SmartStream: A new age of collaboration as banks unite around data management
Banks are facing unprecedented pressures on their data management processes, not only from the growing volume of data, but also due to the regulatory and cost pressures that are squeezing the industry. That is why they are working together as never before to address the issue. Joe Turso, vice-president of SmartStream, elaborates on why the company's Reference Data Utility is proof that this collaboration is working.
It has become a familiar refrain that banks' services are only as good as the data they have. For many years, there has been talk of the data deluge and the need for banks to ensure they have the right data - and the right data quality - to differentiate their services in an increasingly competitive marketplace. For the past decade, there has been growing regulatory pressure - everything from know-your-customer (KYC) and anti-money-laundering (AML) directives to legislation on capital requirements - that has added to the cost and complexity of data management.
The need for more reliability and efficiency in the gathering and processing of data has led the industry to look at standardisation to remove errors and inconsistencies, and to address the potentially huge costs of building in-house solutions. Many banks want to avoid large-scale reinvestment in legacy technology and infrastructure, and the utility model has come to the fore. Reference Data Utility (RDU) from SmartStream is the result of the collaboration between large banks to produce such a model, and some feel it could herald a new era of cooperation.
"There has been a big change in banks' data management needs over the years since the credit crisis," says Joe Turso, vice-president at SmartStream Technologies, who has spent three years with the company after working at RDU client Morgan Stanley. "There has been a fundamental shift in how Tier 1 banks think about data, partly because there is a growing number of regulatory requirements that place demands on the availability and quality of data. This requires investment at a time when revenues are declining and the need to cut costs is growing.
"There are, therefore, contradictory goals. Enterprise data management groups must meet the new requirements but are being forced to cut costs. Most banks have already done what they can to make data management more efficient through shared services and using lower-cost locations. I am excited about what is happening in the industry now; we are seeing the walls taken down, and banks are sharing knowledge and IP around data management. In 25 years in the industry, this is the first time I have seen this level of collaboration. There is a level of trust I have never seen before," he adds.
Agnostic, accurate, efficient and essential
RDU is the result of leading banks working together to establish an industry utility based on market commonality and true collaboration. It aims to manage data holistically across different legal entities in such a way that the shared-service model promotes common fixes to data processing issues.
"In 2013, Tier 1 banks got together to look at a utility model because they recognised that they do roughly the same things with data. They engaged with about a dozen vendors to see which they could leverage as the basis of that utility and SmartStream made the shortlist. After months of due diligence on the operational models and the technology, we were selected for the Securities Product Reference Data - SPReD - platform. We then created RDU Services, which is owned by SmartStream, Goldman Sachs, JPMorgan Chase and Morgan Stanley," Turso explains.
By centralising data processing on to RDU, common market processes can be incorporated across all participants to minimise the effort required to get the data right. RDU acts as a processing agent for its participants' selected data sources that manages their complete data life cycle - sourcing, validation, enrichment and cross-referencing - bringing together best practices to achieve better data quality and more timely responses.
RDU provides a single, multi-tenanted and auditable environment that supports customised integration standards and controls, but users' data governance policies are handled individually across different financial markets and asset types. Participants are assured of highly accurate and transparent access to their data without any compromise on security, integrity or data policy. The utility adds value to existing data sets instead of sourcing excess data and coupling it together, which results not only in less complexity in data management processes, but also more flexibility as requirements change. The centralised model also decreases the risk of problems associated with limited legacy infrastructure and lack of capacity.
"The business case for the utility model has four main drivers. The first is technology, and the goal for banks is to reduce cost and platform complexity. Banks need data across many asset classes and the utility enables data management while banks keep their separate utilities, so there is no need to unify their systems, which would be expensive and takes a lot of time," Turso explains.
"The second driver is the reduction of operating costs. RDU actively captures data issues so that they don't go into banks and impact on their business. There are fewer exceptions, so fewer staff members are needed to address them. Third, the utility drives best practice and, therefore, regulatory compliance. Finally, there is business enablement. RDU allows enhancements to be made in a cost-effective way. As long as the bank understands how much data it has, what the uses of it are and the impact of changing the data, then the transition to the utility model is just about change management in the context of its legacy systems," he adds.
Up time, all the time
RDU operates 24/7 from centres in New York, London, Bristol, San Jose, Mumbai and Bangalore. It enables massively scalable data throughput, rapid response to exceptions and errors, and accurate reporting and audit processes to support any number of client-defined uses for data. That level of control over their data is what simplifies many of the operational challenges that financial institutions face today, as it prevents problems with core reference data from spreading throughout the enterprise.
Reference data can be a huge cost for banks and while it is essential for the running of the business, it offers little in the way of competitive advantage. When that data resides in siloes in different parts of a bank, it fails to deliver its full business value. It can easily become out of date and incorrect, which can ultimately lead to trade breaks. Accurate, complete and linked data, by contrast, delivers process efficiency, cost reductions and risk reduction.
"The concept is mutualisation. We normalise the data and manage it consistently across data sources. On the distribution side, we customise it according to users' preferences. We act as a transaction processing agent, so the banks maintain their vendor/client relationships and we fill the role of a third-party processing data for them," explains Turso.
Spreading the word
Since its launch, the adoption of RDU has spread and its uses have become more versatile. At the end of 2015, SmartStream announced that Euromoney TRADEDATA, Exchange Data International, Interactive Data Corp, S&P Capital IQ, S&P Dow Jones Indices, SIX Financial Information and Thomson Reuters had signed agreements allowing RDU to process their data on behalf of mutual customers. The processing agreements allow the efficient onboarding of each company's data and jointly managed support between each data vendor and RDU.
In the future, Turso believes that many more market participants will turn to the utility to realise its proven efficiencies. "The Tier 1 banks are early adopters and they bring best practice with them. The utility is an extension of their back-office processing capability. As the model matures, we will see more buy-side players coming in to leverage what those banks are doing. So, with the buy side and the sell side involved, we will see a further reduction in trade breaks and exceptions. It may take a couple of years for the buy side to come in, but it faces similar issues with data management," he says.
"Not having good data is a compliance risk, and that is what will continue to drive the collaboration in the industry," he adds.
It remains to be seen where the cooperation between banks on data management could lead, but the results from their efforts on RDU suggest that great things could come from an alliance of best practices.