Recently, we released several posts that have explored the origination of loans by unique data like home ownership, education, employment duration and more. This month, we’re going to do the same and compare how this has changed in comparison to the previous months.
Average income, loan amount and age
Let’s first remind ourselves of some of the figures from November.
This month, the average net income in Estonia slightly increased while the average loan amount decreased by nearly €166. In Finland, the average net income increased by approximately 8% and the average loan amount also increased by 4%. The trend in Spain was lower for both data points, the average net income decreased by nearly 7.5%, at the same time the average loan amount decreased by over 6%.
In December, the average duration across each country was grouped much closer than previously, ranging from 42 – 45 with Spain showing the shortest and Estonia the longest. The difference in average age was slightly higher this month, ranging from 39 in Estonia to 47 in Finland.
Loan and employment duration
December has shown the same pattern as November and October for loan duration, with 36 months being the most common, followed by 60 months. Employment duration also followed suit with ‘More than 5 years’ being the most common, followed by ‘Up to 5 years’ and ‘Up to 1 year’. This would suggest that people who are more confident in the continuation of their employment and the stability of their income are most likely to apply for a loan.
| Loan durations | Estonia | Spain | Finland |
| 3 | 3 | 1 | – |
|---|---|---|---|
| 6 | 7 | 2 | – |
| 9 | 11 | 1 | – |
| 12 | 18 | 4 | – |
| 18 | 15 | 5 | 3 |
| 24 | 34 | – | 2 |
| 30 | 9 | – | – |
| 36 | 635 | 166 | 190 |
| 48 | 57 | 33 | 35 |
| 60 | 466 | 40 | 70 |
| Employment duration | All countries |
| Trial Period | 13 |
| Up to 1 Year | 346 |
| Up to 2 Years | 65 |
| Up to 3 Years | 52 |
| Up to 4 Years | 37 |
| Up to 5 Years | 455 |
| More than 5 Years | 731 |
| Retiree | 69 |
| Other | 39 |
Education and home ownership
Overall, the most common type of education declared by borrowers is of a High School standard, followed by University, Vocational School and Junior High School. However, this varies significantly by country, in Estonia the most common is High School where as in Spain it is University level and in Finland, Vocational School.
| Education level | Estonia | Spain | Finland |
| Junior high school | 164 | 32 | 43 |
|---|---|---|---|
| Vocational | 177 | 31 | 119 |
| High school | 595 | 65 | 59 |
| University | 319 | 124 | 79 |
The most common home ownership status in Estonia and Finland is ‘Owner’, in comparison the most common in Spain is ‘Living with parents’. In Finland, only 2 borrowers were registered as living with their parents, this shows how different social factors can vary significantly between the countries we operate in and why it is important to look at a number of different data points to get the full picture.
| Home ownership status | Estonia | Spain | Finland |
| Owner | 605 | 51 | 119 |
|---|---|---|---|
| Owner Mortgage | 113 | 64 | 71 |
| Living with parents | 212 | 71 | 2 |
| Tenant | 255 | 54 | 90 |
| Council house | 9 | 1 | 8 |
| Other | 61 | 11 | 10 |
Verification
The data below shows how many customer’s income and expenses have been verified. Regardless of whether the borrower’s income has been verified, the background checks with population and credit referencing agencies are still conducted. Overall, the total number of customers who were verified is higher than those classed as unverified.
| Income | Estonia | Spain | Finland |
| Verified | 597 | 231 | 260 |
|---|---|---|---|
| Unverified | 658 | 21 | 40 |
Which data point is the most important?
The individual risk of issuing a loan to a borrower is calculated using all of the parameters above and many more. The self-reported data which is displayed to investors is typically not very predictive and has relatively little influence on the Bondora rating of a particular loan. Therefore, this information should not be viewed as the only data used in determining the expected default of a loan.
Overall, this can give you a great idea of the basic profile of our borrowers and how this changes with the origination of loans in the coming months. Leave us a comment below and let us know which data points you think are the most influential in credit scoring.
