Azure Fabric analytics and Dynamics 365 readiness for Bank Center Credit

Bank Center Credit (BCC) required an enterprise-grade analytical platform to consolidate heterogeneous data, provide real-time reporting to 3,000+ users and establish a secure foundation for future ML/AI. Awara IT implemented a Microsoft Azure Fabric-based data platform—branded Benefitis—to centralize reporting, enable near real-time analytics and enforce bank-grade information security.

The project delivered a governed OneLake architecture, data engineering pipelines, and SQL/real-time endpoints designed for both operational reporting and advanced data science. The solution preserves multicloud ingestion, supports future integrations with Dynamics 365 and Power Platform, and reduces time-to-insight for business leaders and risk teams.

Client / Industry / Country

Bank Center Credit (BCC) is a Kazakhstan-based financial institution operating in the Banking & Insurance sector, serving retail and corporate clients across Kazakhstan with a staff and user base that requires enterprise-scale data and reporting capabilities.

Business challenge

BCC’s legacy reporting environment consisted of fragmented data stores and scheduled extracts with long refresh cycles. The bank needed an analytical tool capable of consolidating transactional, market and third‑party data from multiple clouds and on-prem sources to support regulatory reporting, risk monitoring and commercial analytics.

Key pain points included high data latency (daily or multi-hour batches), limited self-service for 1,000s of business users, lack of a unified data catalog and insufficient isolation/security controls required by Kazakhstan banking regulation. BCC also wanted a platform that would scale to support future ML/AI workloads without a disruptive rearchitecture.

Why Dynamics 365 was selected

Selection criteria prioritized a Microsoft-native stack for long-term compatibility with the bank’s existing Azure estate. Azure Fabric and OneLake were chosen because they provide unified storage and compute primitives that simplify governance, accelerate data engineering and reduce operational overhead compared with multiple point solutions.

Although the project focused on enterprise reporting and DWH capabilities, the architecture was deliberately designed to enable downstream integrations with Dynamics 365 Finance/Customer Engagement and the Power Platform. That ensures BCC can extend analytics into ERP/CRM workflows and apply model outputs to front-office processes without replatforming.

Modules implemented

• OneLake (centralized data lake and governance)
• Fabric Lakehouse and Tables for managed storage
• Data Engineering pipelines (ETL/ELT) and streaming ingestion
• SQL Endpoints and real-time query acceleration
• Security & governance layer (RBAC, encryption, data masking)
• Power BI integration and self-service semantic layer
• ML/AI foundation (workspace, feature store readiness)

Integrations

• Core banking systems (transactional feeds)
• Multicloud sources (AWS and GCP object stores and APIs)
• Third-party market data feeds
• Azure Active Directory and HSM for key management
• SIEM and logging (Azure Monitor/Log Analytics)
• Planned: Dynamics 365 Finance and Customer Engagement integration

Localization & compliance

The implementation adhered to Kazakhstan banking regulations for data residency and operational resilience. Data at rest and in transit were encrypted using Azure-managed keys with optional HSM for critical datasets; role-based access controls and audit trails were implemented to meet the bank’s internal compliance and regulator expectations. Reporting templates and metadata support Russian and Kazakh language labels to meet regional business requirements.

Business value

BCC now operates a single, governed data platform that serves both regulatory reporting and commercial analytics needs. Shorter time-to-insight enabled faster risk decisions and more frequent product performance reviews; consolidated datasets reduced operational reconciliation work and lowered the total cost of ownership for reporting infrastructure.

Crucially, the platform provides a clear path to operationalize ML/AI models and integrate outcomes into Dynamics 365 and other line-of-business systems. That extensibility allows BCC to prioritize next‑phase projects—fraud detection, customer lifetime value scoring and automated credit decisioning—without reworking the data foundation.