KYCentrum

AT A GLANCE

A European finance provider needed to strengthen fraud prevention and customer verification across its digital banking operations. The existing process created too much manual work for risk and compliance teams, while growing transaction volumes made fraud monitoring harder to manage with static rules alone.

Computools helped develop a platform that monitors transactions in real time, flags suspicious activity, supports automated KYC checks, and gives compliance teams a structured environment for case review, reporting, and audit preparation.

The solution reduced confirmed fraud cases by 41%, lowered false-positive alerts by 52%, shortened customer onboarding time by 50–60%, and helped compliance teams resolve cases 63% faster.

THE CLIENT

The client is a European finance provider with branches in Estonia, Latvia, and Lithuania. The company serves private and business customers through banking, payments, cards, loans, leasing, savings, pensions, investments, and private banking services.

Its operations cover both everyday financial services and more complex customer journeys, including remote onboarding, lending, investments, and digital payments. In this environment, fraud prevention, customer verification, AML checks, and compliance reporting had to remain reliable as digital activity continued to grow.

BUSINESS CHALLENGE

The client needed to strengthen fraud prevention and customer verification across a growing digital banking environment. Existing fraud detection relied heavily on static rules and manual reviews, while KYC workflows required too much analyst involvement.

This created several operational risks:

slow onboarding and verification processes;
high false-positive alert rates;
limited fraud detection accuracy;
heavy operational load on compliance analysts;
disconnected fraud, KYC, AML, and reporting workflows;
increasing exposure to PSD2, GDPR, DORA, and SOC 2-related audit requirements;
high operational costs linked to manual compliance checks.

The finance provider needed a unified platform that would support its cybersecurity strategy, improve fraud-detection accuracy, automate KYC processes, and ensure long-term regulatory alignment.

SOLUTION SUMMARY

Computools helped develop a fraud detection and automated KYC platform that combines real-time transaction monitoring, configurable rule-based logic, ML-supported fraud scoring, and compliance workflow automation.

The platform supports:

real-time transaction evaluation and anomaly detection;
fraud scoring based on behavioral, transactional, and rule-based signals;
automated document verification and liveness checks;
sanctions screening and AML enrichment;
case management for fraud and compliance analysts;
explainable decision logic for flagged transactions and customer profiles;
audit trails and compliance-ready reporting;
integration with existing banking infrastructure.

This unified approach reduces manual reviews, accelerates onboarding, and improves regulatory compliance.

IMPACT

The platform delivered measurable improvements across fraud operations and compliance:

confirmed fraud cases decreased by 41%;
false-positive alerts decreased by 52%;
customer onboarding time was reduced by 50–60%;
compliance case resolution became 63% faster;
operational compliance costs decreased by 20–30%;
the organization reached ROI within 6 months.

The client also improved audit readiness through explainable decision logic, complete traceability, and centralized records for fraud and KYC workflows.

WHY COMPUTOOLS

Computools was selected because the client needed an engineering partner with experience in banking software development, regulated financial systems, backend development, integration-heavy architecture, and compliance-oriented workflows. The team approached the project as a risk-and-compliance implementation, where speed alone was not enough. The platform had to process live financial data, support analyst decisions, protect sensitive customer information, and provide transparent records for internal and external review. Computools helped build a system that combined operational automation with the reliability expected in a banking environment.

STORY IN DEPTH

Background

Before the project, the client’s fraud and KYC operations depended on a combination of legacy rules, manual checks, and separate tools used by risk and compliance teams. Fraud analysts had to review a high volume of alerts, many of which turned out to be false positives. KYC analysts handled document verification, liveness checks, sanctions screening, and case review, but there were too many manual steps. This slowed onboarding and increased pressure on internal teams.

The client needed a platform that could integrate fraud detection, KYC verification, AML checks, case management, and audit reporting into a single, controlled environment.

Approach to solution

Computools approached the project as a real-time risk-monitoring and compliance-automation platform, focusing on transaction monitoring, customer verification, risk decisioning, and case review.

The team structured the system to process live data, apply configurable rules, integrate with KYC and AML services, and give analysts clear context for every flagged transaction or customer profile. UX design was critical for the platform: compliance teams needed fast access to risk signals, case history, verification results, and explainable decision logic without digging through disconnected tools.

Computools role

Computools contributed to backend development, integration logic, workflow automation, and platform architecture.

The team worked on:

backend services for fraud and KYC workflows;
transaction monitoring logic;
API orchestration between internal systems and external verification services;
rule-based decision workflows;
case management functionality;
audit trail and reporting logic;
secure data handling for sensitive customer and transaction information;
integration support for monitoring and operational visibility.

Key decisions and outcomes

The platform was built around a hybrid decision model that combined ML-supported fraud scoring with transparent rule-based logic. This gave compliance teams automated risk detection without losing explainability.

Fraud alerts, KYC checks, sanctions screening, AML enrichment, and case review were integrated into a single operational flow. QA testing covered performance, rule logic, verification workflows, and audit trail consistency before launch.

As a result, the client reduced confirmed fraud cases by 41%, lowered false positives by 52%, shortened onboarding time by 50–60%, and improved case resolution speed by 63%.

Design

The design focused on investigation speed, decision clarity, and reduced cognitive load for fraud and compliance teams.

USER PERSONA → SITE MAP → WIREFRAMES → USER INTERFACE

USER PERSONA

A detailed profile created to guide dashboard logic, case review workflows, alert prioritization, and audit-ready decision tracking.

SITE MAP

A hierarchical structure created to organize fraud alerts, KYC checks, AML screening, case review, and compliance reporting.

WIREFRAMES

Low-fidelity layouts were prepared to simplify alert review, KYC verification, case timelines, risk scoring, and compliance reporting.

USER INTERFACE

A clear, data-focused environment built using modern UI design principles for fast, high-accuracy decision-making.

DIGITAL PLATFORM & TECHNOLOGY

JAVA / SPRING BOOT

Java and Spring Boot supported backend services, business logic, API orchestration, case workflows, and integration with fraud, KYC, AML, and reporting components.

PYTHON / ML MODELS

Python-based ML models supported anomaly detection, adaptive fraud scoring, pattern recognition, and periodic model updates to handle evolving fraud scenarios.

APACHE KAFKA

Apache Kafka supported real-time transaction streaming and event processing, allowing the platform to evaluate transaction activity with minimal delay.

POSTGRESQL

PostgreSQL stored structured case data, customer verification records, fraud events, decision logs, and audit trails.

RULE ENGINE (Drools / Camunda)

The rule engine supported configurable fraud and compliance logic, helping analysts and risk teams adjust decision rules without rebuilding the entire system.

XAI MODULE

The explainable AI module helped compliance teams understand why specific transactions, documents, or customer profiles were flagged.

KYC / AML INTEGRATIONS

KYC and AML integrations supported document verification, liveness checks, sanctions screening, watchlist matching, and customer risk enrichment.

TLS 1.3 & HSM KEY MANAGEMENT

Modern encryption and secure key storage supported secure data transmission and protected sensitive customer and transaction information.

AZURE MONITOR & SENTINEL

Azure Monitor and Microsoft Sentinel supported operational monitoring, security visibility, incident logging, and resilience tracking.

PROJECT MANAGEMENT METHODOLOGY

Scrum enabled iterative, controlled delivery of ML models, streaming pipeline components, verification modules, and investigation dashboards. Short development cycles allowed the team to validate each increment with compliance officers, ensuring continuous regulatory alignment, high usability, and predictable progress throughout the project.

WHAT OUR CLIENT SAID

Before working with Computools, our fraud and verification workflows were too fragmented. Analysts had to switch between tools, manually review too many alerts, and spend extra time preparing cases for compliance checks.

Computools helped us build a platform that brought these processes into one clear workflow. Real-time monitoring reduced alert noise, automated KYC made customer checks faster, and explainable decisions helped our analysts understand why each case was flagged. The biggest value for us was not only speed, but better control and transparency in daily risk operations.

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