Credit scores are a big deal in the modern world, especially in America. Here, banks, car dealerships, and others will literally judge you as a person based on your credit score. If you have a low score, then you are obviously bad, regardless of your situation. If you have a high one, then you are obviously good, regardless of your current habits. But it is actually far crazier than that. If you actually are a responsible person and pay off your debts, your score can actually go down. Yes, you read that right. Paying off your debts will actually make your credit score go down. This actually leads to the concept of the ‘credit building loan’. In this perverse concept, a person actually goes in debt to build a better credit score. Yes, this is completely nuts. It also keeps people in what amounts to financial slavery.
Think about it. If you want to buy a car, you first have to go into debt for something else in order to get your score high enough to buy the car. Then the debt for the car helps you get your score high enough to go into even more debt for a house. If you want to go to college, or help your kids to go, you have to have a certain amount of debt in order to get any sort assistance. If you’ve been responsible and paid them off, you’ll be expected to shell out for college in cash. To put it simply, our current financial system encourages and rewards people for being in debt. Which, again, is insane. If the above isn’t enough to convince you, the word ‘mortgage’ comes from the Latin for ‘death grip’. Let that one sink in.
Credit scores as they have been traditionally calculated rely on limited data, focused only on past behaviors. Now though, more data than ever is available and it is being used in new ways to calculate your ability to pay off a loan. Rather than just aggregating how often you pay off revolving debt, credit companies can now look at how fast you drive, how much money gets spent how often and where. They can even see where and when you take vacations. All of that behavior can be analyzed for risk in near real time.
This marriage between big data and big credit can be beneficial in a number of ways. First, since the data is more recent, it is easier to track changes in behavior that indicate more or less risky behavior. If someone who has been at risk in the past suddenly finds a new job and starts paying an electric bill, while also cancelling their cable bill the chances of getting a desired loan go up. Rather than it taking a year to build up a credit score based on the changed behaviors, the increase in responsible behavior can be noticed right away. Similarly, if a person who has been responsibly paying off cards and loans for years suddenly starts going to the casino, the dealership has some reason to hold back on that new car loan.
It becomes easier to take extenuating circumstances into account as well. If someone suddenly has trouble making a payment because of a recent job loss or divorce, that can be weighed against other data to see if it reflects a temporary circumstance or a real shift towards irresponsible behavior. That kind of information may not matter in regards to a new loan but can still apply when trying to rent a new apartment.
Isn’t it a little scary though that the credit score companies can access all that data about you? A little, though in this case it’s easy to see how it can actually be used to benefit the company and you. However, if you are still uneasy about that, we don’t blame you. In that case, we recommend that you sign up with TARTLE and synch your various accounts. That will allow you to take back control of your data and only let even the credit score companies see it as you see fit. And when you do choose to share it, you can actually get paid for it.
What’s your data worth?
redit scores are a big deal in the modern world, especially in America. Here, banks, car dealerships, and others will literally judge you as a person based on your credit score. If you have a low score, then you are obviously bad, regardless of your situation. If you have a high one, then you are obviously good, regardless of your current habits.
Jason Rigby (00:00):
I'm ready now.
Automated (00:16):
Welcome to Tartle Cast with your hosts, Alexander McCaig and Jason Rigby.
Alexander McCaig (00:22):
Yes, we're the hosts. [crosstalk 00:00:25] Thank you for introducing us. Who is this lady?
Jason Rigby (00:30):
I don't know, I don't know. She's always bringing us in.
Alexander McCaig (00:33):
Bringing us in. She's always bringing us in. What a nice lady. And you know what? She never complains. Nothing. She just reads the same intro.
Jason Rigby (00:42):
When I was a little kid, there was a hymn that we used to sing and it was-
Alexander McCaig (00:45):
Like a Bible hymn?
Jason Rigby (00:46):
Yeah. It was "bring them in, bring them in..."
Alexander McCaig (00:52):
That's what I was going to say, the hymn that [crosstalk 00:00:54].
Jason Rigby (00:54):
Yeah. It's so funny how a lot of people don't understand, but a lot of the hymns were written with battle type, marching type, da-ta-da, da-ta-da.
Alexander McCaig (01:04):
They were probably perfect for the Crusades.
Jason Rigby (01:06):
Yes.
Alexander McCaig (01:06):
And probably even more perfect for the children's crusade. Let's talk about how insane that is, you know?
Jason Rigby (01:12):
Yeah. We won't go there.
Alexander McCaig (01:13):
And then you've got the deeper, more orchestra ones for the Spanish Inquisition.
Jason Rigby (01:18):
Before we get into this article, I'm going to go macro with this.
Alexander McCaig (01:20):
Oh, I like macro. I'm drinking my green tea.
Jason Rigby (01:22):
Yeah, he's got some super green juice.
Alexander McCaig (01:24):
It's a CHO.
Jason Rigby (01:25):
Speaking of macro and craziness, let's get into being judged off of a person with your credit score.
Alexander McCaig (01:33):
Oh, my God.
Jason Rigby (01:34):
What is this credit score? Only in America would we do this.
Alexander McCaig (01:37):
And here's what's ridiculous about credit scores. If you're a good person and you pay off some sort of revolving credit, your score goes down. What?
Jason Rigby (01:51):
I don't understand their algorithm.
Alexander McCaig (01:53):
It's designed to keep people in a financial form of slavery.
Jason Rigby (02:01):
Yes.
Alexander McCaig (02:01):
Where it gives you this false sort of benefit. They're like, "You need to take on more credit because it keeps pumping your score up."
Jason Rigby (02:07):
Yeah. Don't you want to go buy a new car? Or you know what's the best thing you can do is get into a mortgage.
Alexander McCaig (02:13):
Yeah. You get into a mortgage, and the word mortgage is Latin. It means death grip.
Jason Rigby (02:17):
It's true. Look it up.
Alexander McCaig (02:19):
Think twice about that.
Jason Rigby (02:20):
When you first told me that, I looked it up and it's true.
Alexander McCaig (02:22):
I know, of course it is. I'm not going to-
Jason Rigby (02:23):
I had to fact-check you.
Alexander McCaig (02:24):
You think I want to lie? There's a reason for me to lie. But the thought about this is that credit in general, the idea is that they want to have you in a revolving system of control. But here's the interesting part. Everybody wants to get their hands on credit. You know, 32% of the world that has the availability of data to actually get underwritten, they're trying to become a part of the system for some sort of financial gain by essentially efficiently leveraging their money in a debt-to-income ratio so that they can expand their lives, and hopefully begin to pay back on that. Because they've taken out money, they've gotten credit so that they can put it towards things that give them a gain so they can pay that credit off and then live a better lifestyle.
Alexander McCaig (03:11):
But as you begin to pay those things off, the current credit score system says, "Oh, your score is going to drop. You're actually less worthy now." They want you to continue to open it up and stay inside of that credit system once you're in it. And they think that applying a score to it judges the person on the quality and the integrity of them paying back and them being truthful.
Alexander McCaig (03:30):
But now that what we're seeing is that there's a big change with big data, is that people all over the globe that never had access to credit, that were essentially red light from it, only specific socioeconomic groups could afford to have credit or allowed to get it, now with the data that we're creating, you can start to underwrite people on information that was albeit abstract before, but now because we're recording it, it can be analyzed and put into some sort of actuary table to define what the risk of that person might be.
Jason Rigby (04:03):
Yeah, and of course, Experian, TransUnion, and Equifax, all three of them are going to make sure that they're compiling mass amounts of data on you to understand, to get that score or to... I mean, they're selling products and services, too.
Alexander McCaig (04:22):
Yeah, they're selling a credit score.
Jason Rigby (04:23):
Yeah.
Alexander McCaig (04:24):
That's what their job is.
Jason Rigby (04:27):
They're also selling data. They're selling your data. People don't realize that they're selling your data to third parties.
Alexander McCaig (04:31):
Yeah, they sell credit ratings. These are the same guys that said during the 2008, 2009 stock market crash, that the mortgage bonds were rated at whatever. You dopes! Anyway, just like any sort of credit scoring system, it's really been, to put it lightly, just bullshit.
Jason Rigby (04:54):
Yes.
Alexander McCaig (04:54):
It's been a bad system.
Jason Rigby (04:56):
Yes.
Alexander McCaig (04:56):
It's prevented people from having certain forms of economic opportunity, and it's only left it out to a few. But now through big data, they have the ability to take in a huge new body of inputs, data inputs, that will help indicate towards credit worthiness and they can test and retest those inputs. So maybe they think the way someone drives a car is going to determine how well they pay back on something.
Jason Rigby (05:20):
Well, I mean, it could be this way. For instance, especially when you think of an automobile, you could say Capital One is probably one of the biggest banks for auto loans.
Alexander McCaig (05:29):
Yes.
Jason Rigby (05:30):
They could look at it and say, "Well, they may be a 640, but the last three auto loans that they've had, they don't pay their other bills, but they pay their auto loans on time." So the risk factor of that is looking at it and saying, "Well, since they've done three autos that well, even though they have a lower score, we'll go ahead and approve them at a lower rate because we know they'll make that payment."
Alexander McCaig (05:52):
Yeah. Because on the automobile side of things, that's more important for them to focus on it.
Jason Rigby (05:56):
Yes, yeah.
Alexander McCaig (05:56):
They find value in paying that off because they need that sort of transportation.
Jason Rigby (05:59):
And that's a simplistic way of looking at it. But these banks are dependent upon... When you go apply for a mortgage, what are they going to do? They're going to pull all three. They're going to pull from Experian, Equifax, and TransUnion.
Alexander McCaig (06:13):
Yeah, because each one of them has a different way of defining the quality of you. And guess what?
Jason Rigby (06:19):
That sounds so bad.
Alexander McCaig (06:20):
You never had any say in the matter.
Jason Rigby (06:22):
No.
Alexander McCaig (06:22):
And so now when we look at the application of big data, it opens it up to all demographics, and how we analyze people starts to become a more full-bodied picture, more truthful picture of who they are.
Jason Rigby (06:33):
So let's say Experian, they came to you and said, "Hey, CEO Tartle, Experian wants to purchase data and we want to find a more truthful view of our consumer."
Alexander McCaig (06:48):
What do you want to know? You want to ask them why they don't want to pay off their loans, or why they can't, or why they run into some sort of economic trouble? The way you rate things is going to be a lot different now. And we can offer you any sort of granularity on that data because you're the one creating that data packet that is bespoke to Experian, that you're going to go then purchase from those people. And if you want to subscribe to their behaviors over a subset of time, you can do that. But you're going to have to have that direct connection, that bridge with them through the marketplace.
Jason Rigby (07:20):
Yeah. And I know there's life events that cause credit issues.
Alexander McCaig (07:26):
They don't give a shit about that.
Jason Rigby (07:27):
Yeah. Whether it's medical bills, whether it may be a divorce. Divorce is a big one.
Alexander McCaig (07:32):
They don't care.
Jason Rigby (07:33):
Right.
Alexander McCaig (07:34):
You're a number. This was your rating. And they look at it, "Here's the contractual agreement you said you were going to pay back on the... You're not paying it." They don't care what happens or what's in between. But I think the-
Jason Rigby (07:45):
That in-between in big data, how does the in-between in big data?
Alexander McCaig (07:48):
Let's talk about that.
Jason Rigby (07:49):
Yeah.
Alexander McCaig (07:50):
The old world was inflexible, and now that big data's come in, the credit models have to become more flexible, and they're not going to be as historical looking. There'll be more real time. That's the difference. That's the enhancement is the availability of data and the availability to process it instantly. Maybe the variability, if you have not a fixed score, but maybe a floating one, maybe that is probably going to be better for you.
Alexander McCaig (08:18):
So the better I act, the better choices I make in my life, just like with the thing you plug into your car and your insurance company gives you a better deal, maybe you're going to see that sort of variable credit worthiness happening with what you're doing on everything else. They begin to record that. And through that big data and that processing, I've made a lot of other good choices outside of trying to get credit, that should help me go in and say, "Well, I'm a good person. I'm truthful. I pay this stuff back. I'm low risk on everything else I do. Why is it that you're not underwriting me on it? Just because I'm not in the middle-class?"
Jason Rigby (08:52):
Yes.
Alexander McCaig (08:53):
Right? That's kind of screwed up. So now we we're opening it up to all those demographics. And when it became a FICO score that was based on, say just for generalization, five separate points that are only there that fits into a certain demographic, now we've opened it up and we look at the ability to repay across many, many different factors.
Jason Rigby (09:13):
So whenever you look at, because I want to make sure I understand this, so whenever you look at big data and we're looking at these three major companies, so a bank is going to come to them and say... Do you think the banks are solely relying on these three?
Alexander McCaig (09:30):
Yes. Yes.
Jason Rigby (09:31):
Just to make these decisions?
Alexander McCaig (09:32):
100%.
Jason Rigby (09:32):
And so thus, that's why all three of these companies are saying, "Let's get more granular with the data"?
Alexander McCaig (09:37):
Yeah. Because they got a grip on things. And they also, when they put a score on something and that score's inaccurate, that's a knock against them. The bank would come back and be like, "You told us all these people were at 720. But we've done our own analysis on their debt-to-income ratios, they're in the six hundreds. What the heck?"
Alexander McCaig (10:01):
And so they want to prevent those things from happening and they want to be even more granular so that they have a deeper assurance in their credit scores. These people live in a world of applying numbers to people and defining them by measurement of some linear scale, even when human beings are non-linear. But that's the issue with credit. But credit is evolving and big data will help credit evolve. It'll become more flexible.
Jason Rigby (10:20):
And now as far as decentralizing, because we're seeing... I just talked to somebody that-
Alexander McCaig (10:28):
Here's the thing. You talk about decentralization. Why do we have to rely on three companies to define?
Jason Rigby (10:32):
Yes, exactly.
Alexander McCaig (10:33):
If you decentralize the effort and we have even a blockchain technology and this data is verified from everybody across the globe, there's no reason for them to say this is what our score is. Every time I interact, it's supported by a network, global network of systems that say, "This person has done this. This is, in fact, the truth."
Jason Rigby (10:51):
Right. Then you've eliminated a lot-
Alexander McCaig (10:54):
You have eliminated the need. So then just us acting as human beings interacting in this decentralized format naturally gives us our own rating. And China does this in a... How do I say this gently? We need to watch our people and how they interact. So from a surveillance state, they give social credit ratings on the people that are in China like, "Oh, this is a good person. This is a bad person."
Alexander McCaig (11:25):
But if you expand that into decentralized, more unifying effort, there's no reason to have these three credit score bureaus be like, "Oh, this is this, this is this." They're no longer really necessary, but they're trying to stay reliant because credit hasn't moved into a decentralized effort. It's still centralized across these three companies.
Jason Rigby (11:44):
And it's so funny. This is decentralized. You see all these crowdfunding and you can see people literally going on there and getting millions of dollars based off of an idea that they put on a website with the video. And so no bank would lend money to somebody that walks into the door and says, "Here's a one-page summary and here's a video."
Alexander McCaig (12:10):
It's too nebulous for a bank, and banks are inflexible because they're burdened by certain banking laws as they should be. I mean, banks have... I don't want to get into this. It's too political. But the things that are more nebulous where there can be support and trust and a payback to the people that are investing in it, happens better in a more decentralized format.
Alexander McCaig (12:31):
And decentralization also spreads risk. It's shared risk across everything. So it's not like the three companies have to take the risk of rating people. And if they screw up, well, they're beholden to it.
Jason Rigby (12:41):
Well, all three of them experienced data breaches. So, I mean, that alone right there. Think about that.
Alexander McCaig (12:45):
Yeah, we're not going to get into that. We're not going to get into that.
Jason Rigby (12:46):
We're not going to get into that. Okay, we're going to be done.
Alexander McCaig (12:48):
Yeah. I'm going to shut that off. But the point is big data will make credit models more flexible. And as the data and the models become more decentralized, we're going to see greater benefit and economic opportunity for people that otherwise didn't have it.
Jason Rigby (13:00):
So it's positive, net positive.
Alexander McCaig (13:02):
Net positive.
Jason Rigby (13:03):
Awesome.
Automated (13:11):
Thank you for listening to Tartle Cast with your hosts, Alexander McCaig and Jason Rigby. Where humanity steps into the future and the source data defines the path. What's your data worth?
