Data Unbound: Dive Into the Possibilities
For decades, the banking industry has possessed a wealth of underutilized customer data. The need for change is evident, and it needs to happen swiftly. Regardless of the desired outcome, be it an enhanced customer experience, improved risk management, insight-driven interactions, or personalized service delivery, achieving digital success at scale hinges on real-time data access coupled with advanced analytics and AI.
Unlock Data Composability With Finacle
Crafted on the pillars of layered OLTP and OLAP architecture, real-time data processing, and embedded insight principles, the Finacle Digital Banking Platform lays a robust groundwork. It empowers banks to seamlessly handle, sustain, and disseminate data at scale—a vital element for propelling cutting-edge banking innovations.
It’s time to elevate your banking operations and engagements with data foundations built for the future.
Accelerate Data Readiness with Finacle Data Platform
Unlock the full potential of your data and accelerate your AI readiness with the Finacle Data Platform. This powerful platform, driven by a robust data pipeline, efficiently captures, extracts, curates, and delivers high-quality data for diverse applications, including analytics, reporting, and AI. The platform's advanced data stores balance velocity, veracity, volume, and variety, providing a unified data estate. It uses a tiered structure aligned with Finacle’s CQRS pattern, separating OLTP and OLAP workloads. Data seamlessly flows from OLTP systems to OLAP data stores and the Finacle Data Lakehouse through event streaming and asynchronous interfaces. With sophisticated low-code configuration options, integration from various data sources is simplified, and data cleansing and transformation are expedited. Built-in data security, observability, and governance features ensure that banks can confidently future-proof their data strategies.
Bian Inspired Data Model, Designed With Domain-Based Data Marts
Elegantly designed, the Finacle Data lakehouse employs domain-based data marts for expansive datasets. Decentralizing data ownership through these domain-oriented marts fosters a self-serve infrastructure, ensuring efficient handling of diverse data within specific domains. This model promotes agility and autonomy, enabling teams to seamlessly access, manage, and derive insights from their datasets.
