What this article shows

Only three of the six cities publish financial-asset figures for households in their 40s: about ¥19.03 million in Tokyo's 23 wards, about ¥9.25 million in Kawasaki, and about ¥7.73 million in Saitama City. Mortgage balances are not included in this statistical table, so we do not infer net worth or debt burden from the asset balances and compare only what is actually published.

Financial assets for ages 40–49 in 6 major Kanto cities (2019)

RankCityFinancial assets (¥1,000)Approximate valueData note
1Tokyo special wards19,026About ¥19.03 millionRelatively reliable
2Kawasaki9,246About ¥9.25 millionRelatively reliable
3Saitama City7,727About ¥7.73 millionModerate
4+YokohamaNot published (null)Insufficient sample
4+Chiba CityNot published (null)Insufficient sample
4+SagamiharaNot published (null)Insufficient sample
Tokyo special wards About ¥19.03 million Financial assets
Kawasaki About ¥9.25 million Financial assets
Saitama City About ¥7.73 million Financial assets

Only Tokyo, Kawasaki, and Saitama City can be compared

Tokyo's 23 wards report ¥19.026 million, Kawasaki ¥9.246 million, and Saitama City ¥7.727 million. The gap between Tokyo and Kawasaki is ¥9.78 million, while Kawasaki exceeds Saitama City by ¥1.519 million.

Yokohama, Chiba City, and Sagamihara are not published, so this is not a complete six-city ranking. Financial assets are balances such as deposits and securities and are not net assets after subtracting liabilities such as mortgages.

In the home-buying years, separate financial assets from real estate and debt

Reading the regional background

Tokyo's 23 wards, Kawasaki including Musashi-Kosugi, and Saitama City including Urawa and Omiya differ in housing prices, homeownership rates, and the timing of home purchases. Many households in their 40s face home purchases and children's education expenses at the same time. A household may have relatively little in financial assets because it owns real estate, or it may hold substantial financial assets while also carrying large debts.

But mortgage balances are not included in this table. The most accurate approach is therefore to keep this strictly as a three-city comparison of financial assets rather than estimating liabilities from city stereotypes.

How to read these figures

Important notes

These asset statistics are averages and do not directly show medians or the distribution of assets. They cover households with two or more members, and real estate assets outside financial assets may not be included.

The article is organized primarily around figures from published statistics. Numerical values directly observable in the statistical tables should be distinguished from interpretations of background factors.

Summary: Limit the comparison to financial-asset balances in the three cities with published data

Key takeaway

Tokyo's 23 wards are highest among the three cities with published figures, but without mortgage debt and real estate values this cannot be called a “net-worth ranking.” It is also better to avoid presenting the figures as a six-city ranking when three cities are unpublished.

  • Tokyo special wards: about ¥19.03 million
  • Kawasaki: about ¥9.25 million
  • Saitama City: about ¥7.73 million
  • Yokohama, Chiba City, and Sagamihara are not published; liabilities are also unknown

Source: Published statistics listed in the Analysis notes at the end of this article


📊 Analysis notes

This article is based on the following statistical data.

  • Statistics used: Statistics Bureau of Japan, National Survey of Family Income, Consumption and Wealth (Household Assets) (Table ID: 0003426527, view on e-Stat)
  • Area: Six major Kanto cities / Kanto region
  • Year: 2019
  • Data retrieved: June 6, 2026
  • Notes: The article is organized primarily around figures from published statistics. Because asset distributions, household differences, and other factors outside the article also matter, numerical values directly observable in the statistical tables should be distinguished from interpretation.

Chart and table values have been independently aggregated and visualized from the statistical data above.

Table values have been organized from the statistical data above.