The cloud propels financial institutions (FIs) forward and provides the opportunity to scale in line with market demands such as volatility in the capital markets space, new regulations in banking and payments or increasing data assets in the insurance industry.
Traditional data infrastructures hold FIs back forcing them to provision their IT capacity to multiple times historical peak to ensure they can react to market conditions linked to fluctuations in index rebalances, annual contract renewals and regulatory announcements. With cloud, FIs can scale capacity up and down on demand, without the cost of pre-provisioning excess infrastructure.
Finextra spoke to Mike Pelliccia, head of worldwide financial services technology solutions at Amazon Web Services (AWS), about how the cloud is enabling FIs to operate and experiment with significantly higher levels of agility by simplifying infrastructure and speeding up prototyping.
On-premises infrastructure no longer meets the business needs of today
Pelliccia highlights that “on-premises data infrastructures do not scale to meet variable and increasing volumes of data. Multiple disconnected data silos with inconsistent formats obscure data lineage and prevent a consolidated view of activity. Rigid data schemas prevent access to source data and limit the use of advanced analytics and machine learning. The high costs of legacy data warehouses also limit access to historical data.”
The cloud helps FIs harness the value of their data and aggregate it at speed and scale so that they can achieve their business goals. Traditional data solutions cannot keep up with the volumes and variety of data that is being collected today by financial players.
Pelliccia adds that a cloud-based data lake allows FIs to store all data in one central repository where it can be more readily available for the application of other technologies such as machine learning, “to support security and compliance priorities, realise cost efficiencies, perform forecasts, execute risk assessments, improve understanding of customer behaviour, and drive innovation.”
This enables organisations to maintain a holistic view of their business, while identifying risks and opportunities. For instance, analyses can help to detect fraud, surface market trends and mine for deeper customer insights to deliver tailored products and personalised experiences.
Scalability for banking
Cloud-based data lakes are the future of data management, but for banking innovation teams the focus is on identifying and proving technical opportunities within the organisation. Pelliccia elaborates that “Innovation requires short project timelines in order to beat the market and keep the cost of failure small. If banks can reduce the time spent on experiments, they can reduce the cost of a failed experiment. Processing simultaneous workloads enables experimentation to drive faster and more efficient innovation.”
The cloud has simplified the CI/CD pipeline - what is referred to as the backbone of modern DevOps and bridges the gap between development and operations teams by automating the building of applications. Historically, developers had to wait for machines to be freed up in order to build, test and debug systems, but now with the cloud, developers can run simultaneous sandbox environments for development and testing, speeding up time to market.
Pelliccia says, “test environments generally were not scaled to production capacity or were restricted to testing during production green-zones, limiting their effectiveness. The cloud has allowed for at-production-scale test environments to be made available for testing and spun down during non-testing periods, which improve test quality and reduce cost.”
Alongside this, banks also have to consider regulations such as Comprehensive Capital Analysis and Review (CCAR), Basel III, IFRS19 and IFRS17. “The cloud allows parallel environments to be spun up to run the new models, reducing the time required for meeting those objectives,” Pelliccia highlights.
Managing big data for capital markets
Pelliccia explains that financial data access and management across multiple data sources can be complex for capital markets firms using on-premises or colocation data centres. “Network hardware and networking expertise can be costly, with set-up taking days or months to complete. This leads to less time to invest in generating business insights with analytics, alongside limited storage and compute capacity.
“The scale and agility of data lakes in the cloud make it easy to aggregate data from multiple sources and conduct large-scale data analytics such as back testing thousands of trading strategies and monitoring the markets to ensure market integrity,” Pelliccia says.
Capital markets firms using AWS can simplify financial data access from multiple providers without complex networking and infrastructure, while at the same time, accelerating data analysis with the broadest set of analytics, business intelligence, and ML services.
For example, when Robinhood required a centralised data platform, the organisation built its data lake on Amazon Simple Storage Service (S3) with only three engineers. AWS helped scale its compute and storage, while managing user access and governance.
Insurance and the multiplicity approach
Pelliccia says that insurers are applying data lakes to multiple use cases. “Whether it’s enhanced rating and processing, risk and catastrophe modeling, customer experience, or product development, they’re leveraging cloud to build a flexible foundation for analytics and innovation.”
The example he uses here is Guardian Life, an organisation that expanded its digital experience with a data lake on the cloud as part of its data growth and analytics strategy. “By moving to AWS, Guardian launched an all-digital platform, Guardian Direct, that allows consumers to research and purchase both Guardian products and third-party products in the Insurance sector.”
Collaborating to get ahead
Financial institutions do not have to migrate data to the cloud alone. Pelliccia adds that companies can turn to AWS and its global community of partners, the AWS Partner Network (APN), for the tools and best practices to collect, store, govern, and analyse data.
“Advanced Technology Partners who achieve Financial Services Competency such as Collibra and TickSmith have deep industry expertise, solutions that align with AWS architectural best practices, and staff with AWS certifications. Those with Data & Analytics Competency such as TIBCO have demonstrated success helping customers evaluate and use the tools, techniques, and technologies of working with data productively, at any scale.”