mintos* provides quite some loan originator data on its public statistics page*. So far, investors were copying the loan originator data by hand to manually build up the time series data. The purpose of this was to keep track of loan originator developments. Popular metrics are loan status, average interest earned and pending payments. One of the techniques applied was data visualization and charting.
Today we can prodly say: Manual work is no longer necessary!
We have automatized the process of visualizing the public mintos data. Major benefit: visualizing mintos loan originators data is key for investors to optimize their portfolios and hopefully mitigate loan originators risks.
To visit the overview page of the mintos loan originators data, just click the button below:
Although the feature has been just released, we have enough experience to reflect on the benefits of data visualization. Here are five benefits that come into my mind.
Keeping track of a loan originator’s loan supply could help to estimate its commitment to the marketplace. The semantics may vary, but questions are raised what an expanding or shrinking loan portfolio of a specific loan originator may mean.
As you probably have heard, some key loan originators are currently building up their own platforms; loan originators that are or were active as lenders on the mintos marketplace. That is to say:
Let’s pick two of them and look at their charts. It seems as if Creamfinance is reducing its mintos portfolio, while the portfolio of Creditstar remains relatively stable.
Of course, more information should be drawn upon to justify strong theses. Nevertheless, visualizing the loan portfolio gives you a first idea of trends.
Maybe the most interesting question when monitoring loan originators data is: Do loan originator risks increase?
This is, of course, not an easy question to answer. For example, Kristaps Mors has analyzed the popular Creditstar loan originator by – among many other arguments – taking into account its pending payments data. The latter is frequently debated among mintos investors.
Another example is the Indonesian lender Dana Rupiah*. As of 20 June 2021, for the last days, its pending payments have increased. Before, the company showed an impeccable pending payments performance. Some investors guess that it has to do with the Covid-19 situation. Whatever the reasons may be, getting an early warning of such developments is useful.
On 21 April 2021, mintos announced that the E-Cash loan originator had been suspended*. All its charts confirm that things went badly.
Some days before the 21 of April, the loan volume was shrinking. Finally, the outstanding loan volume dropped to zero. The originator halted its lending operations on the marketplace.
The loan status gradually changed from “current” to plus 60 days late.
Pending payments were steadily growing until they reached a boundary value at around 1,13 Million Euro. As no payments have been made, average days pending were and are steadily growing.
Average Net Annual Returns dropped to zero.
All in all, I would dare to claim that E-Cash charts display the archetype of a defaulted loan originator. Provided this example, hopefully we can identify crashing loan originators in the making. Of course, nobody can prophesy the future. But knowing the patterns of crash could help to prepare mitigation strategies.
As of summer 2021, investors complain that interest rates are in decline. With our per loan originator charts, you can analyse for which loan originator interest rates grow, remain stable or decline.
To pick one example. For me, Kviku* shows very sane charts. It is kind of the counter example to E-Cash above: Its loan portfolio is growing; most of its loans are in status “current”; pending payments are practically zero; returns are above stable 12 percent.
ID Finance*, on the other hand, has reduced interest rates from above 11% to just 10%.
Comparing charts of multiple loan originators is much easier than following the tabular data everyday on the mintos statistics page. Charts help to see the relations of the numbers over time.
Data visualization not only helps to understand the big picture. From here, automatic alerts and analytics can be developed.
A first step has been made with the daily mintos loan originators pending payments update of @beyondp2p_bot. The telegram bot informs its followers every day about the differences of pending payments from yesterday to today. Using this alert, you get an idea of which loan originators accumulate outstanding payments, and which pay back their debt with the investors.
Further features and automatic analytics are planned. The idea is to introduce a set of rules that trigger automatic alerts once, for example, the data of the loan originator indicates trouble. Once again, the E-Cash example above should be the best reference.
In conclusion, the mintos loan originator data feature is a big step to carry forward what we would like to achieve with beyondp2p: being the number one data-centric source for P2P Investors. Make sure to join the mission! 🚀😎
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