We built PennyCalc because the existing calculators didn't work for people like us.

Three founders working across industries and locations, but facing the same challenges. We all built financial models in Excel and Google Sheets for ourselves - mortgage comparison spreadsheets, hotel/airline point optimization, 401(k) projections, RSU tax estimators - and passing them around in our group chat whenever someone had a big financial decision coming up.

Josh brought a private-equity financial-modeling background, Jessie brought management-consulting and editorial experience, and Michael brought implementation and product-building experience. The recurring problem was the same: many online calculators hid assumptions, skipped edge cases, or mixed a useful result with a sales funnel.

At some point, we looked at the collection of spreadsheets we had developed and realized: these are better than what's widely available. Not because we're smarter, but because we actually use them, test them, and refine them. We built for our own edge cases and it turns out those edge cases are pretty common among people with more complicated financial lives.

So we turned the chat-shared spreadsheets into a website.

Who this is for

PennyCalc is built for people whose financial lives have real complexity. Jumbo loans. AMT exposure. Backdoor Roth strategies layered on top of RSU vesting schedules. Capital gains planning across multiple holding periods. SALT cap scenarios.

Most financial content online is written for someone asking "what is a 401(k)?" That's fine, but it's not you (nor is it us). You know what a 401(k) is, but you want to know how to maximize your returns. What happens to your tax bracket if you max it out, do a mega backdoor Roth, and your spouse's RSUs vest in the same year. We build tools for these scenarios because they are the cases our team models and reviews most closely.

What we actually do differently

The math is visible. Our core calculators expose the formulas, schedules, bracket breakdowns, or year-by-year projections that produce the headline result. When a real provider uses inputs we do not model, the page should say so instead of implying false precision.

The assumptions are stated and overridable. When we default to a 1.1% property tax rate or $1,200/year homeowner's insurance, we tell you and let you change it. Your county's rate is probably different and you should use yours.

The examples are reproducible. Worked scenarios identify their inputs and assumptions so another reader can run the same case. We use personal anecdotes only when the person named has confirmed the details and the experience genuinely helps explain the decision.

We don't give advice (and that's not our job). We build tools that we use ourselves and share them with you. Run your scenarios, draw your own conclusions, and talk to a professional if you need guidance specific to your situation.

How we work with AI

We use AI tools to help organize research, draft and revise copy, implement code, and scaffold tests. AI is not one of our sources and it does not approve a page for publication. Josh, Jessie, and Michael remain accountable for checking primary sources, reviewing calculations and examples, and deciding whether the final page is accurate and useful. A byline names the responsible human reviewer; it does not imply that every sentence was typed without drafting assistance.

Our full sourcing, testing, and correction process is documented on the methodology page.

The team

JC

Josh

Financial Modeling & Data

Josh previously worked in investment banking at Houlihan Lokey and now works in financial modeling at a private equity firm. He leads financial-model and data design, with particular focus on mortgage, tax, and investing calculations. He reviews formulas, assumptions, edge cases, and worked examples with the rest of the team before changes are published. Michael owns the implementation, and both review issues where model design and code meet.

Topics: mortgage, home affordability, capital gains, investment returns, compound interest, Roth vs Traditional, tax history.

Read Josh's full profile

JR

Jessie

Editorial & Research

Jessie previously worked at McKinsey & Company and now works in consumer retail. She leads consumer-facing editorial, research presentation, and SEO. She reviews whether assumptions, limitations, and next steps are understandable to a reader who needs to use the result, not merely read about it.

Topics: paycheck, 401(k), Roth IRA, retirement, bonus tax, tax brackets, Social Security wage base.

Read Jessie's full profile

MK

Michael

Engineering & Implementation

Michael previously worked at Deloitte and now works in data and AI technology. He leads the implementation side of PennyCalc, reviewing calculator code, performance, responsive behavior, privacy controls, and regression tests. He works with Josh where financial-model decisions become code and with Jessie where an interaction or explanation changes what a reader understands.

Topics: debt payoff, auto loans, the math sections on every calculator, mortgage rate history, minimum wage history.

Read Michael's full profile

Professional backgrounds are included only to explain each reviewer's relevant perspective. Past and current employers do not sponsor, review, or endorse PennyCalc. Employer names and profile links are published only with the individual's approval.

How PennyCalc makes money

We're transparent about this: PennyCalc intends to earn revenue through display ads and selected affiliate partnerships when those programs are enabled. If a page contains a compensated link, it is disclosed next to that link. At other times the site may operate without active ads or affiliate offers.

This never affects the calculators or the content. The math doesn't change based on who's advertising. We chose this model because it means the tools are free - no signup, no email capture, no paywall.

Get in touch

Found a bug in a calculator? Have a scenario our tools don't cover? We want to hear about it.

Email: hello@pennycalc.com

Every error report gets investigated. Getting the math right is the whole point.