In 2024, North America had the highest number of high-net-worth individuals, with 8.45 million HNWIs living there. In Asia Pacific, there were also 7.59 billion HNWIs registered in 2024. High-net-worth individuals (HNWIs) are people with wealth exceeding one million U.S. dollars.

The United States is leading the ranking by number of high networth individuals , recording **** million individuals. Following closely behind is China with **** million individuals, while Lesotho is trailing the ranking with * thousand individuals, resulting in a difference of **** million individuals to the ranking leader, the United States. High Net Worth Individuals are here defined as persons with investible assets of at least *********** U.S. dollars in current exchange rate terms.The shown data are an excerpt of Statista's Key Market Indicators (KMI). The KMI are a collection of primary and secondary indicators on the macro-economic, demographic and technological environment in more than *** countries and regions worldwide. All input data are sourced from international institutions, national statistical offices, and trade associations. All data has been are processed to generate comparable datasets (see supplementary notes under details for more information).

In 2021, the number of high net worth individuals (HNWIs) in China amounted to over **** million. The number of HNWIs in the country was projected to increase significantly, reaching more than ** million by 2026. In comparison, Southeast Asia's most populous country Indonesia had just over ** thousand high net worth individuals in 2021.China also had the highest number of ultra high net worth individuals (UHNWIs) in APAC that year.

A variety of datasets for analysis of High Wealth individuals to assist HMRC's High Net Worth Unit in maintaining and refining its population. Matches 10 years of Inheritance Tax Data to the relevant in-life SA data. Updated: ad hoc.

This statistic shows the number of ultra high-net worth individuals in Germany in 2013, 2014, 2016 and 2017. The ultra wealthy population of Germany decreased between 2014 and 2016 from over ** thousand to approximately **** thousand, however there was a period of growth in 2017 when the the number of ultra high-net worth individuals increased to over ** thousand.

North America had the most ultra high net worth (UHNW) individuals in 2019. In that year, ******* ultra wealthy individuals resided in that region. The second highest number of ultra wealthy individuals lived in Asia with ****** individuals.

Asset And Wealth Management Market size was valued at USD 111.8 Trillion in 2024 and is projected to reach USD 153.01 Trillion by 2032, growing at a CAGR of 4% during the forecast period. i.e., 2026-2032.Global Asset And Wealth Management Market DriversThe market drivers for the Asset And Wealth Management Market can be influenced by various factors. These may include:Growing High Net Worth Individual Population: Expanding global wealth concentration is creating larger pools of affluent investors seeking professional management services. Additionally, this demographic shift is generating increased demand for personalized investment strategies and sophisticated financial planning solutions.Aging Demographics and Retirement Planning: Rising life expectancies are pushing individuals toward longer-term wealth preservation strategies and retirement income solutions. Furthermore, this demographic transition is creating sustained demand for advisory services that address complex estate planning and intergenerational wealth transfer needs.

The United States had the highest number of ultra wealthy individuals in 2022. In that year, there were nearly ******* ultra wealthy individuals in the country, while in China (excluding Hong Kong) there were ****** ultra wealthy individuals.

The global insurance market for High Net Worth Individuals (HNWIs) is experiencing robust growth, driven by increasing wealth concentration, rising awareness of sophisticated risk management strategies, and a growing demand for personalized insurance solutions. This market, estimated at $500 billion in 2025, is projected to exhibit a Compound Annual Growth Rate (CAGR) of 7% from 2025 to 2033, reaching approximately $900 billion by the end of the forecast period. Several factors contribute to this growth, including the expanding HNW population across emerging economies like Asia and a heightened need for protection against complex liabilities such as professional indemnity, cyber risks, and reputational damage. The market is segmented by application (Ultra HNWIs, Mid-Tier Millionaires, Millionaires Next Door) and by type of insurance, encompassing Life, Non-Life (including Homeowner's, Personal Excess Liability, Auto, Watercraft, and Professional Liability), reflecting the diverse insurance needs of this affluent demographic. Distribution channels also play a role, with a mix of direct insurers, independent brokers, and private wealth management firms serving this clientele. The competitive landscape is characterized by a mix of global insurance giants and specialized firms catering specifically to HNWI needs. Companies such as MetLife, Prudential, Swiss Life, and AIG are major players, alongside regional insurers and specialized brokers who focus on providing tailored solutions. The future of this market hinges on technological advancements, with Insurtech companies offering innovative products and services, enhanced data analytics for better risk assessment, and personalized digital experiences. Furthermore, the increasing demand for sustainable and socially responsible insurance options, alongside growing regulatory scrutiny, will influence the industry's future trajectory. The regional distribution of the market is geographically diverse, with North America and Europe currently holding significant market shares, but Asia-Pacific is poised for substantial growth, mirroring the expansion of its HNW population and increasing wealth concentration in the region.

The Asia-Pacific private banking market is experiencing robust growth, fueled by a burgeoning high-net-worth individual (HNWI) population, particularly in China, India, and Southeast Asia. The region's expanding middle class, coupled with rising entrepreneurial activity and significant wealth accumulation, is driving demand for sophisticated wealth management services. This demand is further fueled by increasing financial literacy and a growing preference for personalized investment solutions. The market is segmented by service type (asset management, insurance, trust, tax consulting, real estate consulting) and application (personal and enterprise), reflecting the diverse needs of HNWIs. Key players, including UBS, Credit Suisse, and others, are actively expanding their presence in the region through strategic partnerships, technological advancements, and tailored product offerings. While regulatory changes and economic uncertainties pose potential challenges, the long-term growth outlook remains positive, driven by the region's demographic trends and economic development. The market's Compound Annual Growth Rate (CAGR) exceeding 8% indicates a significant upward trajectory. This growth is unevenly distributed across the region, with faster expansion expected in emerging economies like India and Indonesia, due to their rapid economic growth and burgeoning HNWI population. Competition is intense, with established international players competing with regional banks and boutique firms. Success hinges on factors such as technological innovation, client relationship management, and the ability to navigate evolving regulatory landscapes. The market is expected to witness increasing adoption of digital platforms and fintech solutions, enhancing accessibility and efficiency of wealth management services. Furthermore, the focus on sustainable and responsible investing is gaining traction, influencing the investment strategies of both clients and private banking institutions. The forecast period (2025-2033) promises continued growth, fueled by the underlying positive macroeconomic trends and the increasing sophistication of the region's HNWI client base. Recent developments include: February 2023: GXS, a digital bank majority owned by Grab, operator of Southeast Asia's ubiquitous super app, expanded services since opening in September. GXS's app hardly looks like a banking app. The app updates GXS account holders with daily reports on how much interest their deposits have accrued. While a regular savings account offers 0.08% interest, time deposits, opened for specific purposes such as travel or layaway purchases, earn 3.48%., November 2022: SBC Global Private Banking announced the launch of its discretionary digital platform (DPM) in Asia, the first bank in the region to offer this service on a mobile app.. Notable trends are: Rising Insurance Business in Asia Pacific.

The high-net-worth individuals (HNWI) and ultra-high-net-worth individuals (UHNWI) in North America had the highest value of assets worldwide in 2024. The largest part of North American HNWI and UHNWI's assets were financial assets, such as cash and deposits, bonds, equities, and shares, which reached a value of over *** trillion U.S. dollars in 2024. North American wealth management clients also had the highest liabilities, amounting to **** trillion U.S. dollars.

Graph and download economic data for Households; Net Worth, Level (BOGZ1FL192090005Q) from Q4 1987 to Q2 2025 about net worth, Net, households, and USA.

About this dataset

Context

The dataset presents the detailed breakdown of the count of individuals within distinct income brackets, categorizing them by gender (men and women) and employment type - full-time (FT) and part-time (PT), offering valuable insights into the diverse income landscapes within High Bridge. The dataset can be utilized to gain insights into gender-based income distribution within the High Bridge population, aiding in data analysis and decision-making..

Key observations

• Employment patterns: Within High Bridge, among individuals aged 15 years and older with income, there were 1,375 men and 1,338 women in the workforce. Among them, 750 men were engaged in full-time, year-round employment, while 658 women were in full-time, year-round roles.
• Annual income under $24,999: Of the male population working full-time, 0.93% fell within the income range of under $24,999, while 5.47% of the female population working full-time was represented in the same income bracket.
• Annual income above $100,000: 30.40% of men in full-time roles earned incomes exceeding $100,000, while 40.73% of women in full-time positions earned within this income bracket.
• Refer to the research insights for more key observations on more income brackets ( Annual income under $24,999, Annual income between $25,000 and $49,999, Annual income between $50,000 and $74,999, Annual income between $75,000 and $99,999 and Annual income above $100,000) and employment types (full-time year-round and part-time)

Content

When available, the data consists of estimates from the U.S. Census Bureau American Community Survey (ACS) 2019-2023 5-Year Estimates.

Income brackets:

• $1 to $2,499 or loss
• $2,500 to $4,999
• $5,000 to $7,499
• $7,500 to $9,999
• $10,000 to $12,499
• $12,500 to $14,999
• $15,000 to $17,499
• $17,500 to $19,999
• $20,000 to $22,499
• $22,500 to $24,999
• $25,000 to $29,999
• $30,000 to $34,999
• $35,000 to $39,999
• $40,000 to $44,999
• $45,000 to $49,999
• $50,000 to $54,999
• $55,000 to $64,999
• $65,000 to $74,999
• $75,000 to $99,999
• $100,000 or more

Variables / Data Columns

• Income Bracket: This column showcases 20 income brackets ranging from $1 to $100,000+..
• Full-Time Males: The count of males employed full-time year-round and earning within a specified income bracket
• Part-Time Males: The count of males employed part-time and earning within a specified income bracket
• Full-Time Females: The count of females employed full-time year-round and earning within a specified income bracket
• Part-Time Females: The count of females employed part-time and earning within a specified income bracket

Employment type classifications include:

• Full-time, year-round: A full-time, year-round worker is a person who worked full time (35 or more hours per week) and 50 or more weeks during the previous calendar year.
• Part-time: A part-time worker is a person who worked less than 35 hours per week during the previous calendar year.

Good to know

Margin of Error

Data in the dataset are based on the estimates and are subject to sampling variability and thus a margin of error. Neilsberg Research recommends using caution when presening these estimates in your research.

Custom data

If you do need custom data for any of your research project, report or presentation, you can contact our research staff at research@neilsberg.com for a feasibility of a custom tabulation on a fee-for-service basis.

Inspiration

Neilsberg Research Team curates, analyze and publishes demographics and economic data from a variety of public and proprietary sources, each of which often includes multiple surveys and programs. The large majority of Neilsberg Research aggregated datasets and insights is made available for free download at https://www.neilsberg.com/research/.

Recommended for further research

This dataset is a part of the main dataset for High Bridge median household income by race. You can refer the same here

About this dataset

Context

The dataset presents the detailed breakdown of the count of individuals within distinct income brackets, categorizing them by gender (men and women) and employment type - full-time (FT) and part-time (PT), offering valuable insights into the diverse income landscapes within High Forest township. The dataset can be utilized to gain insights into gender-based income distribution within the High Forest township population, aiding in data analysis and decision-making..

Key observations

• Employment patterns: Within High Forest township, among individuals aged 15 years and older with income, there were 367 men and 337 women in the workforce. Among them, 182 men were engaged in full-time, year-round employment, while 146 women were in full-time, year-round roles.
• Annual income under $24,999: Of the male population working full-time, 7.14% fell within the income range of under $24,999, while 4.79% of the female population working full-time was represented in the same income bracket.
• Annual income above $100,000: 24.73% of men in full-time roles earned incomes exceeding $100,000, while 23.29% of women in full-time positions earned within this income bracket.
• Refer to the research insights for more key observations on more income brackets ( Annual income under $24,999, Annual income between $25,000 and $49,999, Annual income between $50,000 and $74,999, Annual income between $75,000 and $99,999 and Annual income above $100,000) and employment types (full-time year-round and part-time)

Content

When available, the data consists of estimates from the U.S. Census Bureau American Community Survey (ACS) 2019-2023 5-Year Estimates.

Income brackets:

• $1 to $2,499 or loss
• $2,500 to $4,999
• $5,000 to $7,499
• $7,500 to $9,999
• $10,000 to $12,499
• $12,500 to $14,999
• $15,000 to $17,499
• $17,500 to $19,999
• $20,000 to $22,499
• $22,500 to $24,999
• $25,000 to $29,999
• $30,000 to $34,999
• $35,000 to $39,999
• $40,000 to $44,999
• $45,000 to $49,999
• $50,000 to $54,999
• $55,000 to $64,999
• $65,000 to $74,999
• $75,000 to $99,999
• $100,000 or more

Variables / Data Columns

• Income Bracket: This column showcases 20 income brackets ranging from $1 to $100,000+..
• Full-Time Males: The count of males employed full-time year-round and earning within a specified income bracket
• Part-Time Males: The count of males employed part-time and earning within a specified income bracket
• Full-Time Females: The count of females employed full-time year-round and earning within a specified income bracket
• Part-Time Females: The count of females employed part-time and earning within a specified income bracket

Employment type classifications include:

• Full-time, year-round: A full-time, year-round worker is a person who worked full time (35 or more hours per week) and 50 or more weeks during the previous calendar year.
• Part-time: A part-time worker is a person who worked less than 35 hours per week during the previous calendar year.

Good to know

Margin of Error

Data in the dataset are based on the estimates and are subject to sampling variability and thus a margin of error. Neilsberg Research recommends using caution when presening these estimates in your research.

Custom data

If you do need custom data for any of your research project, report or presentation, you can contact our research staff at research@neilsberg.com for a feasibility of a custom tabulation on a fee-for-service basis.

Inspiration

Neilsberg Research Team curates, analyze and publishes demographics and economic data from a variety of public and proprietary sources, each of which often includes multiple surveys and programs. The large majority of Neilsberg Research aggregated datasets and insights is made available for free download at https://www.neilsberg.com/research/.

Recommended for further research

This dataset is a part of the main dataset for High Forest township median household income by race. You can refer the same here

About this dataset

Context

The dataset presents the detailed breakdown of the count of individuals within distinct income brackets, categorizing them by gender (men and women) and employment type - full-time (FT) and part-time (PT), offering valuable insights into the diverse income landscapes within Central High. The dataset can be utilized to gain insights into gender-based income distribution within the Central High population, aiding in data analysis and decision-making..

Key observations

• Employment patterns: Within Central High, among individuals aged 15 years and older with income, there were 499 men and 464 women in the workforce. Among them, 289 men were engaged in full-time, year-round employment, while 211 women were in full-time, year-round roles.
• Annual income under $24,999: Of the male population working full-time, 1.38% fell within the income range of under $24,999, while 45.50% of the female population working full-time was represented in the same income bracket.
• Annual income above $100,000: 24.22% of men in full-time roles earned incomes exceeding $100,000, while 1.90% of women in full-time positions earned within this income bracket.
• Refer to the research insights for more key observations on more income brackets ( Annual income under $24,999, Annual income between $25,000 and $49,999, Annual income between $50,000 and $74,999, Annual income between $75,000 and $99,999 and Annual income above $100,000) and employment types (full-time year-round and part-time)

Content

When available, the data consists of estimates from the U.S. Census Bureau American Community Survey (ACS) 2019-2023 5-Year Estimates.

Income brackets:

• $1 to $2,499 or loss
• $2,500 to $4,999
• $5,000 to $7,499
• $7,500 to $9,999
• $10,000 to $12,499
• $12,500 to $14,999
• $15,000 to $17,499
• $17,500 to $19,999
• $20,000 to $22,499
• $22,500 to $24,999
• $25,000 to $29,999
• $30,000 to $34,999
• $35,000 to $39,999
• $40,000 to $44,999
• $45,000 to $49,999
• $50,000 to $54,999
• $55,000 to $64,999
• $65,000 to $74,999
• $75,000 to $99,999
• $100,000 or more

Variables / Data Columns

• Income Bracket: This column showcases 20 income brackets ranging from $1 to $100,000+..
• Full-Time Males: The count of males employed full-time year-round and earning within a specified income bracket
• Part-Time Males: The count of males employed part-time and earning within a specified income bracket
• Full-Time Females: The count of females employed full-time year-round and earning within a specified income bracket
• Part-Time Females: The count of females employed part-time and earning within a specified income bracket

Employment type classifications include:

• Full-time, year-round: A full-time, year-round worker is a person who worked full time (35 or more hours per week) and 50 or more weeks during the previous calendar year.
• Part-time: A part-time worker is a person who worked less than 35 hours per week during the previous calendar year.

Good to know

Margin of Error

Data in the dataset are based on the estimates and are subject to sampling variability and thus a margin of error. Neilsberg Research recommends using caution when presening these estimates in your research.

Custom data

If you do need custom data for any of your research project, report or presentation, you can contact our research staff at research@neilsberg.com for a feasibility of a custom tabulation on a fee-for-service basis.

Inspiration

Neilsberg Research Team curates, analyze and publishes demographics and economic data from a variety of public and proprietary sources, each of which often includes multiple surveys and programs. The large majority of Neilsberg Research aggregated datasets and insights is made available for free download at https://www.neilsberg.com/research/.

Recommended for further research

This dataset is a part of the main dataset for Central High median household income by race. You can refer the same here

Lake County, Illinois Demographic Data. Explanation of field attributes:

Total Population – The entire population of Lake County.

White – Individuals who are of Caucasian race. This is a percent.African American – Individuals who are of African American race. This is a percent.Asian – Individuals who are of Asian race. This is a percent.

Hispanic – Individuals who are of Hispanic ethnicity. This is a percent.

Does not Speak English- Individuals who speak a language other than English in their household. This is a percent.

Under 5 years of age – Individuals who are under 5 years of age. This is a percent.

Under 18 years of age – Individuals who are under 18 years of age. This is a percent.

18-64 years of age – Individuals who are between 18 and 64 years of age. This is a percent.

65 years of age and older – Individuals who are 65 years old or older. This is a percent.

Male – Individuals who are male in gender. This is a percent.

Female – Individuals who are female in gender. This is a percent.

High School Degree – Individuals who have obtained a high school degree. This is a percent.

Associate Degree – Individuals who have obtained an associate degree. This is a percent.

Bachelor’s Degree or Higher – Individuals who have obtained a bachelor’s degree or higher. This is a percent.

Utilizes Food Stamps – Households receiving food stamps/ part of SNAP (Supplemental Nutrition Assistance Program). This is a percent.

Median Household Income - A median household income refers to the income level earned by a given household where half of the homes in the area earn more and half earn less. This is a dollar amount.

No High School – Individuals who have not obtained a high school degree. This is a percent.

Poverty – Poverty refers to families and people whose income in the past 12 months is below the poverty level. This is a percent.

The high-net-worth individual (HNWI) financial wealth value in the Asia-Pacific region reached **** trillion U.S. dollars in 2023. According to Capgemini, the HNWIs financial wealth value has recovered from losses in 2022.

Comprehensive demographic dataset for Kailua Kona, HI, US including population statistics, household income, housing units, education levels, employment data, and transportation with year-over-year changes.

Comprehensive demographic dataset for High Island, TX, US including population statistics, household income, housing units, education levels, employment data, and transportation with year-over-year changes.

In 2019, the primary industry focus of self-made ultra high net worth individuals (UHNWI) was banking and finance. In detail, **** of self-made ultra wealthy individuals investing in this industry. By comparison, ultra wealthy individuals who had inherited their wealth invested most in non-profit and social organizations, with a share of **** percent.