1 00:00:08.040 --> 00:00:12.510 Thank you guys so much for joining us today and today I am excited to talk to 2 00:00:12.510 --> 00:00:15.550 this specific individual that is right here because we're gonna be talking about 3 00:00:15.550 --> 00:00:19.270 an important topic in the M C A industry and it's about fraud. 4 00:00:19.930 --> 00:00:23.030 So my special guest, Joyce, I know who you are, 5 00:00:23.030 --> 00:00:26.150 we've talked for the last couple of months, but please introduce yourself, 6 00:00:26.250 --> 00:00:28.350 the company that you're with and your title. 7 00:00:29.190 --> 00:00:30.950 Absolutely. So my name is Joyce Arnolds. 8 00:00:31.070 --> 00:00:34.030 I am an account executive with Thomson Reuters. Um, 9 00:00:34.190 --> 00:00:38.630 I work with financial institutions for their risk fraud 10 00:00:38.630 --> 00:00:42.790 underwriting collections. Really anything around public records, 11 00:00:43.090 --> 00:00:45.110 due diligence and background investigations. 12 00:00:45.760 --> 00:00:49.510 Joyce application fraud is something that many people are saying is a massive 13 00:00:49.680 --> 00:00:51.030 issue in the MCA space. 14 00:00:51.290 --> 00:00:56.030 So what is one common denominator between application fraud and the MCA space? 15 00:00:56.510 --> 00:00:59.990 I think really what it comes down to, to be really blunt about it, 16 00:01:00.770 --> 00:01:05.110 is a lack of tools and quite frankly, 17 00:01:05.730 --> 00:01:07.470 unpreparedness. Um, 18 00:01:07.490 --> 00:01:12.190 if you have at your fingertips information that can tell you the entire 19 00:01:12.210 --> 00:01:15.390 public record background on an individual in their business, 20 00:01:15.680 --> 00:01:19.550 their related parties, you can reduce your risk. 21 00:01:19.620 --> 00:01:22.910 Generally speaking specifically as it relates to fraud, 22 00:01:22.910 --> 00:01:26.910 there are a few different points that do come up. There's obviously ID fraud, 23 00:01:27.330 --> 00:01:31.150 you know, fake IDs being presented and with those fake IDs, 24 00:01:31.150 --> 00:01:34.150 they're collected but sometimes not looked at. Um, 25 00:01:34.150 --> 00:01:38.190 the other piece is fraud as it relates to the financial statements that are 26 00:01:38.190 --> 00:01:42.910 being provided. They can be altered, they could be, um, you know, 27 00:01:42.910 --> 00:01:44.150 real statements that are altered. 28 00:01:44.150 --> 00:01:47.710 They could be totally fake fabricated statements. Um, 29 00:01:47.730 --> 00:01:51.190 so depending on the eye that's looking at it, you may pick up on that. 30 00:01:51.370 --> 00:01:54.870 You may not, you may take it at face value, you may not. Um, 31 00:01:54.870 --> 00:01:59.750 but there are certainly tools to help you decipher if this is real, 32 00:01:59.750 --> 00:02:03.470 legitimate or fake doctored. Um, 33 00:02:03.470 --> 00:02:06.390 so I think if you don't use the tools, you would miss that. Um, 34 00:02:06.390 --> 00:02:08.550 so that's what I mean by unpreparedness. Um, 35 00:02:08.570 --> 00:02:12.510 and then the other piece that would be a huge risk when it comes to fraud would 36 00:02:12.510 --> 00:02:13.510 be synthetic identity. 37 00:02:14.050 --> 00:02:17.910 So clear offers different things like preventing and investigating and 38 00:02:17.910 --> 00:02:18.743 detecting. 39 00:02:18.810 --> 00:02:22.430 So when it comes to like the fundamentals and someone is trying to apply, 40 00:02:22.760 --> 00:02:25.470 could someone strictly based on application, 41 00:02:25.490 --> 00:02:27.830 on credit report or bank statements, 42 00:02:28.330 --> 00:02:32.750 So a credit report is going to tell you trade details, it's gonna tell you, 43 00:02:32.970 --> 00:02:36.750 you know, years of business, it's gonna tell you, um, 44 00:02:36.940 --> 00:02:38.150 default essentially. 45 00:02:38.370 --> 00:02:42.870 But what you're not going to know is information related to character. Um, 46 00:02:42.870 --> 00:02:47.230 information specifically related to criminal records. But MCA is for sure, 47 00:02:47.490 --> 00:02:51.950 we look at financials, we look at, um, credit reports, 48 00:02:52.610 --> 00:02:55.910 and we're good if they're a small enough shop in either of those areas. 49 00:02:56.650 --> 00:03:01.180 And the answer to that is always tell me how would you know 50 00:03:01.370 --> 00:03:06.020 from those sources whether or not this person has committed white collar crime? 51 00:03:07.970 --> 00:03:08.940 It's tough. Yeah. 52 00:03:08.960 --> 00:03:12.820 You wouldn't know that from a credit report or financial statements. Um, 53 00:03:13.250 --> 00:03:17.420 that right there gives a bit of an eye opener. Mm-hmm. There's more to know. 54 00:03:18.120 --> 00:03:20.620 So how useful is that information, 55 00:03:20.620 --> 00:03:25.060 like when you have a credit report and are you saying that, uh, you know, 56 00:03:25.560 --> 00:03:30.500 the applicants, uh, are trying to defraud or trick lenders in the MCA space? 57 00:03:30.510 --> 00:03:32.900 Could they do it? Like, let, let's talk a little bit about that. 58 00:03:33.880 --> 00:03:36.020 Um, could they do it? Sure. Certainly they, 59 00:03:36.160 --> 00:03:40.900 anyone could purport to be a part of a legitimate 60 00:03:41.300 --> 00:03:44.900 business that they have no part in. They can say, you know, 61 00:03:45.200 --> 00:03:49.860 I'm John Smith with John's lumberyard in Topeka, Kansas, 62 00:03:50.560 --> 00:03:53.860 and you maybe in Brooklyn or Miami, 63 00:03:54.400 --> 00:03:59.020 you have no way to know whether or not this is John Smith of John's Lumber, 64 00:03:59.440 --> 00:04:03.380 but he's providing you with information that would give you the impression that 65 00:04:03.380 --> 00:04:06.260 he is this person. You know, looking into, 66 00:04:07.950 --> 00:04:11.140 there are ways that you can't avoid fraud completely, 67 00:04:11.240 --> 00:04:14.940 but if you do look at IDs to see if they're fake or not, 68 00:04:15.080 --> 00:04:17.740 if you are looking at someone's criminal background, 69 00:04:17.740 --> 00:04:22.460 if you're looking at phone numbers that are being provided or used to, um, 70 00:04:22.520 --> 00:04:26.140 engage with you, um, in order to execute a deal, 71 00:04:26.480 --> 00:04:30.460 you can see whether or not that phone number by looking at public records is 72 00:04:30.780 --> 00:04:34.940 actually anything to do with that. John Smith, with John's lumberyard. 73 00:04:36.000 --> 00:04:40.820 And how prevalent is this currently in, in the state of the MCA space? 74 00:04:41.230 --> 00:04:43.300 Fraud in general? Yeah, I mean, 75 00:04:43.300 --> 00:04:47.460 fraud is rampant right now across industries if it's financial institutions and, 76 00:04:47.760 --> 00:04:48.310 you know, 77 00:04:48.310 --> 00:04:52.580 banks and credit unions are seeing a huge uptick in what's called suspicious 78 00:04:53.020 --> 00:04:55.460 activity reports. And essentially that is, you know, 79 00:04:55.460 --> 00:05:00.020 there's an indication on their account transaction history in most cases that 80 00:05:00.020 --> 00:05:03.780 there is, um, either money laundering happening, there's fraud being attempted, 81 00:05:03.780 --> 00:05:07.380 there's something off and they're investigating and then these suspicious 82 00:05:07.780 --> 00:05:11.020 activity reports are filed. There is an uptick in that right now, 83 00:05:11.030 --> 00:05:14.180 which surprised someone that I spoke with at the Laskey Bank event that I went 84 00:05:14.180 --> 00:05:17.300 to in the MCA space. Like, are banks experiencing this too? 85 00:05:17.330 --> 00:05:21.540 Like banks are NCAs are eCommerce's 86 00:05:22.090 --> 00:05:26.500 insurance companies are being defrauded. That's not new, 87 00:05:27.320 --> 00:05:31.460 but it is increasing. Um, and what does that stem from? It stems from, you know, 88 00:05:31.460 --> 00:05:34.020 financial insecurity. Uh, the, 89 00:05:34.130 --> 00:05:37.060 there's more information out there than ever before. 90 00:05:37.120 --> 00:05:39.380 So people are using it for bad. 91 00:05:39.730 --> 00:05:43.460 Yeah. And how sophisticated are fraudsters becoming nowadays? 92 00:05:44.400 --> 00:05:47.980 Um, some of the ploys that are being, you know, done, 93 00:05:47.980 --> 00:05:49.380 they are not more sophisticated. 94 00:05:49.970 --> 00:05:54.700 They're just doing it at a huge volume because there is automation not only on 95 00:05:54.700 --> 00:05:55.540 the underwriting space, 96 00:05:55.600 --> 00:05:59.900 but there's also automation in what they're doing if it's IRS is calling and 97 00:05:59.900 --> 00:06:02.980 they need the information that you need to provide right now on, you know, 98 00:06:02.980 --> 00:06:04.100 phone calls to consumers. 99 00:06:04.360 --> 00:06:08.940 But this is happening equally where there are shops attempting to de fraud all 100 00:06:08.940 --> 00:06:10.540 types of people, including NCAs. 101 00:06:10.920 --> 00:06:14.500 And when it comes to, uh, common types of fraud, 102 00:06:15.410 --> 00:06:17.380 what types of fraud have you seen? 103 00:06:18.200 --> 00:06:22.980 So what I hear from customers and prospects as to why they're either using us or 104 00:06:23.050 --> 00:06:24.340 they are talking with us, 105 00:06:25.130 --> 00:06:29.580 it's typically not enough information in terms of public records and, 106 00:06:29.920 --> 00:06:33.380 uh, they never knew what they didn't know. They weren't looking for it. Um, 107 00:06:33.380 --> 00:06:36.620 another piece is fake IDs. Big, big, big, big, 108 00:06:36.640 --> 00:06:39.940 big on fake IDs and there's a lot that can be done to prevent that type of 109 00:06:39.940 --> 00:06:42.900 fraud. Um, and you know, 110 00:06:42.900 --> 00:06:47.700 the synthetic identity piece of just like fake information being or, 111 00:06:47.700 --> 00:06:51.540 or real information being used by not the people purporting to be them. 112 00:06:51.760 --> 00:06:53.540 And then it's, you know, 113 00:06:53.840 --> 00:06:58.300 how high a bar of entry is there with your merchant cash advance, 114 00:06:58.960 --> 00:07:00.940 um, outfit to, you know, 115 00:07:00.960 --> 00:07:04.620 are you looking to see if financial statements are fraudulent or not? 116 00:07:05.200 --> 00:07:06.580 Are you know, being doctored? 117 00:07:06.800 --> 00:07:11.220 Are you even doing anything with IDs to see if they're fake? You know, 118 00:07:11.300 --> 00:07:15.460 there's the technology out there to do multi-point inspections, 119 00:07:15.840 --> 00:07:18.700 see the IP address where it's coming from. Is it coming from Senegal, 120 00:07:18.720 --> 00:07:19.900 is it coming from the us? 121 00:07:20.170 --> 00:07:22.660 Does it match where this person says that they're located? 122 00:07:23.190 --> 00:07:26.420 Along with all sorts of, you know, points to see is it a blurred image? 123 00:07:26.440 --> 00:07:31.380 Is it information we've seen before that's been used to defraud someone? Um, 124 00:07:31.380 --> 00:07:35.140 and if you're not looking, you're just leaving yourself open. 125 00:07:35.530 --> 00:07:40.260 Have you ever heard of some crazy unexpected situation when an 126 00:07:40.560 --> 00:07:41.700 MCA uh, 127 00:07:41.700 --> 00:07:45.780 company ends up running a background check and finds out something unexpected 128 00:07:45.910 --> 00:07:48.780 about the person? Something like an unsolved mystery. 129 00:07:49.460 --> 00:07:51.140 I wish it was really that interesting. 130 00:07:51.340 --> 00:07:54.300 I wish I was coming across unsolved murders left and right. 131 00:07:54.850 --> 00:07:58.660 More what it is is when I start working with someone who hasn't been using or 132 00:07:58.720 --> 00:08:02.660 has been using information that might be stale data in the system they're using, 133 00:08:03.240 --> 00:08:07.860 not as relevant when they do take a look, um, at, you know, 134 00:08:07.880 --> 00:08:10.660 up to date current public record information or adverse media, 135 00:08:11.690 --> 00:08:15.100 they'll see things that they didn't know by just looking at financials or 136 00:08:15.100 --> 00:08:16.580 looking at the data they had been looking at. 137 00:08:16.580 --> 00:08:19.380 And I have an example where we signed up an mca, 138 00:08:19.610 --> 00:08:22.940 they hadn't really been using anything, maybe Google and really with Google, 139 00:08:23.080 --> 00:08:27.780 you don't know if that's from yesterday or if that's from two years ago 140 00:08:27.960 --> 00:08:32.260 to know if that person is alive, dead new criminal records. 141 00:08:32.260 --> 00:08:36.380 You're not aware of licensed discipline, like professional licensed discipline. 142 00:08:36.380 --> 00:08:38.300 Wouldn't you like to know? Um, 143 00:08:38.440 --> 00:08:41.460 and there was an example where someone was looked up and there were battering 144 00:08:41.460 --> 00:08:42.293 abuse charges. 145 00:08:42.610 --> 00:08:45.860 I've seen where there are sex offender records with more people in this industry 146 00:08:45.890 --> 00:08:48.260 care about than I would've expected, but they do. 147 00:08:48.520 --> 00:08:50.700 So it says that CLEAR could be used for aml. 148 00:08:51.000 --> 00:08:52.380 So when it comes to money laundering, 149 00:08:52.380 --> 00:08:56.020 what are some signs of money laundering and uh, 150 00:08:56.040 --> 00:08:58.060 how does one even check for something like that? 151 00:08:58.530 --> 00:08:59.500 Yeah, good question. 152 00:08:59.680 --> 00:09:03.620 So this comes up a lot in the banking industry because there are regulatory 153 00:09:03.620 --> 00:09:08.460 requirements to look into and identify signs of money laundering, you know, 154 00:09:08.460 --> 00:09:12.460 someone taking dirty money and trying to make it clean and sort of pass it 155 00:09:12.460 --> 00:09:16.540 through and all of that. Um, but at the end of the day, 156 00:09:16.540 --> 00:09:21.420 what people in the MCA space I think care about just as much as a banking, uh, 157 00:09:21.420 --> 00:09:24.420 compliance person investigating financial crime and, 158 00:09:24.520 --> 00:09:25.980 and money laundering and you know, 159 00:09:26.180 --> 00:09:30.940 fighting money laundering is looking for bad actors and what you're not gonna 160 00:09:30.940 --> 00:09:34.300 find on a credit report or you're not gonna find with the traditional looking at 161 00:09:34.350 --> 00:09:38.300 financials that an MCA would have at their fingertips with an application 162 00:09:38.300 --> 00:09:39.620 packet, um, 163 00:09:39.640 --> 00:09:43.900 is seeing who is around the business and what businesses are related. 164 00:09:44.040 --> 00:09:48.580 So the associations of bad actors or even just potential risk 165 00:09:48.580 --> 00:09:51.100 underwriting risk, but fraud, certainly. 166 00:09:51.710 --> 00:09:52.080 Joyce, 167 00:09:52.080 --> 00:09:56.740 do you think fraudsters will eventually use things like chat G P T and AI to 168 00:09:56.740 --> 00:09:57.620 commit their crime? 169 00:09:58.140 --> 00:10:01.180 I think the big thing with that whole topic is it's Pandora's box. 170 00:10:01.240 --> 00:10:04.540 We really don't know all of the potential of what's out there. 171 00:10:04.570 --> 00:10:08.100 It's kind of like, Ooh, what do you think this could do if you could, you know, 172 00:10:08.460 --> 00:10:12.140 generate a knowledgeable response to a question essentially. 173 00:10:12.920 --> 00:10:17.620 And certainly to gather information and make use of it that's sort of 174 00:10:17.720 --> 00:10:22.420 out there with a question by a fraudster is powerful. I mean, 175 00:10:22.610 --> 00:10:27.220 they just, like, I can go in and any MCA could say, you know, 176 00:10:27.220 --> 00:10:30.780 what's really good marketing campaign to discuss my product, 177 00:10:31.760 --> 00:10:34.460 you're going to get a response for how to really, you know, 178 00:10:34.570 --> 00:10:39.140 discuss something to a certain audience and it's sophisticated and it's quick. 179 00:10:39.520 --> 00:10:44.060 So in the same way a fraudster can learn so much 180 00:10:44.060 --> 00:10:48.340 information in such short time to game a system. 181 00:10:48.980 --> 00:10:51.900 Absolutely. So there's more on the rise for sure. 182 00:10:52.760 --> 00:10:56.380 So is there anything else you want to say, anything you know, you, 183 00:10:56.440 --> 00:11:00.260 you think should be said regarding this specific topic and the MCA space? 184 00:11:01.200 --> 00:11:05.940 Asking trusted advisors the questions and having tools at your 185 00:11:05.940 --> 00:11:08.140 fingertips? That's what I would say. 186 00:11:08.460 --> 00:11:11.940 I also definitely advocate for talking amongst your peers in this industry 187 00:11:11.940 --> 00:11:13.460 because with experience, 188 00:11:14.120 --> 00:11:19.060 you've become sharper and sharper and sharper because the risk is out 189 00:11:19.060 --> 00:11:23.500 there. If it's underwriting risk or in this case fraud. And from experience, 190 00:11:23.720 --> 00:11:25.100 you really do learn a great deal, 191 00:11:25.480 --> 00:11:30.420 but you can also shave off a lot of time by learning from people 192 00:11:30.420 --> 00:11:33.140 who are exposed to what everyone's facing. 193 00:11:33.550 --> 00:11:36.900 Joyce, thank you so much for joining us today and bringing us this wealth of 194 00:11:36.900 --> 00:11:39.740 information because I know that it is not only helpful for me, 195 00:11:40.000 --> 00:11:41.300 but also to the people watching. 196 00:11:41.600 --> 00:11:44.380 Oh, you're welcome. Thank you so much for the opportunity. Thank 197 00:11:44.380 --> 00:11:44.500 You.