Capital markets firms are turning to real time big data analytics for alpha generation, risk management, compliance, consumer metrics and to monetise insight, according to research from TABB Group.
“Big Data Is Dead, Long Live (Real-Time) Big Data: Real-Time Big Data Analytics in Financial Services” reviews the prevailing architecture used to create actionable real time business intelligence based on varied streaming, static, structured and unstructured data sets, and identifies use cases for the buy-side, sell-side and liquidity venues.
According to TABB, the age of the data warehouse, segregation of streaming and static data analytics, and utilising batch-led approaches to analytics is over and we have entered the age of real time big data analytics.
Report author Monica Summerville (pictured) explains that simply having this data is not useful; firms must be able to find and act on patterns in incredibly large volumes of data while using real time streaming analytics that can reference older, stored data without reverting to batch processing.
In order for financial services firms to see some return on investment of these efforts, TABB says the solution lies in taking big data analytics “upstream” by layering streaming and static big data sets to support real time analysis of combined data sets. This capability is a key requirement in order to progress to machine learning and other artificial intelligence based analytics.
“We believe the upstream analytics approach will increasingly be adopted throughout the industry in response to industry drivers, an unending desire for new sources of alpha and the rising complexity of investment approaches,” says Summerville. “The market for real time big data analytics is potentially as large as business intelligence, real time streaming and big data analytics combined. The most successful approaches understand the importance of data acquisition to this process and successfully combine the latest open source technologies with market leading commercial solutions.”
Implementing a business-focused real time big data analytics strategy takes a significant investment in software, hardware, and data, as well as significant sector expertise, Summerville explains.
The leading commercial solutions for real time big data analytics for capital markets are often from vendors with a history of real data streaming analytics and complex event processing (CEP) solutions.
In the short term, TABB believes early adopters of real time big data analytics within capital markets include technically savvy firms on the buy and sell-side whose trading strategy includes putting the firm’s capital at risk, either through proprietary trading or market making strategies.
