twelve hundred bucks a month. That's a 717 00:30:33,440 --> 00:30:35,520 Speaker 1: lot of money for a car. Even though it includes 718 00:30:35,840 --> 00:30:39,520 Speaker 1: everything including insurance. That's still really expensive. And so I 719 00:30:39,560 --> 00:30:41,560 Speaker 1: think you're right. I think some of those pay by 720 00:30:41,600 --> 00:30:44,840 Speaker 1: the hour or pay by the day, car sharing services Toro, 721 00:30:45,080 --> 00:30:47,360 Speaker 1: zip car, those are worth looking into if they're in 722 00:30:47,400 --> 00:30:49,560 Speaker 1: your area. Turtos basically everywhere. Zip car is only a 723 00:30:49,680 --> 00:30:52,360 Speaker 1: certain locations, but yeah, or ride share. And I think 724 00:30:52,360 --> 00:30:54,240 Speaker 1: if you're able to ditch a car completely, if you 725 00:30:54,360 --> 00:30:56,320 Speaker 1: actually run the numbers and see how much your car 726 00:30:56,400 --> 00:30:59,080 Speaker 1: is costing you on an annual basis, and then so 727 00:30:59,200 --> 00:31:01,440 Speaker 1: much more. It could a forty dollars uber ride, But 728 00:31:01,520 --> 00:31:03,960 Speaker 1: ultimately that forty dollars uber ride could end up saving 729 00:31:03,960 --> 00:31:06,040 Speaker 1: you hundreds and hundreds of dollars a month, even though 730 00:31:06,080 --> 00:31:08,080 Speaker 1: it's a more expensive way of getting from one place 731 00:31:08,080 --> 00:31:10,400 Speaker 1: to another. Well, when you look at that overall perspective, 732 00:31:10,400 --> 00:31:13,040 Speaker 1: it could be saving you more. Dude, absolutely, But I 733 00:31:13,040 --> 00:31:14,160 Speaker 1: guess the other part of it too. 734 00:31:14,480 --> 00:31:17,680 Speaker 2: I just want to challenge folks to like think through 735 00:31:17,720 --> 00:31:19,360 Speaker 2: whether or not they truly need it, and to push 736 00:31:19,400 --> 00:31:22,320 Speaker 2: back on sort of the cultural expectation that we have 737 00:31:22,480 --> 00:31:26,080 Speaker 2: a vehicle. Like literally, yesterday I was running home, slash 738 00:31:26,160 --> 00:31:29,280 Speaker 2: running slash walking home from work. Started started to rain 739 00:31:29,360 --> 00:31:32,000 Speaker 2: a little bit, and dude, no fewer than three people 740 00:31:32,120 --> 00:31:34,680 Speaker 2: pulled over and were like, hey, do you need to ride? 741 00:31:35,160 --> 00:31:36,840 Speaker 2: There are folks we you know folks. I know you 742 00:31:36,880 --> 00:31:40,360 Speaker 2: should take rides with strangers always and I found it 743 00:31:40,400 --> 00:31:43,320 Speaker 2: to be incredibly well, it was amazing for a couple 744 00:31:43,320 --> 00:31:44,920 Speaker 2: of reasons. I guess, a, it's awesome that we live 745 00:31:44,920 --> 00:31:46,840 Speaker 2: in a community that were we you know, it's fun 746 00:31:46,840 --> 00:31:49,160 Speaker 2: to see neighbors taking care of other folks and checking 747 00:31:49,200 --> 00:31:50,080 Speaker 2: in stuff like that. 748 00:31:50,520 --> 00:31:52,080 Speaker 1: But I also wish that. 749 00:31:52,080 --> 00:31:55,000 Speaker 2: It wasn't such a rarity to see somebody out there 750 00:31:55,080 --> 00:31:58,040 Speaker 2: running home in the rain and I wasn't like, it's 751 00:31:58,040 --> 00:32:01,000 Speaker 2: not like I was like fleeing from my life, like smiling, 752 00:32:01,080 --> 00:32:03,760 Speaker 2: and it's just drizzling a little bit. And I wish 753 00:32:03,960 --> 00:32:06,720 Speaker 2: that wasn't such a rare site for folks to consider 754 00:32:06,960 --> 00:32:10,160 Speaker 2: walking home or riding their bike, because there are there's 755 00:32:10,200 --> 00:32:14,040 Speaker 2: a much larger possibility of folks doing that. Then I think, 756 00:32:14,040 --> 00:32:17,680 Speaker 2: what's what's normal in our culture today is is all? 757 00:32:18,040 --> 00:32:19,400 Speaker 1: I think. I think the amount of the number of 758 00:32:19,400 --> 00:32:21,200 Speaker 1: box the number of TVs, and the number of cars 759 00:32:21,200 --> 00:32:23,080 Speaker 1: that we own per household is overdone. And if you 760 00:32:23,080 --> 00:32:24,680 Speaker 1: can think about ways to reduce both those things in 761 00:32:24,720 --> 00:32:25,840 Speaker 1: your life, I think it's a good thing. I don't 762 00:32:25,840 --> 00:32:28,880 Speaker 1: know why I mentioned TV's there, but I guess it's just. 763 00:32:28,600 --> 00:32:30,920 Speaker 2: It seems like, yeah, it seems like another one of 764 00:32:30,960 --> 00:32:32,920 Speaker 2: those things that you just like, oh why not? They 765 00:32:32,960 --> 00:32:34,000 Speaker 2: certainly have gotten more and more. 766 00:32:34,040 --> 00:32:35,880 Speaker 1: Fores the norm. But the and the norm is to 767 00:32:35,880 --> 00:32:39,200 Speaker 1: have multiple cars like often often two or three in 768 00:32:39,240 --> 00:32:41,000 Speaker 1: the household r. I don't know what the average number 769 00:32:41,040 --> 00:32:43,520 Speaker 1: of cars that the average household has, but it's it's 770 00:32:43,720 --> 00:32:45,920 Speaker 1: more for a lot of households, at least, especially in 771 00:32:46,040 --> 00:32:48,160 Speaker 1: today's work climate. It's a lot easier than ditch your 772 00:32:48,200 --> 00:32:51,000 Speaker 1: car than ever before. Absolutely. Yeah, all right, Matt, that's 773 00:32:51,000 --> 00:32:53,480 Speaker 1: gonna do it for this Friday flight. Hope you have 774 00:32:53,600 --> 00:32:55,760 Speaker 1: a great weekend. And by the way, if you haven't 775 00:32:55,760 --> 00:32:57,840 Speaker 1: gone to how to money dot com recently, tons of 776 00:32:57,920 --> 00:33:00,320 Speaker 1: new money saving information there, be sure to check it 777 00:33:00,320 --> 00:33:02,240 Speaker 1: out and we'll see you back here on Monday. Matt. 778 00:33:02,320 --> 00:33:05,320 Speaker 1: Until next time, best friends Out, Best Friends Out.