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Investment banking and retail banking often appear near the top of the list of industries investing in “Big Data” technology, but adoption and usage of “Public Cloud” offerings is very limited.
Thesys Technologies was founded in 2009, in the midst of the financial crisis. Thesys’ mission is the democratization of the financial market through the application of technology. Our core belief is that technology is the most effective means to “level the playing field” for all market participants.As an early adopter of the AWS cloud in 2007, cloud technology has been an integral piece of our big data and analytics platform since Thesys’ inception. It is the technology powering the SEC MIDAS (Market Information and Data Analysis Systemsystem), which was deployed in just 6 months by leveraging the cloud infrastructure.
“Technology is the most effective means to ‘level the playing field’ for all market participants”
Big Finance will get in the Cloud—but it will take some Time
Having now used the Cloud extensively for almost a decade, we at Thesys can see that the Cloud has grown up. We like to say, “The Cloud is ready for finance, but Big Finance is not quite ready for the cloud.”
If deployed correctly, the capabilities of the Cloud to provide a secure platform are remarkable. In some ways, it is easier to create a secure system in the Cloud than in a data center,but the question is—are the banks ready to commit? Five years ago when we discussed utilizing cloud technology with CIO’s and other senior technologists at big banks, they would say, “We can probably never use that.” Today, when we speak to those executives we hear, “Well, eventually we will have to be able to use it, but for now, compliance is holding us back.”
This is exactly the state of the Federal Government 4 years ago when we first proposed the MIDAS system to the Securities and Exchange Commission. In the end, the Commission was inspired by the overwhelmingly positive economics the cloud provided. So they followed the newly-minted FedRAMP guidelines, and they let us deploy their system in the cloud, which was a huge success.
Perhaps a more impactful example of the adoption of the Cloud in finance is the Consolidated Audit Trail. The final three bidders) for CAT each proposed a deployment of their solution in the Cloud. Pursuant to SEC Rule 613, CAT will be the largest financial datastore and analytics platform, with the primary goal of creating a single, comprehensive audit trail to enhance regulators’ ability to surveil the US securities markets in an effective way. The reporting requirements and technology infrastructure must be adaptable to changing market structures and reflective of trading practices, as well as scalable to handle increases in market volumes.
What is needed is a financial equivalent of FedRAMP—call it “BankRAMP,” to set the procedures and guidelines for deploying banking systems in the cloud, and allow banks to utilize the Cloud benefits.
Financial Big Data Grows up
The driving force behind big data technology is regulatory or legal requirements, a desire to improve agility and the pursuit of IT cost savings.
More data is being created than ever before, and tougher questions are being asked of the data. Institutions started experimenting with off-the-shelf Big Data technology and quickly realized that off-the-shelf technology is not sufficient for financial Big Data and they are playing catch up with Big Data concepts, whichdo not exist within their legacy systems.
Most off-the-shelf Big Data technologies originated in advertising and online retail industries, and are therefore tuned for different data models. They favor indexing and storing rich objects and establishing the links between them. Financial transactions like electronic trading use long, time-ordered series of orders, acknowledgments, and trades, all linked together—often by relative time relationships, rather than direct relationships such as “likes” or “is friends with”. Some financial datarequires complicated transformation to be valuable for analytics and is not handled efficiently by current Big Data technology. Finally, many of these off-the-shelf systems lack security features, such as fine-grained, role-based access control and data at rest encryption.
Many legacy systems within the banks use data stored in a self contained repository, for which software was specifically developed to access and present the data in a human-readable form. Banks have to first unravel their traditional systems and implement Data as a Service (DaaS) concepts that can provide data on demand to each user regardless of geographic or organizational separation between provider and consumer. This concept fits well with the Service-Oriented Architecture (SOA) many organizations have adopted, as it renders the actual platform on which the data resides, enabling both business users and data scientists to fully realize the value of big data.
Buzzwords Start to Converge Cloud, Big Data and IoT
The technology is still in its early days, but data from devices in the Internet of things will become one of the “killer apps” for the Cloud. Leading cloud and data companies such as Google, Amazon Web Services and Microsoft are bringing IoT services to life, allowing seamless movement of data to cloud-based analytics engines. Additionally, new players are disrupting traditional banking services by providing a user experience geared towards individual consumers, focusing on solving specific problems through data-driven technology. These startups are taking advantage of the cloud infrastructure and other non-core services that can be outsourced to deliver service through all available channels.These companies are tech savvy, but often lack financial subject matter expertise. This knowledge gap provides an opportunity for financial institutions that understand the challenges of the business to outperform the newcomers and gain market share. To accomplish this, financial institutions must use cloud resources to level the playing field, starting by integrating their proprietary data with structured and unstructured data from multiple sources and including it in their analytics engines. Making DaaS, analytic tools, and infrastructure to experiment available to employees can become a huge driver for innovation while enabling the organization to become more agile.
The Agile Organization—Not a methodology but a Mindset
Many organizations have implemented Agile Development methodologies to address changes in business requirements faster and deliver value earlier. Technology should not be viewed as a cost center or support function for the business, but as the primary platform to provide and deliver products. To stay competitive, business leaders need a deep understanding of their business and the technology landscape as a whole. The role of the CIO is changing—it is not just about delivering technology, but about having a deep understanding of the business problem to be solved.
Using big data and analytics will enable banks to tailor their services to a specific customer or customer group. Public cloud infrastructure will allow institutions to manage and scale workloads, reduce time and costs without restricting scalability. Having an agile mindset, data, and infrastructure enables and fosters innovation within an organization, setting up banks to be competitive with the new FinTech disruptors. Banks need not fear these trends. By leveraging the Cloud they will have everything in place to quickly adapt in an ever-changing environment, which will keep customers happy and loyal to their brand.