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Drizz raises $2.7M in seed funding •
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Featured on Forbes
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Drizz raises $2.7M in seed funding •
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Featured on Forbes
A bug in a mobile banking app will be a lot worse than a broken UI. It could mean the system debits twice, makes connections to dangerous third parties, or even lock a user out during a payment.
Take a case where a user initiates a transfer in your app that is interrupted by a timeout. Because your app shows the transfer as Failure, the user attempts the transfer again. In that time, your backend may have processed the request. So, as a result of the timeout, two debits are made for a single transfer. This type of failure happens for various reasons. They may include bypassing security checks, payment completed by the user, but a confirm page never loads, etc.
Just looking at an application with a good UI will not give you the guarantee that the application provides sufficient data protection features. You need to run different types of tests to see how your application will perform when it is used by a large number of users, and various things happen (application and network are stressed).
This needs to include testing an app’s general features such as: determining a request to transfer funds is idempotent, whether security measures such as Root Detection can be bypassed, and the effectiveness of protective measures, such as SSL Pinning, and Device Attestation.
This incorporates testing the main banking system, mobile applications, APIs, payment gateways, KYC, fraud engines, and real-time payment systems. Just a UI test passing itself does not mean you can release your application.
A release is safe as long as your app functions securely, accurately, and remains stable as various components of the app, network, service providers, and back-end infrastructure gracefully degrade.
This is an engineering guide that shows how to test mobile banking and fintech apps with regard to KYC, SSL pinning, root detection, device attestation, OTP and MFA automation, biometrics, idempotency, payment failure states, APIs, load, Network resilience, Real devices, and peripherals, accessibility, compliance, and CI/CD.
3 main things that make fintech testing harder:
Verizon's 2025 DBIR found financial gain motivated 95% of breaches, with system intrusion leading pattern across 22,000 plus incidents.
A r/digitalnomad founder who built payment systems for 3 years said testing was always hardest part.
Compliance adds another layer of QA work in Fintech and Banking Apps.
A r/fintech commenter shared that one must-have is a compliance-and-reliability-first mindset from day one when building fintech and banking apps.
Functional testing here is about state. Each flow carries money or identity, so each needs positive, negative, and interrupted paths.
The high stakes flows:
The edge cases where bugs cluster:
Model each flow as a state machine and test transitions. A transfer that moves from initiated to pending to settled has failure branches at each hop, and those branches are where reconciliation bugs hide.
A reddit user on r/digitalnomad framed priority well: pick 2 or 3 non-negotiable flows like sign up, KYC, and money in or out, and treat them as a pre flight checklist before every deploy.
Assess the security controls from an adversarial point of view. Use Frida and Objection on a rooted device, to test if the controls can be defeated.
- Certificate pinning: Hook the pinning logic (e.g. OkHttp's CertificatePinner) and/or TrustManager and route the traffic through Burp Suite. If the proxy is able to see the cleartext traffic, the certificate pinning control has been bypassed.
- Root detection: You must check the app on a Magisk-enabled device with DenyList configured, and attempt to defeat root-detection using standard bypasses. . If the app launches despite the device being rooted, root detection has been bypassed.
Client-side security checks can be dealt better with runtime instrumentation. It is best to enforce critical security decisions server-side wherever possible. Server side decisions are fundamentally more secure than any client-side checks and validation. The server should reject sessions when Play Integrity or Apple App Attest returns an unacceptable verdict, rather than relying solely on client-side checks that can be circumvented using tools such as Frida.
Check secure storage explicitly:
- Neither tokens, PANs nor balances are seen in logs, clipboard, screenshots, unencrypted SharedPreferences/PLists.
- Key material is stored in Keystore/Keychain, away from the app's own files.
Finally, run OWASP MASTG categories and simulate most relevant attacks to a money app, such as MITM, replay, credential stuffing and account takeover. Our mobile app security testing guide contains more details.
Zimperium's 2025 Global Mobile Threat Report states that nearly 60% of iOS apps and 43% of Android apps have PII data leakage issues and over 50% of the devices are running outdated and/or compromised OS.
As one user on r/reactnative states, mobile security testing is different because the attacker gets the compiled binary and the device itself.
Hardcoding an OTP works in a staging or dev environment. It's not practical for production because the production environment requires a true source. Some of these true sources include:
Cross app automation can be hard. If a second factor lives in another authenticator app like google auth or Duo, then a session scoped to one app cannot jump to other apps, so teams code OTP and TOTP retrieval.
The same is true for biometrics. A platform's test path for biometric or PIN entry is usually scripted, and a PIN fallback is scripted in the case of failure for biometric entry, using patterns in how to test login functionality on mobile.
Start with idempotency. Submit the same transfer two times using one Idempotency Key, then check that there is only a single ledger entry. If you submit it with different keys then there should be two ledger entries.
It's better to force failures than to wait for them to happen. Some of the failures you can force are:
After that, reconcile what the UI shows against the ledger over API. Double tap on a slow network is a classic case of double debit, so client debounce and server side dedupe should be tested separately. Same rigor should be applied to the in app purchase flow.
In a banking app, a failed transfer or a bypassable pinning check is a fraud vector and a compliance finding. That moves bar from "does feature work" to "does security control hold when someone attacks it, and does ledger stay correct when network dies mid transaction."
The table below lists the various test surfaces and what you need to validate in fintech apps in the order of priority.
Consider the greatest possible negative impact for which your failure could be primarily responsible. This would put the threat of payment insecurity and compliance ahead of the failure of a less important cosmetic control.
To build a robust test plan, you must prioritize your highest-risk scenarios. Below is how you should relate potential failures to the evidence needed to resolve them:
KYC is not just the uploading of a document. A customer goes through document capture, OCR, identity matching, liveness checks, provider checks, and manual checks.
Explicitly verify negative test cases: assert system rejection and appropriate error states for blurry ID scans, fake IDs, drives scanned in poor lighting, mistakes from OCR, multiple names, multiple accounts, failures to ID, accepting unverified documents, timeouts due to the testing provider, and failures to provide a service.
Consider events asynchronously. A KYC service may provide a webhook when the user leaves the application. Events can be sent out of order. Your back end must reject outdated status changes and consider the last confirmed or rejected status.
Ensure audit logs and correlation IDs are retained at each test step, while mandating the immediate masking, tokenization, or automated cleanup of synthesized KYC PII to comply with storage limitation policies.
For Isolated Development, OTP hard-coding is convenient, but it is inadequate for a regression suite that simulates production. For the controlled source:
Test the use cases for timed codes, recently sent but definitively unused codes, code use limits, and code lockouts, in addition to locking a user out of the system due to failed login attempts. In all of these cases, previously issued codes must be invalidated when a new code is requested.
Biometric verification must test authentication failures, verification canceled intentionally, failed or unsuccessful scans, biometric lockout, changes to verification enrollment, biometric verification hardware missing or unavailable, and verifying the PIN. Biometric success must unlock an asymmetric private key stored securely on the device (Secure Enclave/StrongBox) to sign a server-generated cryptographic challenge, preventing simple boolean bypasses.
Scanning jailbroken and rooted devices. Implementing Frida, Objection, Burp Suite, and MobSF (Mobile Security Framework) to assess controls against SSL pinning, root detection, runtime rewriting protection, storage of insecure data, and data leakage.
Attempt to bypass client-side SSL pinning using dynamic instrumentation frameworks (e.g., Frida or Objection) to modify traffic, and evaluate the application's runtime defenses against compromised execution environments. Analysis of app crash logs along with cache information, screenshots, data in clipboard and SharedPreferences, Keychain, Keystore, property lists.
In the event of client side checks signaling at most once, powerful enforcement is provided on the server side. Make requests with invalid integrity check or attestation outcomes and check for server side rejections. Test for attestation tokens that are invalid, replayed, and mismatched
OWASP Mobile Application Security can be used as a coverage map. For each applicable requirement, link either an automated check, a manual check, or a documented risk decision.
Each payment transaction is modeled as payment states such as initiated, authorized, pending, settled, reversed, declined, and unknown. Transitions for all valid states are tested, and transitions for illegal states are negated.
A timeout is an unknown outcome that is not an automatic failure. The server may have processed the request before the failed connection. Upon reconnection the app should query the status of the transaction as opposed to making a new payment.
Your framework should confirm the following:
Confirm, auth, and settle transactions under force. This includes closing the app, toggling data, switching Wi-Fi and cellular manually and other similar techniques like placing the app in the background, rotating the device, or purposefully delaying callbacks.
Analyze 3 sources: API response, ledger entry, customer-visible transaction history. Balances, fees, reversals, notifications, and statements must be considered during reconciliation.
Payment gateways, KYC, and fraud services can be developed separately from the core banking system. Contract tests should support validation of input fields, input formats, error codes, signatures, and ANSI compatibility of various versions.
Build tests for timeouts and malformed responses, HTTP 429, duplicate webhooks, invalid signatures, and other server errors. Test events for bound back-off throttling with idempotent design and an eventual retry.
Sandboxes do not closely resemble production environments. Describe the differences. Thorough checks or certification environments provided by the vendor should be used to fill the major gaps.
Represent business cases involving peak transactions (e.g. peak payment transactions at pay-day or market surge). Capture payment duplicates, latency, errors and queue latency for reconciliation. Capture success and failure rates and latency of payment transactions for duped requests.
Test cold starts and warm starts, frame drops, battery use, memory use, crashes, ANRs, and longest transaction time for payment confirmation and authentication. Test payment flows in budget devices. Poor client performance results in backend congestion.
Think of emulators as ways to quickly check functionality on user stories. Reliable device attestation, Root detection, Hardware Security, biometrics, and OEM-specific behaviors need real devices. So, services such as push notifications and camera captures must be tested on the Go.
Build your device matrix with real production data. Look at data coverage for operating systems, manufacturers, hardware tiers, screen sizes, and types of biometrics. Also, consider some adverse devices, by pushing less common devices into regression cycles.
You must test TalkBack, VoiceOver, large text, contrast, focus order, and touch-target size. You must also test currencies, rounding, dates, and regional payment methods. Formatting defects should always be treated as financial defects.
Both deterministic and private results require the use of a synthesized covering set. Real production data from lower environments should never be used.
For each API, create test accounts with a known KYC, balance, beneficiary, device, and risk state. After each account creation, the account must be reset to the original state. To ensure manageability, OTP secrets and API keys for accounts must be generated and managed.
Use of deterministic data reduces random failures and prevents payment test failures from damaging the starting balance.
For the contract, service behavior, and infrastructure layers, API tools can be used for automating each of them respectively.
For adversarial checks, mobile automation can be used along the customer journey path; security tools can be used for checking.
For traffic control, load tools can be used. There is no single product that can take the place of this layered approach.
Drizz solves mobile UI regression for most teams. Its Vision AI recognizes elements on screens and removes the need for fixed selectors, and tests written in English are executed on real iOS and Android devices.
Drizz is built for pages that are constantly evolving, such as verification screens for password, MFA/KYC, biometrics, and similar. Automated Self-healing and deployment on-prem or on a VPC private cloud are offered. Concurrent API assertions, ledger checks, performance, and security are recommended.
Adjust CI/CD checks based on speed and risk:
A release report should include the build version, environment, device, test data set, security-control results, failed scenarios, accepted risks, and the outcome of financial reconciliation.
It is not the total number of tests that matter. What is important is the extent to which the final valid state of important transactions was attained and no negative effects were caused to other transactions, each security measure was enforced on the server, and each customer was provided the correct outcome.
The pattern across banks and fintechs is consistent, and most of it traces back to scale and regulation rather than tooling.
No single tool covers a banking app, so teams assemble a layered stack. The point is coverage at each layer rather than any one product.
Well, traditional automation fails at two places. The auth screens shatter selector based suites, and a bank's security review scrutinizes your testing tool as hard as your app.
On flows, Drizz drives app with Vision AI that reads rendered screen instead of querying a locator. An OTP field, an MFA step, or a biometric dialog is targeted by what's on screen, so a compliance driven UI change doesn't snap your selectors, and Drizz self heals step when a layout shifts.
The same plain English suite runs on real iOS and Android devices, where attestation, root detection, and biometric behavior are honest. Where an engineer on Appium authors around 15 tests a month, Drizz teams report closer to 200, with flakiness down from roughly 15% to about 5%.
On procurement, Drizz is SOC 2 Type II certified, runs on prem or in your VPC, and supports SSO and SAML, RBAC, audit logs, and encrypted APK storage, which maps onto GLBA, NYDFS, DORA, and RBI reviews. The enterprise mobile testing guide goes deeper.
Building a fintech mobile application requires more than just testing the UI. Authentication should be examined for verification of identity using the server. Each transaction should also save correctly to the ledger, and the system should allow safe retries and recoveries.
Test KYC, account access, payments, and reconciliation using your APIs and mobile App. Check how these workflows behave when network connectivity is lost, requests are geared twice, services provided by third parties respond sluggishly, or the application restarts, using physical devices. You should also perform security tests and check if unauthorized persons are able to access accounts or transact.
It is important to run sanity tests to ensure that transactions reach a conclusive state on all the systems after a release. For instance, a payment that is successful should be reflected on the mobile application, the transaction record, and the reconciliation.
Include these checks as part of your process for every release. This ensures your team has evidence to support the consistency of the application before the changes are released to the users.
This is where Drizz comes in, especially for fintech apps. It helps apps to automate end-to-end mobile tests while helping to keep those automation suites reliable even when the mobile application changes.
A redditor on r/mobiledev shared something we wish we should have said first - “AI assisted testing's biggest benefit was catching repetitive UI regressions faster, rather than replacing QA”. That’s what Drizz stands by.
Related Content:
Mobile app security testing | Test login functionality on mobile | Mobile app testing checklist | Book a demo
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