Some time ago when I was looking into the German credit scoring dataset, different models have shown that a "moral" of a person, namely, their empirically observed tendency to return borrowed money, is one of the main predictor for their credit score.
Which is kind of obvious.
This measure of "moral" can be deduced when data on one's credit history is available. In countries with long-established credit traditions, like Germany, it is normally not a problem to get this empirical evidence. However, in some countries this is not the case. Moreover, you can always stumble upon people who have not applied for any kind of loan, ever, anywhere.
How would you go about this problem?
For example, you can rely on a report coming from an independent credit agency (think SCHUFA in Germany). They track your incomes and expenditure and come up with a verdict. You can reach out to these agencies when you need to be backed up for, say, renting a flat, too. Such ratings are not available everywhere, and also, their estimate is not always the ultimate truth: SCHUFA has allegedly committed some errors in its analyses.
The second option to consider is try to come up with a tailored subjective estimate of your solvency based on your behavior and mindset. These two options should be taken into consideration separately.
In 2012, SCHUFA announced that they were going to use the personal data from people's Facebook profiles in their scoring, which, of course, has raised a vast negative feedback. Nevertheless, Kreditech, a Hamburg-based fintech startup providing microcredits to people, found in 2012, does act on this SCHUFA initiative. According to this article in the Economist, Kreditech asks a potential borrower for access to their data on Facebook, and, based on their profile and contacts, can infer, whether this person is likely to return a loan. The Economist quotes a Kreditech representative as saying that an applicant with a Facebook friend who has defaulted on a firm's loan would most probably be rejected.
This kind of verdict goes well in line with the proverb: "Tell me who your friend is and I'll tell you who you are". However, an average person aged between 25 and 43 has 360 friends on Facebook. This is in the US, but you get my point. So, out of these 360, one could have a friend (or two) who is a taxidermist, a tuk tuk driver or who has otherwise failed in grad school, but that does not help infer anything about the applicant. I am still waiting to get a reply from Kreditech, hopefully, I'll receive it sometime.
Facebook should indeed make a very good living from people's mundane life data. My assumption is supported by the fact that someone very knowledgeable I am friends with left his job as a quantitative analyst in finance to take a role of a software developer in Facebook. Also, their have just announced their new hire, Vladimir Vapnik, which means that they can afford it. The question is, do the users benefit from Facebook to the same extent as Facebook benefits from them.
Back to the task of credit scoring, there is another, indirect way to estimate someone's credibility. These are the psychometric scores based on questionnaires. The major name among companies that are doing such analyses is The Entrepreneurial Finance Lab (or the EFL). It is a business that originates from the Harvard University. It was found in 2006, and it's aim has been to take credit scoring to the next level, making it scalable and independent from data on past credit history, business field or financial documentation in possession.
I have found some evidence of implementation of the psychometrical analyses for credit scoring in the internet, but no example of a questionnaire itself. While I can imagine that analysts may employ some kind of deep learning to establish links between someone's personality traits and their "morale", on a micro and a macro levels, with a reduced knowledge on how this is actually done, this is still a black box to me. So I should just take someone's words that this works. And when it does, this is indeed amazing because it can help bridge so many gaps in crediting uncovered before.
In the meantime, it would be, perhaps, easier to make the potential borrowers go through a polygraphic analysis.
Which is kind of obvious.
This measure of "moral" can be deduced when data on one's credit history is available. In countries with long-established credit traditions, like Germany, it is normally not a problem to get this empirical evidence. However, in some countries this is not the case. Moreover, you can always stumble upon people who have not applied for any kind of loan, ever, anywhere.
How would you go about this problem?
For example, you can rely on a report coming from an independent credit agency (think SCHUFA in Germany). They track your incomes and expenditure and come up with a verdict. You can reach out to these agencies when you need to be backed up for, say, renting a flat, too. Such ratings are not available everywhere, and also, their estimate is not always the ultimate truth: SCHUFA has allegedly committed some errors in its analyses.
The second option to consider is try to come up with a tailored subjective estimate of your solvency based on your behavior and mindset. These two options should be taken into consideration separately.
In 2012, SCHUFA announced that they were going to use the personal data from people's Facebook profiles in their scoring, which, of course, has raised a vast negative feedback. Nevertheless, Kreditech, a Hamburg-based fintech startup providing microcredits to people, found in 2012, does act on this SCHUFA initiative. According to this article in the Economist, Kreditech asks a potential borrower for access to their data on Facebook, and, based on their profile and contacts, can infer, whether this person is likely to return a loan. The Economist quotes a Kreditech representative as saying that an applicant with a Facebook friend who has defaulted on a firm's loan would most probably be rejected.
This kind of verdict goes well in line with the proverb: "Tell me who your friend is and I'll tell you who you are". However, an average person aged between 25 and 43 has 360 friends on Facebook. This is in the US, but you get my point. So, out of these 360, one could have a friend (or two) who is a taxidermist, a tuk tuk driver or who has otherwise failed in grad school, but that does not help infer anything about the applicant. I am still waiting to get a reply from Kreditech, hopefully, I'll receive it sometime.
Facebook should indeed make a very good living from people's mundane life data. My assumption is supported by the fact that someone very knowledgeable I am friends with left his job as a quantitative analyst in finance to take a role of a software developer in Facebook. Also, their have just announced their new hire, Vladimir Vapnik, which means that they can afford it. The question is, do the users benefit from Facebook to the same extent as Facebook benefits from them.
Back to the task of credit scoring, there is another, indirect way to estimate someone's credibility. These are the psychometric scores based on questionnaires. The major name among companies that are doing such analyses is The Entrepreneurial Finance Lab (or the EFL). It is a business that originates from the Harvard University. It was found in 2006, and it's aim has been to take credit scoring to the next level, making it scalable and independent from data on past credit history, business field or financial documentation in possession.
I have found some evidence of implementation of the psychometrical analyses for credit scoring in the internet, but no example of a questionnaire itself. While I can imagine that analysts may employ some kind of deep learning to establish links between someone's personality traits and their "morale", on a micro and a macro levels, with a reduced knowledge on how this is actually done, this is still a black box to me. So I should just take someone's words that this works. And when it does, this is indeed amazing because it can help bridge so many gaps in crediting uncovered before.
In the meantime, it would be, perhaps, easier to make the potential borrowers go through a polygraphic analysis.
