Deep Learning meets Capital Markets
Real-time analytics and automation of communications data.
Accurate, effectively and timely communication is critical in the capital markets. re:infer automates the interpretation of communications, enabling real-time, scalable, efficient service, fulfillment and risk management.
In the capital markets information is your edge. Firms typically generate tens or hundreds of millions of messages every year. Employees spend over half their day reading, writing, deleting and forwarding messages.
In the pre-trade space the firm doesn’t have the capacity to intelligently listen to clients across all the conversational touchpoints, weakening the capacity to prospect, onboard, drive engagement, sales and efficient execution.
In the post-trade space, every message is an exception to Straight-Through Processing (STP) and introduces operational risk. Without understanding, measuring and monitoring the flow of fulfilment in these currently opaque channels we cannot increase STP rates, drive self-service, automation and reduce cost base.
re:infer’s Deep Learning platform unlocks the value in your communications.
re:infer converts unstructured communications (emails, calls, chats, notes) into structured data in real-time allowing for analytics and automation.
In the Pre-Trade environment, re:infer is automatically discovering client intents, sentiments, trends and hidden relationships that translate into trading signals for front-office teams.
In Post-Trade Operations, re:infer is discovering manual processes, quantifying failures, highlighting root-cause errors, detecting incorrect reference data and providing a bridge to downstream automation.
Across the trade lifecycle, re:infer is revolutionising the way client data is processed, enabling new revenue streams and improved operating efficiency.
re:infer creates opportunities for growth
Automatic capture of management information
Minimising the sources of latency
Automation of manual processes
Make every conversation count
COO was tasked with implementing a board-level change programme: cut the operational cost base by 50% within 5 years.
re:infer was selected to identify quality-of-service across all channels. Our cognitive intent platform was able to identify processes and workflows that are suitable for automation and transition to a digital operations infrastructure that is centered around real-time analytics, automation and self-service.
Projected Annual Savings
FTE hours per annum
Facilitated end-to-end automated processes