Forbes

How Financial Services Can Enable Modern Data Platforms For Digital Transformation

Chief Strategy Officer at Lightbits Labs, making high-performance storage simple, agile and cost-efficient for any cloud.

Big data is transforming financial services by improving forecasting, risk analysis, customer satisfaction and more. The massive datasets driving these advances, though, require organizations to rethink their resources, processes and especially data platforms.

Financial services companies tend to be early tech adopters under the constant pressure of high stakes and fierce competition. But data center storage performance and capacity challenges can prevent them from extracting maximum value from their big data. As a result, they risk losing their competitive advantage in this new digital economy.

The potential for reward is high. The financial services industry (FSI) grew 9.9% last year and could continue at a 6% growth rate through 2025 to reach $28.5 trillion. To grab their share of that market, FSI companies need modern data platforms that can rapidly store, access and analyze massive amounts of data. Extracting value from their data can result in tremendous business advantages, such as personalized marketing, new services creation, process automation and fraud detection and prevention.

Digital transformation is a competitive necessity for FSI organizations. But success lies in transforming their culture and operations and modernizing their aging data storage architectures.

FSI Priorities And Pain Points

Exponential data growth is putting a tremendous strain on legacy storage systems initially architected for spinning disk drives. To complicate the situation, the dynamic nature of modern applications requires storage infrastructure that reliably supports instant data access at scale, delivers high-availability service and provides enough throughput to feed accelerated compute servers.

FSI companies rely increasingly on data stored in databases, data warehouses and data lakes. However, traditional data lake storage architectures couple compute and storage resources, whereby increasing one resource requires increasing the other in lockstep. This type of data center implementation results in high capex and opex.

Some of the important aspects of digital transformation for FSI organizations to keep in mind include considering how to achieve:

• Improved forecasting and risk analysis. Investing incurs risk. Analyzing market and economic trends fast enough to quickly act for financial gain is paramount. Traditional storage architectures that tightly couple compute and storage resources, however, lack the scalability and resilience to component and system failures to reliably support sub-second analyses and decisions.

• Greater customer intimacy and inferencing. Armed with customer trend data, banks know which financial products to pitch to each customer, a predictive capability called inferencing. Banks prefer to distribute this data out to branch locations to increase access speed and shorten the time to insight—a strategy that requires newer, disaggregated storage architectures.

• Accelerated microservice storage access. Container technology such as Kubernetes can create cloud-native applications that are decomposed into hundreds or thousands microservices. And virtualization platforms, like VMware, provide better isolation, security, portability and management of applications in a way that was not possible before. However, both containerized and virtualized environments need simultaneous access to highly-available and persistent storage, driving the need for modern, software-defined data platforms that can keep pace.

• Reduced data infrastructure costs. Like other companies, FSI companies stand to benefit from commodity storage hardware components that are quickly and easily replaceable in the event of a failure. This helps them contain costs as they grow.

Data aggregation difficulties inhibit digital transformation in insights based only on partial or incomplete data that can be skewed, which leads to poor business outcomes. Meaningful analytics require comprehensive, accurate and up-to-date data.

The Data Scalability Factor

These factors have created the demand for more agile, simple and cost-efficient data storage that easily and affordably scales to satisfy digital transformational goals.

Modeling their infrastructures after those of cloud service providers, for example, helps FSI companies meet these requirements. In the cloud, all resources are virtualized, and configuration and management are software-defined. A cloud-enabled setup delivers access to the following.

• A disaggregated architecture that offers the ability to independently scale storage and compute resources, both for maximum performance and to avoid costly resource overprovisioning.

• The flexibility to move storage resources dynamically to meet the low-latency infrastructure requirements of transactional workloads.

• API-driven software-defined capabilities to flexibly grow and move storage resources dynamically as business demands require.

• Support for complex analyses across huge data stores aggregated from numerous sources in different formats.

One way that FSI companies can work with this approach is with disaggregated NVMe/TCP storage. In addition to decoupling storage and compute resources for independent scaling, NVMe/TCP builds in resiliency with redundant components at the disk drive, power supply and CPU levels and with replication technology and erasure coding protection between nodes and data centers.

Common Pitfalls To Avoid In Your Digital Transformation

Digital transformation offers the promise of operational optimization and has become a necessity to stay relevant and deliver value, but few FSI organizations achieve success. Some of the most common pitfalls to avoid include lack of in-house expertise, unclear objectives, internal resistance and ignoring data.

Lack of in-house expertise can significantly impact a successful outcome; therefore, organizations with these critical knowledge gaps should look to outsource expertise to implement their digital transformation agenda. Develop a well-articulated strategy with specific, measurable and achievable goals that align the organization on common objectives.

Every employee should also understand what they are doing and why it’s important. Break down silos and organize toward a culture that embraces change. The leadership team is responsible for squashing internal resistance and painting a clear picture of the target culture, which is on par with the common objectives.

Lastly, don’t ignore your data. Organizations that embrace digital transformation miss a huge opportunity for success when they fail to extract insights from their data. Modern data management is a critical step in your digital transformation.

Conclusion

Digital transformation among highly competitive FSIs is placing new processing and aggregation burdens on traditional storage architectures, creating bottlenecks and holding FSIs back from realizing key digital transformation goals. Addressing resource and process challenges along with a strong technology approach, however, can help FSIs harness their big data to their full potential, even as it grows exponentially in the coming years.