Advanced Testing Techniques

In banking development (and in fintech, in general), software quality isn’t negotiable. Payment flows, lending engines, and compliance modules must behave consistently across millions of unpredictable scenarios. For years, Test-Driven Development (TDD) has been the go-to methodology: write a test, write just enough code to pass it, then refactor. While effective, TDD is fundamentally example-based—it checks for correctness against specific, predefined inputs. 

But in complex financial systems, the real risks often lurk in edge cases you didn’t think to test. This is where Property-Based Testing (PBT) comes in. Instead of checking against a few examples, PBT validates that your system upholds certain properties across a vast range of automatically generated inputs. 

Why Property-Based Testing? 

TDD excels when the domain is straightforward. For example, validating that an interest calculation function returns 105 for a principal of 100 at 5%. But what about edge cases—negative balances, leap years in amortization schedules, or floating-point rounding issues in multi-currency conversions? 

With Property-Based Testing, you don’t write dozens of one-off test cases. Instead, you describe the properties the function should always satisfy, such as: 

“The balance should never be negative after applying valid transactions.” 

“The sum of principal and interest payments must equal the total repayment.” 

“Exchanging currencies and then converting back should not lose more than a small tolerance.” 

The testing framework then generates thousands of random inputs to verify those properties. 

Example: Loan Repayment Validation 

Using a JavaScript/TypeScript environment with fast-check, here’s how a property-based test for a loan repayment function might look: 

 1 import * as fc from "fast-check"; 
 2  
 3 // Function under test 
 4 function calculateRepayment(principal: number, rate: number, months: number): number { 
 5   return principal * (1 + rate/100 * months/12); 
 6 } 
 7  
 8 // Property: repayment should always be >= principal 
 9 test("repayment is never less than principal", () => { 
10   fc.assert( 
11     fc.property(fc.integer({ min: 100, max: 1_000_000 }),  
12                 fc.double({ min: 0, max: 20 }),  
13                 fc.integer({ min: 1, max: 360 }), 
14       (principal, rate, months) => { 
15         const repayment = calculateRepayment(principal, rate, months); 
16         return repayment >= principal; 
17       } 
18     ) 
19   ); 
20 }); 

Instead of validating one or two cases, this test checks the property across hundreds of randomized combinations of principal, interest rate, and term length. 

Benefits for Fintech Systems 

For banks and fintechs, Property-Based Testing adds an extra layer of robustness: 

Discover hidden bugs – Edge cases like leap-year interest, floating-point imprecision, or boundary conditions often surface only through randomized exploration. 

Greater confidence in compliance-critical logic – When regulators demand evidence of exhaustive testing, PBT helps demonstrate resilience against unanticipated scenarios. 

Less brittle tests – Instead of maintaining long lists of hardcoded inputs, you define invariant properties that should always hold true. 

Scalable coverage – Particularly valuable for systems handling diverse data inputs such as transaction feeds, API payloads, or customer data streams. 

TDD and PBT: Not Mutually Exclusive 

It’s important to note that Property-Based Testing doesn’t replace TDD—it complements it. Use TDD for guiding design with simple, deterministic examples, then apply PBT for areas of financial logic that demand resilience across infinite input spaces. 

For example: 

TDD for “account creation should fail if mandatory fields are missing.” 

PBT for “account balance should always equal the sum of transactions.” 

Challenges and Considerations 

Like any methodology, PBT has tradeoffs: 

Learning curve – Writing good properties requires deep understanding of financial invariants. 

False positives – Poorly defined properties may trigger failures that aren’t actual bugs. 

Test performance – Running thousands of input variations takes more time and compute, though this can often be tuned with configuration. 

Still, for high-stakes financial systems, the payoff in reliability far outweighs the overhead. 

Trust in Fintech 

The importance of trust when it comes to fintech is mandatory. When handling payments, loans, or compliance-sensitive operations, even a rare edge case can cause financial loss, reputational damage, or regulatory breaches. Property-Based Testing gives development teams a powerful tool to uncover those hidden pitfalls. 

Combining TDD for design clarity with PBT for robustness leads to more resilient, auditable, and regulator-ready systems. For fintech teams building the infrastructure of tomorrow, testing properties rather than just examples isn’t just a technique—it’s an imperative.