WEBVTT 00:00:00.000 --> 00:00:02.480 Welcome to the Deep Dive. Today, we are pulling 00:00:02.480 --> 00:00:04.480 back the curtain on one of the most powerful 00:00:04.480 --> 00:00:07.559 yet often least understood corporations that 00:00:07.559 --> 00:00:11.080 governs modern American finance. Fair Isaac Corporation. 00:00:11.460 --> 00:00:13.320 Universally known, of course, by its acronym 00:00:13.320 --> 00:00:16.559 FICO. Right. And for most of us, FICO is just 00:00:16.559 --> 00:00:19.640 that three digit number, you know, a seemingly 00:00:19.640 --> 00:00:21.899 immutable fact that determines whether you get 00:00:21.899 --> 00:00:24.859 a mortgage. the rate on your next car loan, or 00:00:24.859 --> 00:00:26.839 even the deposit you need for your utilities. 00:00:27.079 --> 00:00:29.820 Exactly. But if you think FICO is simply a score, 00:00:30.179 --> 00:00:33.100 you are missing the forest for the tree. A very, 00:00:33.140 --> 00:00:36.119 very big forest. So our mission today is a deep 00:00:36.119 --> 00:00:39.030 dive into the source material. We have a detailed 00:00:39.030 --> 00:00:41.929 history, a corporate roadmap, and some really 00:00:41.929 --> 00:00:44.490 interesting legal analysis of FICO. We want to 00:00:44.490 --> 00:00:46.490 understand how an academic endeavor, a statistical 00:00:46.490 --> 00:00:49.329 model invented over half a century ago, transformed 00:00:49.329 --> 00:00:52.250 itself into a global data analytics powerhouse. 00:00:52.469 --> 00:00:55.210 And critically, why that near monopolistic market 00:00:55.210 --> 00:00:58.369 position is now facing some intense legal and 00:00:58.369 --> 00:01:00.689 regulatory scrutiny right here in the United 00:01:00.689 --> 00:01:02.649 States. We have to understand the company that 00:01:02.649 --> 00:01:04.849 owns the algorithm, not just the number the algorithm 00:01:04.849 --> 00:01:08.090 produces. And the high level facts alone really 00:01:08.090 --> 00:01:11.790 set the stage for this immense scale. FICO was 00:01:11.790 --> 00:01:14.670 founded way back in 1956. As Fair, Isaac and 00:01:14.670 --> 00:01:17.030 Company. Right. The brainchild of two men, Bill 00:01:17.030 --> 00:01:19.390 Fair, who was an engineer, and Earl Isaac, a 00:01:19.390 --> 00:01:22.849 mathematician. That marriage of engineering discipline 00:01:22.849 --> 00:01:25.890 and mathematical rigor is just the perfect origin 00:01:25.890 --> 00:01:28.560 story for an algorithmic company, isn't it? It 00:01:28.560 --> 00:01:31.000 really is. And the sheer scale of their penetration 00:01:31.000 --> 00:01:32.859 is the foundational challenge we're discussing. 00:01:33.060 --> 00:01:35.219 I mean, it is hard to wrap your head around the 00:01:35.219 --> 00:01:38.159 ubiquity of the system. We saw data showing that 00:01:38.159 --> 00:01:42.879 in 2013 alone, lenders purchased over 10 billion 00:01:42.879 --> 00:01:45.439 FICO scores? 10 billion. And that's not revenue. 00:01:45.500 --> 00:01:48.859 There's 10 billion specific instances where institutions 00:01:48.859 --> 00:01:51.840 relied on this one proprietary model to make 00:01:51.840 --> 00:01:54.239 a critical financial decision. In a single year. 00:01:54.480 --> 00:01:56.280 It just shows that FICO isn't merely a vendor. 00:01:56.359 --> 00:01:58.799 It's foundational infrastructure. It's the rails 00:01:58.799 --> 00:02:01.319 upon which vast amounts of global consumer finance 00:02:01.319 --> 00:02:04.219 run. And if those rails are proprietary and expensive, 00:02:04.459 --> 00:02:07.219 as plaintiffs are now alleging. then the entire 00:02:07.219 --> 00:02:09.879 economy feels that pinch. Okay, so let's unpack 00:02:09.879 --> 00:02:12.599 this history first and see how they went from 00:02:12.599 --> 00:02:15.860 two guys in California to a mandatory fixture 00:02:15.860 --> 00:02:19.139 in global finance. The story really begins in 00:02:19.139 --> 00:02:21.219 the cradle of what would become Silicon Valley. 00:02:21.800 --> 00:02:24.400 Bill Fair and Earl Isaac. They met while working 00:02:24.400 --> 00:02:26.639 at the Stanford Research Institute in Menlo Park, 00:02:26.800 --> 00:02:29.240 California. So the initial founding of Fair, 00:02:29.379 --> 00:02:32.360 Isaac & Company in 1956 was really rooted in 00:02:32.360 --> 00:02:34.659 this academic environment, applying statistical 00:02:34.659 --> 00:02:37.479 theory to a deeply subjective problem. And that's 00:02:37.479 --> 00:02:40.060 the crucial context. You have to remember, before 00:02:40.060 --> 00:02:43.060 the mid -1950s, lending decisions were almost 00:02:43.060 --> 00:02:45.659 entirely subjective. Right. A loan officer would 00:02:45.659 --> 00:02:47.819 look at your personal collateral, your reputation 00:02:47.819 --> 00:02:50.539 in town, maybe even arbitrary factors like your 00:02:50.539 --> 00:02:53.250 handshake. or the closey war. And make a human 00:02:53.250 --> 00:02:55.669 judgment call. It was subjective, it was slow, 00:02:55.870 --> 00:02:58.490 and it was inherently biased. And Fair and Isaac 00:02:58.490 --> 00:03:00.669 saw an inefficiency there that they believed 00:03:00.669 --> 00:03:03.110 mathematics could solve. Precisely. They were 00:03:03.110 --> 00:03:05.370 proposing to replace a subjective qualitative 00:03:05.370 --> 00:03:09.189 system with an objective quantitative one. And 00:03:09.189 --> 00:03:12.229 the transition from theory to product was pretty 00:03:12.229 --> 00:03:14.530 rapid for that era. Just two years, right? Just 00:03:14.530 --> 00:03:18.150 two years. In 1958, they sold their very first 00:03:18.479 --> 00:03:20.800 credit scoring system. And here's where we see 00:03:20.800 --> 00:03:23.099 their early strategic brilliance in market building. 00:03:23.379 --> 00:03:26.460 It wasn't enough to just invent the score. They 00:03:26.460 --> 00:03:28.939 had to convince a traditional skeptical industry 00:03:28.939 --> 00:03:32.159 to actually adopt it. And we know they proactively 00:03:32.159 --> 00:03:34.979 pitched their system to 50 American lenders. 00:03:35.060 --> 00:03:38.710 50. Right out of the gate. That effort was absolutely 00:03:38.710 --> 00:03:41.330 critical to establishing early market penetration. 00:03:41.610 --> 00:03:43.629 They weren't waiting for the market to discover 00:03:43.629 --> 00:03:45.750 them. They were selling the whole concept of 00:03:45.750 --> 00:03:48.289 statistical risk management. And by getting those 00:03:48.289 --> 00:03:50.990 initial 50 lenders on board, they were creating 00:03:50.990 --> 00:03:53.469 an early, powerful network effect. Of course, 00:03:53.590 --> 00:03:55.870 the more institutions that used it, the more 00:03:55.870 --> 00:03:58.110 standardized and valuable the data became for 00:03:58.110 --> 00:04:00.770 everyone else. So the company grew, validated 00:04:00.770 --> 00:04:02.949 by the success of these early models, and that 00:04:02.949 --> 00:04:05.990 leads to a major corporate step. They go public. 00:04:06.169 --> 00:04:09.349 FICO went public in July of 1987, listing on 00:04:09.349 --> 00:04:11.849 the New York Stock Exchange. That move provided 00:04:11.849 --> 00:04:14.069 the capital necessary for the huge expansion 00:04:14.069 --> 00:04:16.029 we're going to discuss later. But the score we 00:04:16.029 --> 00:04:18.589 know today, that universal number, that didn't 00:04:18.589 --> 00:04:21.310 debut until 1989. That's when the first general 00:04:21.310 --> 00:04:24.350 purpose FICO score hit the market. Exactly. This 00:04:24.350 --> 00:04:27.069 wasn't a specialized tool for one bank. It was 00:04:27.069 --> 00:04:29.449 designed to be used across a wide spectrum of 00:04:29.449 --> 00:04:31.889 consumer lending decisions, from credit cards 00:04:31.889 --> 00:04:35.019 to installment loans. It standardized the measurement 00:04:35.019 --> 00:04:37.439 of consumer credit risk using the credit report 00:04:37.439 --> 00:04:39.740 data that was available at that time. Let's just 00:04:39.740 --> 00:04:42.129 clarify the foundation of that standard. The 00:04:42.129 --> 00:04:46.470 base FICO score ranges from 300 to 850. And we 00:04:46.470 --> 00:04:48.490 bring this up not because the number itself is 00:04:48.490 --> 00:04:51.569 surprising, but because that specific range represents 00:04:51.569 --> 00:04:54.290 the fundamental proprietary intellectual property 00:04:54.290 --> 00:04:57.410 that FICO built its empire on. An objective gauge 00:04:57.410 --> 00:05:00.009 of a potential borrower's creditworthiness. But 00:05:00.009 --> 00:05:02.649 for FICO to become an empire, it needed a massive, 00:05:02.709 --> 00:05:05.430 decisive victory. It needed a moment where it 00:05:05.430 --> 00:05:07.949 transitioned from being one option to being the 00:05:07.949 --> 00:05:10.370 standard. And that moment arrived with a mortgage 00:05:10.370 --> 00:05:13.170 market milestone. in 1995. Okay. What stands 00:05:13.170 --> 00:05:16.029 out here is that 1995 wasn't just another product 00:05:16.029 --> 00:05:18.389 update. This was a regulatory and industry -wide 00:05:18.389 --> 00:05:21.170 endorsement. What were the specific actions that 00:05:21.170 --> 00:05:23.870 Fannie Mae and Freddie Mac took? So Fannie Mae 00:05:23.870 --> 00:05:26.829 and Freddie Mac, these two massive government 00:05:26.829 --> 00:05:29.670 -sponsored enterprises or GSEs that are just 00:05:29.670 --> 00:05:31.970 essential cogs in the U .S. housing machine, 00:05:32.149 --> 00:05:35.189 they began using FICO scores to help determine 00:05:35.189 --> 00:05:37.509 which American consumers qualified for mortgages. 00:05:37.870 --> 00:05:40.189 They didn't just use them, they effectively mandated 00:05:40.189 --> 00:05:42.910 them, right? By only buying up mortgages that 00:05:42.910 --> 00:05:46.329 use the FICO score as a qualifying factor. That's 00:05:46.329 --> 00:05:48.850 the key. Let's unpack the seismic effect of that 00:05:48.850 --> 00:05:51.569 decision. This wasn't simply one large lender 00:05:51.569 --> 00:05:54.290 adopting the score, because Fannie and Freddie 00:05:54.290 --> 00:05:57.250 purchased the vast majority of mortgages to stabilize 00:05:57.250 --> 00:05:59.750 the housing market. Their decision effectively 00:05:59.750 --> 00:06:03.310 made the FICO score mandatory for any conventional 00:06:03.310 --> 00:06:06.040 loan in the United States. Precisely. Before 00:06:06.040 --> 00:06:09.879 1995, FICO was excellent. After 1995, it became 00:06:09.879 --> 00:06:12.600 entrenched and really non -negotiable infrastructure. 00:06:12.980 --> 00:06:14.560 If you wanted to participate in the conventional 00:06:14.560 --> 00:06:17.060 mortgage market, you had to use the FICO score, 00:06:17.180 --> 00:06:20.120 period. This move granted the Fair Isaac Corporation 00:06:20.120 --> 00:06:23.379 immense self -reinforcing market power, and it 00:06:23.379 --> 00:06:25.199 provides the foundation for the monopolistic 00:06:25.199 --> 00:06:27.540 challenges we're discussing today. So in less 00:06:27.540 --> 00:06:30.259 than 40 years, a statistical model designed in 00:06:30.259 --> 00:06:32.519 a research institute went from being a hard sell 00:06:32.519 --> 00:06:35.680 to 50 lenders to being the definitive mandatory 00:06:35.680 --> 00:06:38.240 requirement for the most significant debt most 00:06:38.240 --> 00:06:40.439 Americans will ever undertake. That's a staggering 00:06:40.439 --> 00:06:44.040 pace of standardization. The 1995 milestone changed 00:06:44.040 --> 00:06:46.480 everything, and it really kicked off a massive 00:06:46.480 --> 00:06:48.899 strategic evolution for the company. It did. 00:06:49.060 --> 00:06:52.160 We need to remember that FICO is legally the 00:06:52.160 --> 00:06:54.920 Fair Isaac Corporation. a name they adopted in 00:06:54.920 --> 00:06:58.319 2003, moving away from the original fair Isaac 00:06:58.319 --> 00:07:00.300 and Company. And this was far more than just 00:07:00.300 --> 00:07:03.480 a simple corporate rebrand. Oh, absolutely. It 00:07:03.480 --> 00:07:06.439 signaled a strategic shift away from being perceived 00:07:06.439 --> 00:07:09.339 as merely a credit score generator towards what 00:07:09.339 --> 00:07:12.660 they truly became. a comprehensive data analytics 00:07:12.660 --> 00:07:14.720 and enterprise software company. They were no 00:07:14.720 --> 00:07:16.800 longer just defining risk. They were selling 00:07:16.800 --> 00:07:19.660 the tools to manage and mitigate that risk across 00:07:19.660 --> 00:07:22.220 the entire financial spectrum. And we can trace 00:07:22.220 --> 00:07:24.959 this corporate identity shift quite clearly by 00:07:24.959 --> 00:07:26.620 just looking at the journey of their headquarters. 00:07:27.019 --> 00:07:29.800 It's actually a fascinating map of changing priorities 00:07:29.800 --> 00:07:31.939 and leadership philosophies. They didn't just 00:07:31.939 --> 00:07:35.279 settle down. They actively moved to follow perceived 00:07:35.279 --> 00:07:37.939 strategic advantages. That's a great way to put 00:07:37.939 --> 00:07:40.180 it. I find this trajectory incredibly inspiring. 00:07:40.170 --> 00:07:42.990 They started in San Rafael, California, you know, 00:07:42.990 --> 00:07:46.230 close to their academic roots. But then in 2004, 00:07:46.449 --> 00:07:49.649 after Thomas Grudnowski became CEO, they made 00:07:49.649 --> 00:07:52.709 a significant strategic pivot and moved the headquarters 00:07:52.709 --> 00:07:55.920 all the way to Minneapolis, Minnesota. And that 00:07:55.920 --> 00:07:58.459 move is really telling. Minneapolis is a major 00:07:58.459 --> 00:08:01.079 center for financial services, particularly in 00:08:01.079 --> 00:08:03.959 retail banking and payments processing. So moving 00:08:03.959 --> 00:08:06.860 there suggested a strategy focused on being physically 00:08:06.860 --> 00:08:09.120 close to the operational hubs of their primary 00:08:09.120 --> 00:08:11.180 customers. They were centering on the business 00:08:11.180 --> 00:08:14.560 of lending. Exactly. But the pendulum swung back. 00:08:15.019 --> 00:08:17.660 When William Lansing joined as CEO, they moved 00:08:17.660 --> 00:08:19.600 the headquarters back to California to San Jose 00:08:19.600 --> 00:08:22.560 in 2013. That move just screams, we are a tech 00:08:22.560 --> 00:08:24.959 company first. It's a return to the talent pool 00:08:24.959 --> 00:08:27.459 and the innovative ethos of Silicon Valley. It 00:08:27.459 --> 00:08:29.740 suggests a renewed focus on platform development, 00:08:30.000 --> 00:08:33.200 algorithm optimization, all the tech buzzwords. 00:08:33.460 --> 00:08:35.159 And then we get to the current, and I have to 00:08:35.159 --> 00:08:36.960 say, somewhat surprising headquarters location, 00:08:37.360 --> 00:08:40.019 Bozeman, Montana. Right. They established an 00:08:40.019 --> 00:08:42.779 office there in 2016 and eventually designated 00:08:42.779 --> 00:08:45.460 it as their corporate headquarters. This signals 00:08:45.460 --> 00:08:47.820 perhaps a shift toward operational efficiency, 00:08:48.220 --> 00:08:50.919 lower overhead. And maybe a decentralized model, 00:08:51.059 --> 00:08:53.360 leveraging remote talent while still maintaining 00:08:53.360 --> 00:08:55.620 these big engineering and sales hubs in places 00:08:55.620 --> 00:08:57.919 like San Jose and Minnesota. It's a company that 00:08:57.919 --> 00:09:00.860 is actively optimizing itself, always looking 00:09:00.860 --> 00:09:03.340 for the next strategic advantage. That dynamic 00:09:03.340 --> 00:09:06.059 movement of the HQ illustrates a company that 00:09:06.059 --> 00:09:09.320 refuses to be static. But the real evidence of 00:09:09.320 --> 00:09:11.779 their transformation into a data analytics giant 00:09:11.779 --> 00:09:15.759 lies in their acquisition strategy. Yes. It shows 00:09:15.759 --> 00:09:18.700 a deliberate, almost military -like effort to 00:09:18.700 --> 00:09:20.840 cover every single aspect of the credit lifecycle. 00:09:21.340 --> 00:09:23.480 Analyzing the long list of acquisitions from 00:09:23.480 --> 00:09:26.419 1992 through 2019 is like reading a strategic 00:09:26.419 --> 00:09:29.059 blueprint. It really is. Their early moves were 00:09:29.059 --> 00:09:31.259 about bolstering their core risk management offerings, 00:09:31.500 --> 00:09:33.840 making their scores more robust. For instance, 00:09:34.019 --> 00:09:35.840 the acquisitions of risk management technologies 00:09:35.840 --> 00:09:38.769 and prevision in 1997. That signaled an early 00:09:38.769 --> 00:09:41.149 understanding that simply providing a number 00:09:41.149 --> 00:09:43.929 wasn't enough. They needed to provide the software 00:09:43.929 --> 00:09:46.110 and the analysis tools for lenders to integrate 00:09:46.110 --> 00:09:48.250 that number into their day to day operations. 00:09:48.409 --> 00:09:51.610 Right. But the major transformative shift, the 00:09:51.610 --> 00:09:53.590 one that truly changed FICO's identity forever. 00:09:54.039 --> 00:09:56.919 was the acquisition of HNC Software in 2002. 00:09:57.220 --> 00:09:59.360 This was not a small tweak. This was an earthquake. 00:09:59.679 --> 00:10:02.539 HNC was a leader in real -time transaction monitoring 00:10:02.539 --> 00:10:05.100 and fraud detection. And that acquisition was 00:10:05.100 --> 00:10:08.299 a competitive moat. Before HNC, FICA was focused 00:10:08.299 --> 00:10:11.820 on assessing creditworthiness. After HNC, they 00:10:11.820 --> 00:10:13.980 could offer institutions a whole suite of tools 00:10:13.980 --> 00:10:17.129 that fought fraud in real time. Why is that so 00:10:17.129 --> 00:10:19.210 critical? Because preventing a billion dollars 00:10:19.210 --> 00:10:21.889 in credit card fraud is far more valuable to 00:10:21.889 --> 00:10:24.250 a bank than predicting who might default on a 00:10:24.250 --> 00:10:27.370 $10 ,000 loan. It instantly justified higher 00:10:27.370 --> 00:10:29.409 enterprise pricing. And it created a dependency 00:10:29.409 --> 00:10:31.950 on FICO for institutional security, not just 00:10:31.950 --> 00:10:34.769 consumer risk. Exactly. But they didn't stop 00:10:34.769 --> 00:10:37.389 there. They diversified into the full lifecycle 00:10:37.389 --> 00:10:40.269 of debt management. We see moves into optimization, 00:10:40.570 --> 00:10:44.039 like acquiring Dash Optimization in 2008. Which 00:10:44.039 --> 00:10:46.320 focuses on improving business decision making 00:10:46.320 --> 00:10:48.899 speed through prescriptive analytics and then 00:10:48.899 --> 00:10:52.700 tackling the back end. That's the flip side of 00:10:52.700 --> 00:10:55.919 lending risk. In 2012, they acquired CR Software, 00:10:56.179 --> 00:10:58.600 which specializes in collections and receivable 00:10:58.600 --> 00:11:01.399 software. So FICO started by predicting who would 00:11:01.399 --> 00:11:03.919 pay, and now they own the tools to chase down 00:11:03.919 --> 00:11:06.100 payments from those who didn't. They effectively 00:11:06.100 --> 00:11:08.899 became indispensable partners, covering both 00:11:08.899 --> 00:11:11.419 the front -end risk assessment and the back -end 00:11:11.419 --> 00:11:13.840 recovery. And the push into future data architecture 00:11:13.840 --> 00:11:17.279 is so evident with Carmosphere. In 2014, they 00:11:17.279 --> 00:11:19.860 acquired Carmosphere, which specialized in big 00:11:19.860 --> 00:11:22.299 data analytics for Hadoop. Okay, for the listener 00:11:22.299 --> 00:11:24.480 who might not be familiar with the jargon, Hadoop 00:11:24.480 --> 00:11:26.879 is an open -source framework designed to store 00:11:26.879 --> 00:11:30.320 and process extremely large, complex, and unstructured 00:11:30.320 --> 00:11:32.919 datasets. The kind of data that goes far beyond 00:11:32.919 --> 00:11:35.779 a traditional credit report. Exactly. This acquisition 00:11:35.779 --> 00:11:39.210 shows FICO anticipating the future. It signaled 00:11:39.210 --> 00:11:41.389 their ability to move beyond analyzing structured 00:11:41.389 --> 00:11:44.450 credit files and into the realm of unstructured, 00:11:44.529 --> 00:11:47.549 massive data streams. Positioning them to analyze 00:11:47.549 --> 00:11:50.549 consumer behavior and enterprise risk using next 00:11:50.549 --> 00:11:53.389 generation tools. This cemented the change to 00:11:53.389 --> 00:11:55.889 Fair Isaac Corporation. They became a vendor 00:11:55.889 --> 00:11:58.779 of high -end analytical infrastructure. And finally, 00:11:58.879 --> 00:12:01.480 the aggressive move into anti -financial crime 00:12:01.480 --> 00:12:03.940 and security. Right. They acquired Tonbeller 00:12:03.940 --> 00:12:07.519 AG in 2015, specializing in anti -money laundering 00:12:07.519 --> 00:12:10.960 and compliance, then Quadmetrics in 2016. Which 00:12:10.960 --> 00:12:13.179 allowed them to offer an enterprise security 00:12:13.179 --> 00:12:16.059 score for organizations, essentially a corporate 00:12:16.059 --> 00:12:19.159 credit score for cybersecurity risk. And EZMcom 00:12:19.159 --> 00:12:23.220 in 2019. So you are precisely right. FICO is 00:12:23.220 --> 00:12:25.240 no longer just the company providing a number 00:12:25.240 --> 00:12:28.700 between 300 and 850. They are a multibillion 00:12:28.700 --> 00:12:31.279 -dollar enterprise software vendor involved in 00:12:31.279 --> 00:12:33.980 fraud detection, collections, optimization, compliance, 00:12:34.360 --> 00:12:36.820 and institutional security scoring. Their business 00:12:36.820 --> 00:12:39.139 model is entirely integrated into the global 00:12:39.139 --> 00:12:41.320 financial infrastructure. Completely. Before 00:12:41.320 --> 00:12:43.480 we move on to scale and the current legal battles, 00:12:43.659 --> 00:12:45.779 let's quickly revisit the scores themselves because 00:12:45.779 --> 00:12:48.139 FICO's complexity is also evident in its product 00:12:48.139 --> 00:12:50.629 layering. Right. We talked about the base FICO 00:12:50.629 --> 00:12:52.909 score, 300 to 850, which is a general purpose 00:12:52.909 --> 00:12:55.429 measure. But the source material highlights the 00:12:55.429 --> 00:12:57.950 existence and purpose of industry -specific scores. 00:12:58.250 --> 00:13:01.190 And these have a different higher range, 250 00:13:01.190 --> 00:13:04.129 to 900. That's right. So why does that range 00:13:04.129 --> 00:13:06.750 expand and why do these specific scores even 00:13:06.750 --> 00:13:10.970 exist? It's all about predictive tuning. An industry 00:13:10.970 --> 00:13:14.070 -specific score is tuned to be more predictive 00:13:14.070 --> 00:13:17.009 of risk within that particular vertical. For 00:13:17.009 --> 00:13:19.740 example, a FICO auto score. Is customized to 00:13:19.740 --> 00:13:21.860 predict the likelihood of defaulting on an auto 00:13:21.860 --> 00:13:24.559 loan? Exactly. It might weigh timely payment 00:13:24.559 --> 00:13:26.779 of previous auto loans or the utilization rate 00:13:26.779 --> 00:13:28.700 on credit cards differently than a standard mortgage 00:13:28.700 --> 00:13:31.879 score would. So the 250 to 900 range doesn't 00:13:31.879 --> 00:13:33.940 necessarily mean the consumer has better credit. 00:13:34.039 --> 00:13:36.659 It just means the model is calibrated for a narrower, 00:13:36.720 --> 00:13:39.730 more specialized risk profile. That's it. And 00:13:39.730 --> 00:13:42.710 by offering these tailored scores, FICO can maximize 00:13:42.710 --> 00:13:44.809 its revenue by selling multiple products to the 00:13:44.809 --> 00:13:47.169 same lender, asserting its specialized expertise 00:13:47.169 --> 00:13:49.889 across different lending departments. It's brilliant 00:13:49.889 --> 00:13:52.450 product segmentation that further locks in their 00:13:52.450 --> 00:13:55.710 position as the authoritative provider of risk 00:13:55.710 --> 00:13:59.129 metrics for virtually any lending scenario. So 00:13:59.129 --> 00:14:01.830 now we connect that deep history and strategic 00:14:01.830 --> 00:14:05.850 evolution to FICO's current market reality. The 00:14:05.850 --> 00:14:08.690 scale is... Well, it's almost unbelievable. We 00:14:08.690 --> 00:14:10.929 already established the 10 billion scores purchased 00:14:10.929 --> 00:14:13.990 by lenders in 2013, which shows that institutional 00:14:13.990 --> 00:14:17.049 reliance. But the score has also become essential 00:14:17.049 --> 00:14:20.450 to individual consumers. Yes. The sheer volume 00:14:20.450 --> 00:14:23.570 of consumer engagement is astonishing. In that 00:14:23.570 --> 00:14:27.240 same year, 2013. 30 million American consumers 00:14:27.240 --> 00:14:29.980 access their scores themselves. 30 million. That 00:14:29.980 --> 00:14:32.000 shows a huge transition in consumer behavior. 00:14:32.299 --> 00:14:34.460 It's no longer just a metric used against you. 00:14:34.519 --> 00:14:36.820 It's a vital tool for personal financial planning 00:14:36.820 --> 00:14:39.179 and negotiation. And the market dominance becomes 00:14:39.179 --> 00:14:41.080 crystalline when you consider the distribution 00:14:41.080 --> 00:14:44.019 network. For the listener, the three major U 00:14:44.019 --> 00:14:46.860 .S. credit bureaus are Equifax, Experian, and 00:14:46.860 --> 00:14:49.340 TransUnion. And FICO scores are available through 00:14:49.340 --> 00:14:51.759 all three of them. That ubiquity is non -negotiable 00:14:51.759 --> 00:14:54.659 for standardization. If a lender pulls a report 00:14:54.659 --> 00:14:57.460 from Experian, they expect to see the FICO score 00:14:57.460 --> 00:14:59.559 as the gold standard of risk measurement. But 00:14:59.559 --> 00:15:02.120 the source material also mentions FICO's availability 00:15:02.120 --> 00:15:04.399 through the fourth U .S. Credit Reporting Bureau, 00:15:04.580 --> 00:15:08.509 PRBC. And that detail is important. PRBC stands 00:15:08.509 --> 00:15:12.029 for Pay Rent Build Credit. It focuses on including 00:15:12.029 --> 00:15:15.210 non -traditional credit data, like rent and utility 00:15:15.210 --> 00:15:17.629 payments. The fact that FICO scores are available 00:15:17.629 --> 00:15:20.809 through PRBC shows their ability to integrate 00:15:20.809 --> 00:15:24.309 into new, evolving data streams designed to serve 00:15:24.309 --> 00:15:27.029 potentially credit -thin populations. It proves 00:15:27.029 --> 00:15:29.129 that FICO is not beholden only to the established 00:15:29.129 --> 00:15:31.970 Big Three. They maintain universal access across 00:15:31.970 --> 00:15:34.610 the spectrum of data providers. This is strategic 00:15:34.610 --> 00:15:37.210 ubiquity, ensuring that almost every significant 00:15:37.210 --> 00:15:39.389 credit decision in the U .S. relies on their 00:15:39.389 --> 00:15:41.409 intellectual property. But their reach extends 00:15:41.409 --> 00:15:43.549 far beyond the domestic market. I mean, we are 00:15:43.549 --> 00:15:46.169 talking about a true global data analytics firm. 00:15:46.389 --> 00:15:48.649 Indeed. The source material underscores their 00:15:48.649 --> 00:15:51.110 substantial global footprint, providing scores 00:15:51.110 --> 00:15:53.350 and analytical services in major international 00:15:53.350 --> 00:15:56.070 markets. Including neighboring economies like 00:15:56.070 --> 00:15:58.590 Mexico and Canada, where they hold significant 00:15:58.590 --> 00:16:01.289 market share. The global operational footprint 00:16:01.289 --> 00:16:04.070 listed in the sources is truly impressive and 00:16:04.070 --> 00:16:06.990 illustrates the scope of their ambition. International 00:16:06.990 --> 00:16:09.750 locations in major economies like Australia, 00:16:10.029 --> 00:16:13.809 Brazil, China, Germany, India, Italy, Japan, 00:16:14.269 --> 00:16:16.850 the UK. And they even maintain a presence in 00:16:16.850 --> 00:16:19.769 smaller specialized markets like Lithuania, Poland, 00:16:19.909 --> 00:16:22.710 and South Africa. This global presence serves 00:16:22.710 --> 00:16:26.429 multiple strategic purposes. It diversifies their 00:16:26.429 --> 00:16:29.029 risk exposure away from any single regulatory 00:16:29.029 --> 00:16:31.649 body, which is particularly relevant given their 00:16:31.649 --> 00:16:33.809 domestic antitrust challenges. And second, for 00:16:33.809 --> 00:16:36.230 multinational banks, having a single familiar 00:16:36.230 --> 00:16:38.889 and objective risk management vendor that operates 00:16:38.889 --> 00:16:41.750 seamlessly across diverse regulatory environments 00:16:41.750 --> 00:16:44.309 is an enormous advantage. They're exporting the 00:16:44.309 --> 00:16:46.990 concept of data driven statistical credit worthiness 00:16:46.990 --> 00:16:48.950 worldwide. That's exactly what they're doing. 00:16:49.049 --> 00:16:51.210 And that global scale and proprietary product 00:16:51.210 --> 00:16:53.769 suite translate directly into immense financial 00:16:53.769 --> 00:16:56.519 power. Looking at recent financial data based 00:16:56.519 --> 00:17:00.039 on 2025 SEC filings, we can establish FICO's 00:17:00.039 --> 00:17:02.059 current market capitalization and profitability. 00:17:02.440 --> 00:17:04.940 The revenue figures are striking. They reported 00:17:04.940 --> 00:17:10.740 revenue of $1 .99 billion. Nearly $2 billion 00:17:10.740 --> 00:17:13.539 generated from algorithms, software, and data 00:17:13.539 --> 00:17:16.160 analytics. It's a testament to the high value 00:17:16.160 --> 00:17:18.259 the financial industry places on their proprietary 00:17:18.259 --> 00:17:20.819 risk models. But what really hammers home the 00:17:20.819 --> 00:17:23.380 efficiency and the market power is the margin. 00:17:23.559 --> 00:17:27.740 The operating income was $925 million. And net 00:17:27.740 --> 00:17:30.779 income stood at $652 million, a nearly billion 00:17:30.779 --> 00:17:33.559 -dollar operating profit from $2 billion in revenue. 00:17:33.819 --> 00:17:35.940 That's the kind of margin you see when you sell 00:17:35.940 --> 00:17:37.980 proprietary... intellectual property with very 00:17:37.980 --> 00:17:40.200 low marginal costs. The infrastructure is built, 00:17:40.279 --> 00:17:42.299 the data feeds are running, and the algorithms 00:17:42.299 --> 00:17:45.079 are operating. Every subsequent score they sell 00:17:45.079 --> 00:17:48.099 is almost pure profit. And they manage this operation 00:17:48.099 --> 00:17:52.279 with just 3 ,811 employees. Their status as an 00:17:52.279 --> 00:17:56.200 S &P 500 component, traded as NYSE. FICO just 00:17:56.200 --> 00:17:57.819 solidifies their position as one of the most 00:17:57.819 --> 00:18:00.059 essential and profitable financial technology 00:18:00.059 --> 00:18:02.240 giants in the world. So when you look at that 00:18:02.240 --> 00:18:04.400 level of financial dominance and market saturation, 00:18:04.960 --> 00:18:06.880 The $10 billion score is the near billion -dollar 00:18:06.880 --> 00:18:10.480 operating income. It becomes obvious why FICO's 00:18:10.480 --> 00:18:12.960 dominant position would attract intense scrutiny. 00:18:13.220 --> 00:18:15.960 Which leads us directly into the modern challenges 00:18:15.960 --> 00:18:19.059 they face. The story of FICO in the 21st century 00:18:19.059 --> 00:18:21.720 is increasingly defined by the legal pushback 00:18:21.720 --> 00:18:24.220 against its market power. And the key distinction 00:18:24.220 --> 00:18:26.259 we have to make here is that the controversy 00:18:26.259 --> 00:18:29.339 isn't about whether the score is accurate. No, 00:18:29.339 --> 00:18:32.180 it's about whether FICO is using its infrastructural 00:18:32.180 --> 00:18:35.400 status. That national standardization solidified 00:18:35.400 --> 00:18:39.500 back in 1995 to charge excessive prices and stifle 00:18:39.500 --> 00:18:41.859 competitors. And the U .S. Department of Justice, 00:18:42.039 --> 00:18:44.559 the DOJ, has certainly been involved. We saw 00:18:44.559 --> 00:18:46.859 the initial rumblings of an antitrust investigation 00:18:46.859 --> 00:18:49.619 opened in March of 2020. Which was eventually 00:18:49.619 --> 00:18:51.700 reported as closed later that year in December 00:18:51.700 --> 00:18:54.829 2020. But the concern, especially among political 00:18:54.829 --> 00:18:56.950 leaders, it never really went away. We saw a 00:18:56.950 --> 00:18:58.769 high profile resurgence of political pressure 00:18:58.769 --> 00:19:01.750 much more recently in March 2024. Right. When 00:19:01.750 --> 00:19:03.990 U .S. Senator Josh Hawley publicly urged the 00:19:03.990 --> 00:19:06.529 DOJ to open a new investigation into the Fair 00:19:06.529 --> 00:19:09.410 Isaac Corporation. The political allegation didn't 00:19:09.410 --> 00:19:11.950 mince words. The senator specifically stated 00:19:11.950 --> 00:19:14.970 that FICO appears to be using its monopolistic 00:19:14.970 --> 00:19:17.849 power over the credit scoring market to increase 00:19:17.849 --> 00:19:21.109 costs for mortgage lenders. And that claim is 00:19:21.109 --> 00:19:23.569 important because it directly targets the heart 00:19:23.569 --> 00:19:27.490 of FICO's power, the 1995 standardization by 00:19:27.490 --> 00:19:30.029 Fannie and Freddie. It's the foundation. Since 00:19:30.029 --> 00:19:33.049 lenders must use FICO to sell conventional mortgages, 00:19:33.250 --> 00:19:36.109 they are, in the senator's view, captive customers. 00:19:36.430 --> 00:19:38.809 And the allegation is that FICO is exploiting 00:19:38.809 --> 00:19:41.410 that mandatory infrastructure role to continuously 00:19:41.410 --> 00:19:43.509 raise the cost of participating in the housing 00:19:43.509 --> 00:19:46.119 market. But the core fight, it's not happening 00:19:46.119 --> 00:19:48.240 in Washington. It's happening in courtrooms across 00:19:48.240 --> 00:19:50.400 the country through these business to business 00:19:50.400 --> 00:19:52.859 lawsuits. Yes. We're talking about a flood of 00:19:52.859 --> 00:19:55.200 class action lawsuits. At least 10 were filed 00:19:55.200 --> 00:19:58.579 between 2020 and 2023. And the plaintiffs are 00:19:58.579 --> 00:20:00.990 FICO's direct customers. This is the ultimate 00:20:00.990 --> 00:20:03.410 confrontation between FICO and the institutions 00:20:03.410 --> 00:20:05.890 it serves. The plaintiffs are credit unions, 00:20:06.210 --> 00:20:08.450 major banks, regional mortgage lenders, real 00:20:08.450 --> 00:20:11.150 estate brokerages, even auto dealers. These are 00:20:11.150 --> 00:20:13.130 the institutions whose business models require 00:20:13.130 --> 00:20:16.109 them to purchase FICO scores hundreds, thousands 00:20:16.109 --> 00:20:19.150 or even millions of times a year. So what exactly 00:20:19.150 --> 00:20:22.210 are these lenders alleging in detail? It's not 00:20:22.210 --> 00:20:24.809 just about high prices, is it? It's about the 00:20:24.809 --> 00:20:28.130 mechanisms FICO allegedly uses to maintain that 00:20:28.130 --> 00:20:30.490 monopoly. That's the crux of the legal argument. 00:20:31.109 --> 00:20:33.890 The plaintiffs claim FICO maintains monopoly 00:20:33.890 --> 00:20:36.789 power through a series of anti -competitive agreements 00:20:36.789 --> 00:20:39.650 and business practices. And one of the central 00:20:39.650 --> 00:20:42.049 claims revolves around alleged tying agreements. 00:20:42.490 --> 00:20:44.930 OK, let's define a tying agreement in this context. 00:20:45.210 --> 00:20:48.160 So a tying arrangement is where a seller. Who 00:20:48.160 --> 00:20:50.779 has a monopoly in one market, the tying product, 00:20:51.000 --> 00:20:53.619 which here's the mandatory FICO score used for 00:20:53.619 --> 00:20:56.279 mortgages. Right. forces customers to also buy 00:20:56.279 --> 00:20:59.140 a separate product or service, the tied product. 00:20:59.359 --> 00:21:01.359 Which might be other FICO analytics software, 00:21:01.680 --> 00:21:04.680 fraud tools, or consulting services? Exactly. 00:21:04.859 --> 00:21:06.920 They make it a condition of obtaining the product 00:21:06.920 --> 00:21:09.940 you have to buy. So the allegation is that FICO 00:21:09.940 --> 00:21:12.259 is leveraging the one product lenders must buy 00:21:12.259 --> 00:21:15.180 the score to coerce them into buying the other, 00:21:15.220 --> 00:21:17.299 more lucrative analytical products we discussed 00:21:17.299 --> 00:21:19.859 earlier. The anti -fraud software, the collection 00:21:19.859 --> 00:21:23.680 software? Yes. This creates a powerful competitive 00:21:23.680 --> 00:21:27.220 moat. How so? Well, if a competitor develops 00:21:27.220 --> 00:21:30.259 a better collection software or a more accurate 00:21:30.259 --> 00:21:32.960 specialized auto score, lenders may still be 00:21:32.960 --> 00:21:35.660 hesitant to adopt it. Because FICO could potentially 00:21:35.660 --> 00:21:38.480 retaliate by raising the price or restricting 00:21:38.480 --> 00:21:40.940 access to the mandatory base FICO mortgage score? 00:21:41.180 --> 00:21:43.650 It's a network of alleged dependencies. So the 00:21:43.650 --> 00:21:45.730 lenders aren't just complaining about the cost 00:21:45.730 --> 00:21:47.730 of the score itself, but about the structure 00:21:47.730 --> 00:21:50.750 of the contracts, which they claim mandate purchasing 00:21:50.750 --> 00:21:53.710 a broader suite of FICO products. And that they 00:21:53.710 --> 00:21:56.150 charge artificially inflated prices for these 00:21:56.150 --> 00:21:58.329 captive products. That's the financial core of 00:21:58.329 --> 00:22:00.869 the lawsuit. The lenders argue that they are 00:22:00.869 --> 00:22:03.730 essentially paying a monopoly tax a premium because 00:22:03.730 --> 00:22:06.069 they have no viable alternative, particularly 00:22:06.069 --> 00:22:09.089 when dealing with GSE backed mortgages. And this, 00:22:09.190 --> 00:22:12.349 the plaintiffs argue, hurts competition and raises 00:22:12.349 --> 00:22:14.950 the cost of credit throughout the entire financial 00:22:14.950 --> 00:22:17.990 ecosystem. But surely the lenders knew the cost 00:22:17.990 --> 00:22:20.309 of standardization when they signed on in 1995. 00:22:20.970 --> 00:22:24.150 Is this really an antitrust issue or is it just 00:22:24.150 --> 00:22:26.829 buyer's remorse now that FICO has become so successful 00:22:26.829 --> 00:22:28.970 and its prices have gone up? Well, that is the 00:22:28.970 --> 00:22:30.890 central question the court will have to wrestle 00:22:30.890 --> 00:22:34.009 with. FICO's defense is that they're being competitively 00:22:34.009 --> 00:22:37.089 smart and innovative and that their pricing reflects 00:22:37.089 --> 00:22:39.990 the value of their proprietary intellectual property. 00:22:40.460 --> 00:22:42.859 But the plaintiffs successfully argued that FICO 00:22:42.859 --> 00:22:45.779 is exploiting a regulatory mandate, that 1995 00:22:45.779 --> 00:22:48.900 Fannie Freddie decision, which they claim eliminates 00:22:48.900 --> 00:22:51.900 any true price competition. And the biggest validation 00:22:51.900 --> 00:22:54.319 of the seriousness of these claims came in September 00:22:54.319 --> 00:22:57.259 2023. This was the moment the legal challenge 00:22:57.259 --> 00:22:59.740 received its judicial green light. Tell us about 00:22:59.740 --> 00:23:01.799 that. Yes. U .S. District Judge Edmund Chang 00:23:01.799 --> 00:23:04.400 delivered a really critical ruling. He stated 00:23:04.400 --> 00:23:06.119 that the plaintiffs had presented enough evidence 00:23:06.119 --> 00:23:08.940 that FICO had violated antitrust law to allow 00:23:08.940 --> 00:23:11.259 the lawsuits to proceed to discovery and trial. 00:23:11.460 --> 00:23:14.740 That ruling is seismic. It means these claims 00:23:14.740 --> 00:23:17.559 are not just political posturing or idle complaints. 00:23:17.720 --> 00:23:20.180 They are recognized by the judiciary as having 00:23:20.180 --> 00:23:23.319 sufficient factual basis to challenge FICO's 00:23:23.319 --> 00:23:26.160 fundamental business model under U .S. antitrust 00:23:26.160 --> 00:23:28.289 law. The judge essentially acknowledged that 00:23:28.289 --> 00:23:30.529 the plaintiffs had plausible arguments that FICO 00:23:30.529 --> 00:23:32.809 was exploiting its government -mandated status 00:23:32.809 --> 00:23:35.950 as the national standard. It means the company 00:23:35.950 --> 00:23:38.950 founded on statistical objectivity must now subject 00:23:38.950 --> 00:23:41.549 its business structure and proprietary algorithms 00:23:41.549 --> 00:23:44.190 to the intense scrutiny of a major antitrust 00:23:44.190 --> 00:23:46.279 trial. The financial industry is essentially 00:23:46.279 --> 00:23:48.740 challenging the terms of its own dependency on 00:23:48.740 --> 00:23:51.339 the Fair Isaac Corporation. It truly is the ultimate 00:23:51.339 --> 00:23:53.720 test of whether total market domination achieved 00:23:53.720 --> 00:23:56.200 through standardization and strategic acquisition 00:23:56.200 --> 00:23:59.539 is defensible under modern competition statutes. 00:23:59.700 --> 00:24:01.559 So this deep dive has really shown us how the 00:24:01.559 --> 00:24:03.940 Fair Isaac Corporation became the invisible engine 00:24:03.940 --> 00:24:06.440 of global consumer finance. We began with two 00:24:06.440 --> 00:24:08.779 men at the Stanford Research Institute inventing 00:24:08.779 --> 00:24:11.039 a concept of objective credit risk measurement 00:24:11.039 --> 00:24:15.160 way back in 1956. And that concept was cemented 00:24:15.160 --> 00:24:17.180 as the national standard for the U .S. mortgage 00:24:17.180 --> 00:24:21.440 market in 1995. Then, through massive strategic 00:24:21.440 --> 00:24:24.920 acquisition, FICO transformed itself from a specialized 00:24:24.920 --> 00:24:27.920 credit score provider into a multifaceted software 00:24:27.920 --> 00:24:30.500 and data analytics corporation. Generating nearly 00:24:30.500 --> 00:24:34.799 $2 billion in revenue by 2025. Today, FICO is 00:24:34.799 --> 00:24:37.170 a global data behemoth. providing the metrics 00:24:37.170 --> 00:24:40.109 for risk management, fraud detection and optimization 00:24:40.109 --> 00:24:42.829 across countless industries worldwide. Yet that 00:24:42.829 --> 00:24:45.789 very success has created intense scrutiny, culminating 00:24:45.789 --> 00:24:48.470 in political demands for investigation. And more 00:24:48.470 --> 00:24:51.470 importantly, these high stakes class action lawsuits 00:24:51.470 --> 00:24:54.190 from the very banks and lenders who depend on 00:24:54.190 --> 00:24:56.609 its core product. And they're alleging monopolistic 00:24:56.609 --> 00:24:58.750 pricing and anti -competitive tying agreements. 00:24:58.990 --> 00:25:01.109 The discussion boils down to this fundamental 00:25:01.109 --> 00:25:03.829 tension, the efficiency provided by standardization 00:25:03.829 --> 00:25:11.180 versus the costs and potential. FICO built the 00:25:11.180 --> 00:25:13.319 engine, and now the users of that engine are 00:25:13.319 --> 00:25:15.769 fighting over the price of the oil. So what does 00:25:15.769 --> 00:25:18.349 this all mean for you, the listener? We know 00:25:18.349 --> 00:25:20.970 that your personal FICO score, ranging from 300 00:25:20.970 --> 00:25:24.529 to 850, is based on your credit reports and was 00:25:24.529 --> 00:25:26.789 established as the national standard for mortgages 00:25:26.789 --> 00:25:30.150 back in 1995. But think back to that long list 00:25:30.150 --> 00:25:32.329 of acquisitions we meticulously went through. 00:25:32.509 --> 00:25:35.609 Fraud detection, security scoring, optimization, 00:25:36.150 --> 00:25:40.079 compliance, collection software. Right. Considering 00:25:40.079 --> 00:25:42.599 that FICO has aggressively moved into every corner 00:25:42.599 --> 00:25:44.799 of institutional risk management and big data 00:25:44.799 --> 00:25:47.380 infrastructure, the final provocative thought 00:25:47.380 --> 00:25:50.440 we want to leave you with is this. Given FICO's 00:25:50.440 --> 00:25:52.599 immense profitability and proprietary control 00:25:52.599 --> 00:25:55.160 over these key software tools, how much more 00:25:55.160 --> 00:25:57.259 of the modern financial and transactional ecosystem, 00:25:57.640 --> 00:26:00.099 from preventing corporate fraud to optimizing 00:26:00.099 --> 00:26:02.579 collections on credit cards, is now silently 00:26:02.579 --> 00:26:05.500 governed and influenced by the powerful yet invisible 00:26:05.500 --> 00:26:08.549 algorithms of the Fair Isaac Corporation? They 00:26:08.549 --> 00:26:10.450 aren't just scoring credit anymore. They are 00:26:10.450 --> 00:26:12.950 managing risk, fighting fraud, and defining the 00:26:12.950 --> 00:26:14.789 rules of engagement across the entire financial 00:26:14.789 --> 00:26:17.490 world. Something to mull over the next time you 00:26:17.490 --> 00:26:19.730 see that three -digit number. Thank you for joining 00:26:19.730 --> 00:26:21.089 the Deep Dive. We'll catch you next time.