Project description:

This was a series of visual stories focusing on Japan’s experience in the super-aging society. Japan faces obstacles in many areas like healthcare, housing, pension, etc. In the article on the housing problem, we analyzed that people need to continue mortgage payments until 73 years old on average because the average age of new borrowers is rising. In another story, we pointed out that we could face a shortage of doctors in some suburban areas due to the aging of doctors. We demonstrate the inconvenient truth by simulating the future and encourage immediate action.

Impact reached:

The article on housing problem attract high engagement from our readers and was one of the most read article last year with more than 300,000 viewers. Engagement from financial industry is especially high and we received letters from our readers. One said that lenders need to consider the risk of own behavior to solve the excess lending problem.

The article on aging doctors attract the attention from health ministry and local governments.

Techniques/technologies used:

We extracted data from 200+ PDF files with more than 30,000 pages by using the Python program. We calculated the average lending age and duration of the loan from a pool of mortgage data, and also we simulated the repayment amount for each year by using the mortgage rates.

For visualization, we used the scrolly telling techniques to enhance a better understanding of our readers.

What was the hardest part of this project?

We tried to access the comprehensive data on mortgages including large and small financial institutions. We asked many banks to provide their loan data, but banks were reluctant to provide their own data. The mortgage loan is a cash cow for banks under the ultra low-interest rate and they don’t admit their responsibilities for offering a large amount of loan to the aging society.

Throughout many interviews, we realized that mortgage-backed securities (MBS) are a good source of loan data and we finally collected the comprehensive data for our analysis. Using the data which include millions of mortgage loan, we revealed the inconvenient truth for the financial institutions.

What can others learn from this project?

This was the first time we used investor’s resources for our investigation.  We’re very surprised that there were full of interesting numbers. Even if it were PDF format, the document format is almost stylized and it is relatively easy to extract data. Documents for investors are highly technical at the first glance, but it’s worth a try.

Project links:

vdata.nikkei.com/en/newsgraphics/aging-society/housing-loan/

vdata.nikkei.com/en/newsgraphics/aging-society/aged-doctor/