Siren is moving its semantic data investigation platform into the fintech sector following a €3 million round of seed funding led by Atlantic Bridge University Fund. John Randles, CEO at Siren, says the semantic platform fills white space between business intelligence solutions and coding of deep analytic tools by providing a product that enables investigation of data in real time, at Big Data scale, across multiple data sets.
The company has been testing the platform in financial markets for the past couple of months and has a dozen pilot projects running at large sell-side organisations, custodians, asset managers, and hedge funds. Three use cases include operational intelligence, such as system monitoring, process monitoring and cybersecurity; research intelligence, such as discovery of trading opportunities and Know Your Customer (KYC) and counterparty risk management; and fraud intelligence that can be used by regulators and compliance teams.
Randles says: “Financial firms have made major investments in data and Big Data infrastructure, but not in the data investigation domain. Search, business intelligence dashboards and graphic databases have been available for a while, but there has not until now been a coherent semantic layer able to investigate all data. The Siren platform leverages investment in Big Data by using semantic technology to relate adjacent datasets, answer business questions without the need for an IT project and deliver knowledge graphs showing patterns and concentrations that it may not have been possible to see before.”
An example of this is the ability to ask questions that firms have not been able to ask before about trade data captured by Financial Instruments II (MiFID II) trade data. Perhaps how a firm’s trading behaviour compares to that of the market.
To answer complex questions, the Siren platform allows investigation of data wherever it is, from streaming Twitter feeds to databases. Working with clients, the company builds a semantic model that identifies key relationships across selected date. The data becomes meaningful and accessible via search, dashboard analytics, knowledge graphs and real-time alerts.
Randles says it usually takes five to 10 days to build a semantic model, which can then be used immediately to answer questions. Clients can add more datasets and answer more questions as they go along.
The technology behind the platform is based on research from the National University of Ireland and was initially offered by Siren to national security services and the police, where mission-critical investigation of data is often done under intense time pressure. Supported by seed funding, the company is extending its reach into the financial and life science sectors, and growing its team, which started with four people last year and is now heading towards and beyond 30 people.