Instalment Plan True Cost and APR Calculator for Phone and Appliance Kist Offers

The problem: "easy instalments" with no visible rate

A mobile phone shop advertises a handset at a cash price, or "only" a certain amount a month for twelve months with a small down payment and a processing fee. Many buyers, especially first-time earners and students, compare the monthly figure with their salary and sign. Few can work out that the plan might cost far more than the cash price in effective annual interest terms, and that a bank or wallet loan might be cheaper or more expensive. Shops rarely state an annual rate, and when they do, it may be a flat rate that understates the true cost.

Calculating a true rate needs the timing of every payment. That is a solved mathematical problem, but not one ordinary buyers can do.

The same applies to other everyday credit: motorcycles, solar panels, furniture and laptops for students are all commonly sold on instalments by shops and dealers, and buy now, pay later options are spreading in online stores. A single calculator that handles all of these, and a public record of what they really cost, helps buyers ask better questions before they sign and gives consumer groups evidence instead of anecdotes.

What already exists and the gap

• Bank EMI calculators compute the monthly payment for a given interest rate. They work forwards from a rate, not backwards from an offer.
• Spreadsheet functions such as RATE and IRR can find the rate if you know how to set the cash flows up correctly, including fees and down payments.
• Comparison sites list bank products, not shop instalment plans.

The gap is a free, bilingual tool that starts from the offer the buyer actually has in front of them and gives one honest, comparable number, plus a public dataset of what local plans really cost.

Inspiration

In the United States, Regulation Z (Truth in Lending), Appendix J sets out the actuarial method for computing the annual percentage rate on closed-end credit, with equations and worked examples, so that lenders disclose a comparable rate. This project uses that published method as a well-documented, testable reference for the calculation, while making clear it is a calculation method, not local law.

What you build

• Buyers enter the cash price, down payment, any fees and the instalment plan. They see the APR, the total amount paid and how much more that is than the cash price, in rupees and as a percentage.
• Comparison mode lets a buyer put two shop offers and a loan quote side by side.
• The public report shows the range of effective rates across real offers collected by the team, by product type and seller type.

The technically interesting part

• Solving for the rate. The APR is the rate that makes the present value of all payments equal to the amount financed. There is no closed-form answer for most plans; implement Newton's method or bisection with safe starting points and prove it converges for valid inputs.
• Getting the cash flows right. Upfront fees reduce the amount financed; a down payment is paid at time zero; some plans have a first instalment at signing. Each choice changes the answer, so model them explicitly.
• Money arithmetic. Use decimal arithmetic, not floating point, and decide rounding rules up front.
• Testing against a standard. Reproduce the worked examples from the published method exactly before trusting your engine.

How to evaluate it

• Correctness: your engine matches the published worked examples and a spreadsheet IRR calculation for 100 generated plans.
• Dataset quality: each collected offer has a date, source and photo or link, and two team members check each entry.
• Usability: five or more people who have bought on instalments try the tool and explain the result in their own words.
• Impact: in the user test, did seeing the APR change which offer they would choose?

Suggested plan

• Weeks 1 to 3: study the APR method and worked examples; write the engine with tests.
• Weeks 4 to 6: form, results screen and comparison mode.
• Weeks 7 to 10: collect and verify real offers.
• Weeks 11 to 13: user tests and the public report.
• Weeks 14 to 15: final report and demo.

Path to a product

Financial literacy groups, consumer rights organisations and fintech companies that offer fair credit all benefit from a trusted calculator. It could be offered as an embeddable widget for comparison sites or as a free public tool with sponsorship. It is a good first portfolio project for fintech roles because the maths is exact and testable.

Scope warning

This is a calculator and a dataset, not financial advice; say so clearly. Do not name and shame individual shops in the public report; summarise by category. Never publish a rate you have not verified from a real offer.

Learn what you need on Sefism

• Programming foundations roadmap: the core skills for a careful first project.
• Frontend development cheat sheet: building the form and results screen.
• Next.js Documentation: the web app framework.
• Vitest Documentation: testing the APR engine against worked examples.
• Data analytics roadmap: presenting the collected offers honestly.

Get help with this idea

The hard part is modelling each offer's cash flows correctly and collecting trustworthy data. Tauseef can help you check the engine, plan the data collection and turn the report into a strong portfolio piece. If you are new here, create a free account first.

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