01
Payment rails and orchestration
Integrations with acquirers, PSPs, and open banking providers, with retries, idempotency, webhooks, and clear failure states.
Payments · ledgers · insight
Industry focus
FinTech
Payment products, ledgers, and risk-aware platforms that treat money movement, identity, and compliance as core product design.
Financial software fails in public: incorrect balances, weak fraud controls, or brittle payment rails damage customers and regulators alike. We design systems where money movement is explicit, reconcilable, and observable.
Our work spans consumer and B2B fintech, card and open-banking style payments, wallet and ledger backends, KYC/AML workflows, and operational dashboards for finance and risk teams.
We treat PCI DSS scoping, PSD2/SCA where relevant, and fraud monitoring as architecture decisions, not bolt-ons after launch.
How Technisal helps
How Technisal supports FinTech
We help product and engineering teams ship payment and financial platforms with clear ledgers, controlled integrations, and measurable risk posture.
02
Tokenisation and PCI-aware design
Keep card data out of your scope where possible via tokenisation partners, vault patterns, and network-token friendly flows.
03
Double-entry ledgers and reconciliation
Immutable journal models, multi-currency balances, and reconciliation jobs against bank and processor statements.
04
KYC, AML, and onboarding
Identity verification, screening hooks, risk scoring inputs, and case management for compliance operations.
05
Fraud monitoring and SCA flows
Rules and signals for abuse detection, step-up authentication, and PSD2/SCA-aligned customer journeys where required.
Our approach
A practical path from shared understanding to durable outcomes in fintech.
- 1
Define money and identity state machines
Model payment, payout, refund, and onboarding states before UI polish, so every transition has an owner and an audit event.
- 2
Minimise PCI and sensitive data scope
Route card and sensitive auth data through compliant providers; design your app around tokens and references.
- 3
Build the ledger as the source of truth
Application balances derive from journal entries; reports and customer balances reconcile to the same core.
- 4
Instrument risk and ops early
Dashboards for exceptions, fraud queues, settlement lag, and webhook failures, not only happy-path metrics.
Outcomes we aim for
Reconcileable money movement
Transactions, refunds, and fees that can be explained to finance, support, and auditors without spreadsheet archaeology.
Controlled compliance surface
Clear boundaries for card data, SCA, and KYC evidence so you know what is in scope and what is delegated.
Faster, safer product iteration
Idempotent APIs and explicit states reduce incident risk when you add new payment methods or markets.
What you receive
- Payment and ledger domain model with state diagrams
- PSP/open-banking integration with webhook handling
- Tokenisation and PCI scope reduction plan
- KYC/AML workflow and case-tool integration
- Fraud and exception monitoring dashboards
- Reconciliation jobs and ops runbooks
What careful delivery considers
Domain realities that shape architecture, compliance, and product choices, addressed explicitly in our work.
PCI DSS is about scope as much as controls
The fastest path to a maintainable programme is often not storing or transmitting raw card data. Architecture choices determine how much of the DSS applies to your environment.
SCA and open banking change UX
Strong customer authentication and account-to-account payments introduce redirects, challenges, and delayed confirmation. Product design must absorb these, not fight them.
Ledgers without reconciliation are theatre
Pretty balance UIs mean little if they drift from processor settlement. Build automated matching and exception workflows from day one.
Common questions
Do you replace our payment service provider?
Usually not. We design around PSPs and banks you choose (or help evaluate), focusing on orchestration, ledgers, risk workflows, and product experience above the rails.
Can you support multi-currency and multi-entity products?
Yes. We model currencies, FX, and legal entities carefully in the ledger so reporting and payouts remain consistent as you expand.
How do you approach fraud without a large data science team?
Start with high-signal rules, velocity checks, device and behavioural features you can operate, and clear case queues. ML models can follow once labels and process are solid.
Ship financial products with clear money truth
Share your payment model, markets, and compliance constraints. We will outline an architecture and delivery plan that finance and engineering can both trust.