Traders Magazine spoke with David Wang, PhD CFA, Managing Director at State Street, who won Best New Product at the 2024 Markets Choice Awards.
Please tell us about State Street Alpha Data Quality.
State Alpha AI Data Quality Platform (AADQ) harnesses AI and machine learning to detect potential errors across investment data domains and ensure the integrity of our partner’s data. Suspicious data elements are escalated to operations teams for investigation and remediation, forming a feedback loop that helps AADQ refine its predictions and respond to changing market regimes, price levels and volatility.
How did your product come about and what gap in the marketplace does it aim to fill?
As the world’s largest asset servicer, State Street touches 10% of global assets every day. This gives us a unique and differentiated view into the myriad data quality issues facing investment firms, data providers, exchanges and custodians.
Traditional processes for validating investment data typically employ thresholds (is the value greater or less than some threshold value), or list membership (is this ticker symbol found in a list of securities comprising the S&P 500) to detect anomalies.
These methods rely on human expertise to establish appropriate thresholds and maintain lists. They also generate large numbers of false positives. A market value that exceeds a threshold could well be legitimate on days when markets experience massive moves.
We built AADQ to flag complex anomalies not easily caught by manual rules. Additionally, AADQ’s specificity significantly reduces false positives that would require investigation by human analysts thereby boosting operational efficiency.
What data management challenges do investment firms face?
Investment firms are challenged by an unprecedented glut of data. While every financial institution aspires to be “data-driven,” the reality is that many firms are still burdened by legacy technology, data silos, and manual processes that inhibit their ability to effectively leverage those rapidly growing volumes of data.
The velocity at which data is generated presents further challenges. In most cases, useful information has an extremely short shelf life and needs to be extracted from raw data in near real time to provide value.
Accurate, timely, and consistent data is critical to making informed investment and operational decisions. Financial data spans many domains, from pricing and reference data to benchmarks, positions, and investable cash. Organizations employ large teams of specialists to manage and validate these disparate data sources in the hope of flagging and remediating suspicious data.
Today’s capital markets generate data at a pace that makes it difficult for teams to keep up, even at larger institutions. Finding the proverbial needle in a haystack is an apt metaphor for data validation. There are very few actual errors, but those that go undetected can create significant problems if consumed by downstream systems.
What does the future hold for your company?
State Street’s global team of data scientists, engineers and product managers are constantly launching new applications that harness AI to generate differentiated insights for investment teams and eliminate operational inefficiencies across the front, middle and back office. Leveraging our significant annual R&D spend and global presence enables us to bring innovative products and services to market faster for the benefit of our clients, their end investors and the greater capital markets ecosystem
