What Can Data Tell Us About Money? A Simple Look at Savings, Wealth, and Debt

By abhishek.verma75000 · October 8, 2026

A simple look at savings, wealth, debt, and spending through data. Money is part of everyone’s life, but our financial habits can be very different. To…

The 18-25 age group shows the highest average savings rate at 29.88%, outperforming other age brackets. Two charts were generated showing savings rate comparisons across all age groups and occupation categories, along with detailed data tables breaking down the exact figures for each group.

The analysis generated two visualizations and detailed data tables comparing debt-to-income (DTI) ratios and high debt risk rates across countries and wealth brackets. The charts show the top 10 countries ranked by average DTI, with color intensity indicating the percentage of people with high debt risk in each country. A second chart breaks down DTI and debt risk by wealth bracket, revealing how financial strain varies across income levels. Generally, lower wealth brackets tend to carry a heavier debt burden relative to their income, along with higher rates of debt risk, while wealthier brackets show more manageable debt-to-income levels.

Financial literacy score shows essentially no correlation with either net worth or savings rate in this dataset. The correlation coefficients are very close to zero (r = 0.002 for net worth, r = -0.002 on a log scale, and r = 0.005 for savings rate), meaning people with higher financial literacy scores don't tend to have meaningfully higher net worth or savings rates than those with lower scores.

Out of 10,000 people analyzed, 4,263 (42.6%) are millionaires. The biggest differences between millionaires and non-millionaires come down to investing behavior rather than personality traits: millionaires invest nearly 3x more annually ($24,013 vs $8,479) and have dramatically better portfolio diversification scores (84.4 vs 49.2). They also save a higher percentage of income (32% vs 24%) and show slightly more frugality and investment knowledge. Interestingly, 'soft' traits like financial discipline, delayed gratification, self-control, and consistency scores were nearly identical between the two groups — suggesting that concrete financial actions like consistent investing and diversification matter more than personality differences in building wealth.

The analysis generated visual comparisons of net worth across business owners, entrepreneurs, and employees, including a bar chart comparing average and typical net worth values, and a box plot showing how net worth is spread out within each group. These charts let you visually compare how financial outcomes differ depending on someone's work status.

Salary and bonus income is by far the strongest driver of net worth in this dataset, with a correlation of 0.468. Business income and passive income show essentially no correlation (0.001 and 0.003 respectively), meaning they don't move together with net worth in any consistent pattern across this group. This is partly explained by the averages: people earn about $143,570 a year in salary and bonuses on average, compared to just $3,692 from business income and $1,560 from passive income — salary income is simply much larger and more consistent, making it the dominant factor tied to net worth.

A correlation matrix was built covering seven productivity and habit consistency metrics (daily and weekly productivity scores, task completion rate, procrastination score, time management score, overall habit consistency score, and deep work hours per day) alongside two financial outcomes: financial stability score and net worth (log). This was visualized as a color-coded heatmap, where darker red and blue shades show stronger positive and negative relationships respectively. The heatmap lets you quickly spot which habits tend to move together with financial stability and wealth accumulation.

The analysis ranked countries by combining their average net worth, financial literacy score, and savings rate into an overall rank. Two charts and several data tables were generated showing the top 10 and bottom 10 countries across these three dimensions. The first chart compares individual metric ranks (net worth, financial literacy, savings rate) for the top and bottom performing countries, making it easy to spot which countries consistently excel or lag across all three measures. The second chart zooms into the top 10 countries, comparing their financial literacy scores against savings rates side by side.

Looking at sleep, stress, exercise, and overall health consistency across age and gender groups, the healthiest routines belong to 18-25 year old Females, who sleep 8.65 hours a night, exercise 3.38 days a week, and report the lowest stress level (46.07), earning a composite health score of 74.0 out of 100. The least healthy segment is 56-65 year old Males, with less sleep (7.89h), less exercise (2.92 days/wk), and higher stress (51.09), scoring 65.8. As for whether healthy routines line up with financial success: the relationship is mixed. Health scores correlate moderately positively with financial stability score (0.34), suggesting healthier segments tend to be a bit more financially stable, but surprisingly correlate negatively with income percentile (-0.64) meaning the healthiest groups (younger people) actually report lower income percentiles, likely because income naturally rises with age/career stage. So healthy habits align somewhat with financial stability, but not with higher income.

Using the IQR method, 2,307 of 10,000 individuals (about 23%) were flagged as outliers across monthly expenses, annual luxury spending, or debt-to-income ratio. Breaking it down: 463 had extreme monthly expenses, 880 had extreme luxury spending, and 1,111 had extreme debt-to-income ratios. Overall, outliers tend to have a higher median income percentile (57.3) than non-outliers (48.1), and the most common profile is someone in the $1M-$2.5M wealth bracket working full-time. However, the two types of outliers tell very different stories: luxury-spending outliers are mostly affluent (median income percentile of 74.9), while debt-to-income outliers are mostly financially distressed (median income percentile of just 21.0). So while outliers as a whole skew toward high earners, the debt-heavy outliers represent a distinct group of lower-income individuals carrying disproportionate debt burdens.