About FinCalcs
Calculators, planning tools and practical guides to explore the choices behind your money decisions.
Our Mission
FinCalcs exists to make financial planning accessible, accurate, and free. We build interactive tools powered by government data so anyone can make informed money decisions — without needing a financial advisor, a spreadsheet, or a finance degree.
FinCalcs combines user-entered numbers, financial formulas and published reference data. Sources include the Federal Reserve, IRS, Bureau of Labor Statistics and Census Bureau. Use the assumptions and source dates accompanying a tool to understand its result.
The Founder
Abiot Y. Derbie, PhD
Biomedical Data Scientist · Founder of FinCalcs
Abiot Y. Derbie, PhD is a biomedical data scientist specializing in multi-prediction modeling, neuroimaging analytics, and large-scale data pipeline engineering. He holds a PhD in Neuroscience from The Hong Kong Polytechnic University, with a Bachelor's and Master's degree in Psychology. His research focuses on building predictive models from complex, multi-source datasets — extracting meaningful patterns from thousands of data points to inform real-world outcomes.
His background in psychology fuels a deep interest in behavioral finance and market psychology — understanding why people make the financial decisions they do, how cognitive biases shape spending and investing, and how better tools can help people overcome those biases. FinCalcs was born from that intersection: rigorous data science meets the human side of money.
He built FinCalcs to bring that approach to personal finance: define the question, identify the relevant inputs, compare scenarios and explain the assumptions behind a result. Published reference data provides context; your own balances, costs and lender quotes make a scenario relevant to you.
What We Offer
Interactive Calculators — Mortgage, Debt, Income and Tax, Investing and Retirement, Auto, Healthcare, and Planning tools.
600 City Salary Pages — 75 cities at 8 salary levels showing take-home pay adjusted for local taxes and cost of living.
51 State Take-Home Pay Guides — 3,000+ word guides covering state tax structures, effective rates, and comparison tools.
Rate References — Dated borrowing and savings references help you interpret a scenario. Use a lender or account-provider quote for the terms available to you.
Benchmark Comparisons — Explore published averages and historical comparisons, with attention to the survey year, population and dollar units.
Data Sources
Federal Reserve Economic Data (FRED) — Published series for mortgage rates, Treasury yields, the federal funds rate and other economic indicators. Each observation describes its own period and population.
Internal Revenue Service (IRS) — Federal tax rules, deductions and contribution limits. Use the tax year and eligibility conditions stated with a calculation.
Bureau of Labor Statistics (BLS) — Consumer Expenditure Survey, Consumer Price Index, and occupational wage data.
U.S. Census Bureau — American Community Survey information on household income and housing costs. These measures describe specific populations and survey periods.
Social Security Administration (SSA) — Benefit calculation formulas, full retirement age tables, spousal benefit rules, and COLA history.
Federal Reserve Survey of Consumer Finances (SCF) — Historical household wealth and debt statistics, including the published age-group medians and means used in our net-worth comparison.
Editorial Standards
Source-aware. Check the source, units, population and date behind a financial comparison.
Dates with meaning. A page-review date describes the page review; a rate observation or survey year describes the underlying data.
Clear disclaimers. FinCalcs provides educational tools — not personalized financial advice.
Transparent affiliates. Affiliate relationships are disclosed. Calculator results are never influenced by partnerships.
For full details, see our Editorial Policy.
Mathematical Reviewers
Mathematical review examines a tool’s formulas, inputs, assumptions and outputs. Useful checks include worked examples, boundary cases and agreement between a calculation and its explanation. The research profiles below describe expertise in statistical and computational methods.
Eskezeia Y. Dessie, PhD
Statistical Modeling & Machine Learning
Research Fellow at Indiana University School of Medicine, Specializes in computational modeling, predictive analytics, and model validation using advanced statistical and machine learning methods.
Armin Allahverdy, PhD
Machine Learning & Data Mining
Data scientist specializing in machine learning, data mining, statistical modeling, and pattern recognition. Reviews fincalcs.co quantitative content for statistical methodology and computational integrity across calculators, decision-support modules, and community benchmarks.
Reading a result: Start with the model’s stated scope, inspect the assumptions and try a second scenario. A useful comparison makes clear which inputs changed and why the result moved. Read our editorial standards for how we approach sources, calculations and corrections.