TL;DR:
- Solaris, a banking technology specialist, adopts Snowflake’s Data Cloud to enhance data team productivity and enable end-users to create their own products.
- The company aims to develop an enterprise-wide data strategy by defining objectives, business processes, regulatory requirements and addressing skills gaps.
- Snowflake’s strong governance, security features, and consumption-based pricing align with Solaris’ goals for innovation and scalability.
- The transition to Snowflake involved migrating 70 data sources and empowering domain teams to build data products.
- Solaris benefits from Snowflake’s training and support services to optimize data pipelines and connections.
- 40% of Solaris employees now have direct access to Snowflake, democratizing data usage.
- The adoption of Snowflake has facilitated machine learning applications for regulatory reporting, fraud detection, and KYC checks.
- Future plans include expanding Snowflake usage, developing self-service interfaces, and exploring AI applications for unstructured data and enhanced search capabilities.
Main AI News:
Banking technology specialist, Solaris, has embraced Snowflake’s Data Cloud to elevate the efficiency of its data team and empower end-users to create their own innovative products. Solaris, renowned for offering Banking-as-a-Service solutions to financial institutions worldwide, embarked on a journey to maximize the potential of its existing data resources. Roy Ben David, Group Director of Data and Analytics at Solaris, emphasized the importance of establishing a comprehensive enterprise-wide data strategy as the starting point: “In order to drive our vision, we first delineated our objectives, identified the business processes to address, acknowledged regulatory mandates, and assessed the skills gap that required filling. Subsequently, we embarked on the quest to select the technology that would breathe life into our vision.”
In scrutinizing the available options, Ben David’s team scrutinized whether Snowflake, with its robust governance and security features tailored for the banking sector, aligned with their objectives. Solaris was particularly drawn to Snowflake’s flexible pricing model, which resonated with Ben David: “I have a preference for cost-efficient solutions that align with our growth trajectory. Snowflake’s consumption-based model resonated with us, allowing for scalability in tandem with our expansion.”
Ben David’s primary goals included enhancing his team’s innovative capabilities and empowering business users to construct their own data-driven products. His aspiration was to dissolve bottlenecks and steer the organization toward more agile problem-solving. In addition, he aimed to bridge the gap between domain-specific teams within the company and their data, thereby equipping them to not only gain a clearer perspective of high-quality data but also enable them to independently develop data products.
In Ben David’s vision, domain experts would identify data-driven opportunities, while his data team would assume the role of enablers. This shift in mindset and approach would stimulate innovation, including the integration of machine learning into the company’s operations to create sophisticated products that outperform competitors, transcending traditional reporting and analytics.
Embracing a Novel Platform
The transition to Snowflake was not without its challenges, given the complexity of migrating 70 data sources. However, the migration to Snowflake, which commenced in April 2022, concluded successfully in January 2023. Ben David elaborated on the process: “We categorized various business areas into domains and not only distributed data to these domains but also established data products within them. After nine months, stakeholders within these domains were empowered to construct new data products using Snowflake as their foundation.”
Following implementation, Solaris benefited immensely from Snowflake’s training and support package, which fine-tuned the platform’s functionality as the project progressed. Ben David shared his perspective: “We were keen to optimize our workflow using Snowflake more efficiently. Snowflake Professional Services guided us through our data pipelines and connections, delivering outstanding results.”
Today, Solaris employs Snowflake on a daily basis, providing secure access to data for a substantial portion of its workforce. Previously, only a fraction of Solaris employees, ranging from 5% to 10%, had access to data. This figure has now risen to 40%, as more professionals routinely utilize the platform. Ben David noted: “Our employees now have access to the tools they require for their roles, and we can manage access more effectively.”
Furthermore, employees have become proactive in identifying data issues, simplifying the process for end-users to develop their own data products. This shift has democratized data utilization, making Snowflake an essential tool for process improvement.
Exploring Emerging Technologies
The rapid adoption of Snowflake has unlocked new possibilities for Solaris, particularly in the realm of machine learning (ML). By harnessing Snowflake to power regulatory reporting, Solaris staff can create and train ML models in AWS SageMaker, enhancing fraud detection and Know Your Customer (KYC) checks: “We identified specific business challenges and tasked data scientists with creating models to address them. They could easily access our KYC domain on Snowflake, which centralizes insights, seamlessly transfer it to AWS SageMaker, train models, and achieve the desired outcomes.”
The next objective is to expand the utilization of Snowflake by building additional self-service interfaces through Streamlit, an open-source framework enabling professionals to develop data applications. These interfaces will seamlessly integrate with Snowflake, delivering added value to stakeholders while maintaining user-friendliness.
Furthermore, Solaris is exploring the application of Artificial Intelligence (AI) to meet regulatory requirements within the finance industry. This includes extracting insights from unstructured data sourced from PDFs and enhancing search capabilities for non-technical stakeholders. Ben David envisions that these capabilities will attract more users to Snowflake, enabling them to pose natural language queries that the system will translate into executable code. This forward-thinking approach exemplifies Solaris’ commitment to innovation and leveraging cutting-edge technology to gain a competitive edge in the banking sector.
Conclusion:
Solaris’ strategic embrace of Snowflake’s Data Cloud not only enhances internal data capabilities but also positions the company as a forward-thinking innovator in the banking technology sector. The democratization of data access and the integration of machine learning and AI capabilities are expected to drive Solaris’ competitiveness and market relevance, offering customers more sophisticated and efficient solutions in the dynamic financial services landscape.
