China vs Lithuania: Bank overhead costs to total assets

China
0.8%
in 2021
Lithuania
0.9%
in 2021
China rank
160th
Lithuania rank
157th

Bank overhead costs to total assets over time

  • China
  • Lithuania
12345200020102021

How they compare

Lithuania currently reports 0.9% against 0.8% in China, a difference of 0.1%.

That makes Lithuania's figure about 1.1 times China's.

Across all 22 years both countries report, Lithuania has been ahead every year.

China ranks 160th and Lithuania ranks 157th of 168 countries.

Lithuania has averaged higher in every one of the 3 decades both report.

Head to head by decade

Decade China Lithuania Difference Ahead
2000s 1.3% 3.3% 2.0% Lithuania
2010s 1.0% 1.4% 0.4% Lithuania
2020s 0.8% 0.9% 0.1% Lithuania

Averages of every year both report within each decade.

Frequently asked questions

Which has higher bank overhead costs to total assets, China or Lithuania?
Lithuania, at 0.9% against 0.8% in China as of 2021.
What is the difference in bank overhead costs to total assets between China and Lithuania?
0.1%, with Lithuania ahead.
How many years of comparable data are there for China and Lithuania?
22 years are reported by both, from 2000 to 2021.
How do China and Lithuania rank globally for bank overhead costs to total assets?
China ranks 160th and Lithuania ranks 157th of 168 countries.
Where does this data come from?
Bankscope, Bureau van Dijk (BvD), published as Bank overhead costs to total assets (%). Statizoid refreshes it automatically from the source and publishes the full history for both places.

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China vs Lithuania: Bank overhead costs to total assets. Statizoid, drawing on Bankscope, Bureau van Dijk (BvD). Retrieved 01 September 2026, from https://financial-sector.statizoid.com/compare/bank-overhead-costs-to-total-assets-percent/china/lithuania/

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About this data

Indicator
Bank overhead costs to total assets (%)
Unit
%
Source
Bankscope, Bureau van Dijk (BvD)
Licence
CC BY 4.0 (World Bank Open Data)
Coverage
168 places, 3,204 data points, 2000–2021
Last refreshed

Raw data are from Bankscope. Data2090[t] / ((data2025[t] + data2025[t-1])/2). Numerator and denominator are first aggregated on the country level before division. Note that banks used in the calculation might differ between indicators. Calculated from underlying bank-by-bank unconsolidated data from Bankscope.