The use of streaming analytics for automated trading has gone from cutting edge to mainstream. Today, no one would think of building an equities trading system without quantitative analysis of real-time market data integrated with historical models. Streaming analytics has entered the mainstream in trading, but there are many more opportunities and some firms are pushing the envelope in less well-known, disruptive areas.
The technology underpinning this innovation is Fast Data. In a Fast Data architecture, real-time data and historical data are brought together in a business context to support automated and manual decisions, to automate as much straight-through processing as possible, and to empower business stakeholders to control the system and manage exceptions confidently with the context they need.
Even if you’re a real-time infrastructure geek, here are three domains you may not have considered using Fast Data.
Operational Risk Management and Operational Intelligence
Not all bad trading days are caused by market conditions—some of them are caused by software. With operational risk management/operational intelligence, understand the operational conditions that can adversely impact your business. This includes the availability of fresh market data, access to liquidity, and up-to-date information about counterparties. Leading firms are using Fast Data to increase transparency of operational issues with clients both in and outside their firm. This allows their clients to make informed decisions about how to use services, and improves trust between the two parties.
For example, a foreign exchange dealer might notice when they lose connection to a major liquidity source, and widen their spread to prevent too much exposure from accumulating while the operational issue is resolved.
Customer Retention and Customer Relationship Management
Customer retention and customer relationship management are huge across the financial industry. The electronification of markets and rise of automated trading has eliminated many personal relationships that used to drive trading behavior. Today a trading firm may not know its customers personally, but it can still model and understand their behavior to see, earn, and retain their business. Using Fast Data, the most competitive firms deliberately seek out opportunities to connect with customers, whether to propose a new trading approach or simply check in on a decline in activity. These kind of valuable, timely interactions enable them to build personal relationships and credibility.
In one firm, this means monitoring how customers consume research materials, and how those materials impact their trading behavior. This enables a sales trader or account manager to reach out with the most relevant information, particularly when there is an update to some research.
Counterparty Behavioral Analysis
Profitability is always top of mind. Some of our most sophisticated customers use Fast Data to continuously analyze trading behavior of clients and counterparties to understand when the firms actual realized gains track their predicted gains. If trading profitability begins to suffer, it can be a signal that strategies need to be revisited, or sometimes an indication that a particular trading partner is to be avoided or treated differently. No one likes to be taken advantage of, and in a real-time market, Fast Data identifies problems while they can still be fixed.
Analyzing counterparty behavior can help you identify rogue traders, or runaway algorithms, and reach out while there is still time to preserve the relationship and avoid regulatory involvement.
Fast Data Use On the Rise
Capital markets have always been ahead of the curve when it comes to using real-time data for trading, making the best decisions based on the best and most up-to-date data. Streaming analytics and Fast Data technologies make building these systems easier. The same techniques can be applied across the organization, to any situation in which timely decision-making or intelligent predictive automation is required. If your streaming analytics are only being used for trading, you are missing out on opportunities.
Join us for “Streaming Analytics in Capital Markets: Filter the Noise and Capture Opportunities,” a webinar featuring Sang Lee, Managing Partner at Aite Group and Richard Tibbetts, CTO of Event Processing, TIBCO, to learn how streaming analytics can help avoid risk and capture opportunities at microsecond speeds.