Lending and trading are two places where software carries real financial risk. A loan system has to decide who to lend to, track what is owed for months or years, and cope with missed payments. A trading system has to match buyers and sellers fairly, in order, and in a fraction of a millisecond. Both depend on exact numbers and a clear record of every change of state.
You'll start with how lending platforms work: the loan origination system that takes an application through to a decision. Then you'll look at credit scoring, where a machine learning model estimates how likely a borrower is to repay. After that you'll move to trading and see how an exchange keeps an order book and uses matching algorithms to pair buy and sell orders, and finish with a system design walkthrough of a stock exchange.
Remember that money and prices should never be held as floating point numbers, because rounding errors add up across interest calculations and fills. Store amounts as integers in the smallest unit, or as exact decimals. Once you've finished this module, move on to Testing, Observability & Delivery.
An explainer on what a loan origination system is and how lending technology supports the loan process from the first application through to a decision.
A hands-on project on building a credit scoring model with machine learning, estimating whether a borrower is likely to repay. Work through it alongside the code.
How exchanges match buy and sell orders, and how the matching algorithm decides which order is filled first.
A system design walkthrough of a stock exchange that compares several approaches to handling orders and matching them.