A1 — Applied Intelligence
Financial Systems
Engineering trust into every transaction
Applied domain A1
Financial systems demand precision, reliability, security and complete traceability. We build technology for environments where every transaction matters and every decision must be explainable.
When the numbers matter, the infrastructure behind them matters even more.
- Risk & scoring systems
- Transaction processing
- Financial data platforms
- Regulatory reporting
- Fraud detection
- Audit-ready architectures
- Decision-support systems
- High-volume financial analytics
The real problems
The real problems → Our approach
- 01
Decisions that must be explained
Credit and fraud decisions increasingly come from models, yet customers, auditors and regulators still need to know why. A score without reasons is a liability.
Our approachExplainable scoring
Rules and machine-learning models run as a single ensemble, and every decision carries its reason codes and factor contributions — readable by an analyst and reportable to a regulator.
- 02
Speed and certainty together
Payment authorisation leaves very little time for a fraud check. A false decline loses a customer; a missed fraud loses money. Latency and accuracy have to be engineered together.
Our approachEvent-driven transaction processing
Transactions flow through an event backbone with idempotent processing and ordered, replayable streams. A retry never counts a payment twice, and any day can be replayed for investigation.
- 03
Data spread across core systems
Core banking, cards, digital channels and third-party feeds each hold part of the picture, often with different identifiers and update cycles. Reconciling them by hand is slow and error-prone.
Our approachAn immutable decision log
Each decision is recorded with the model version, input features, thresholds, the analyst who acted and when. Audit questions are answered with a query, not a reconstruction.
- 04
Regulation that keeps moving
BDDK, MASAK and SPK requirements evolve, and every change touches data definitions, controls and reports. In systems built without traceability, each audit turns into a project of its own.
Our approachControlled change
New models run as challengers against the current champion on live traffic before promotion, and every rule change is versioned and approved before it takes effect.
The product for this domain
VARDA Prism
Explainable risk, scoring & fraud intelligence
Every decision, split into its spectrum.
Real-time transaction scoring that combines rules and machine learning, with reason codes, case management and an immutable log for every decision.
- Real-time scoring
- Reason codes for every decision
- Case management and reporting
- Immutable decision log
Illustrative scenarios
Illustrative scenarios
Scenarios are illustrative; they do not describe specific clients.
- 01
Real-time card fraud scoring
ContextA mid-sized participation bank flags card transactions with static rules. Analysts work through long queues of alerts, most of them false, and cannot see why a rule fired.
OutcomeRules and a gradient-boosted model score each transaction together, with reason codes attached. Analysts work a shorter, prioritised queue and can explain every decline to the customer.
- 02
Regulatory reporting from one source
ContextA leasing company prepares its regulatory returns from spreadsheets assembled by finance and operations. Every reporting period brings manual reconciliation and late corrections.
OutcomeReports are generated from a governed data model with lineage back to the source systems. Figures reconcile automatically, and every number can be traced to the records behind it.
- 03
Suspicious-transaction monitoring
ContextA payment institution must screen transfers against sanctions lists and flag suspicious patterns for MASAK reporting, but its monitoring runs as an overnight batch.
OutcomeScreening and pattern detection move into the transaction stream. Cases open with their evidence attached, and each decision is logged for audit.
Compliance & governance
Compliance & governance
- Designed to support the BDDK regulation on banks’ information systems, including access control, audit logging and change management.
- Designed to support MASAK obligations for monitoring and reporting suspicious transactions.
- Designed to support KVKK requirements through data minimisation, masking and logged access to personal data.
- Designed to support SPK record-keeping and reporting requirements for capital-markets institutions.
- Designed to support ISO/IEC 27001-style controls: encryption, segregation of duties and immutable audit trails.
Frequently asked questions
Frequently asked questions
01Can the system run entirely on our premises?
Yes. Financial deployments are designed on-premises first: models, feature store, decision log and case management all run inside your data centre with no dependency on external services. Private-cloud or hybrid set-ups are possible where your policies allow them.
02How do you explain a machine-learning decision to a regulator?
Each score is stored with its reason codes and the contribution of every factor, together with the model version and thresholds in force at that moment. Model documentation covers training data, validation results and known limitations. Together they let you reconstruct and justify any individual decision.
03Does this replace our core banking system?
No. We work alongside core systems, not instead of them. Data is read through change data capture or existing interfaces, and decisions are returned through APIs that your core and channel systems call. The core remains the system of record.
04How do you keep false positives under control?
By treating them as a cost to be measured rather than an acceptable side effect. Thresholds are tuned against the real cost of each error type, analyst feedback flows back into training, and no model change reaches production before it has been compared as a challenger on live traffic.
Let’s design the right architecture for financial systems.
Risk scoring, fraud detection, transaction processing and regulatory reporting, built for precision, full traceability and decisions you can explain.