Deep Learning meets Capital Markets.

Deep Learning meets Capital Markets.
Deep Learning meets Capital Markets.

Cutting-edge technology for understanding capital markets communications data.

In a competitive capital markets environment, digitally advanced services and architectures will be the determinant of future success. Artificial intelligence can deliver innovation that was previously hard to achieve.

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The Problem

THE PROBLEM

Capital markets firms are sitting on a vast trove of largely un-mined and unstructured communications data containing uniquely valuable insights into client sentiment, market activity and operational processes.

These insights lie in the millions of emails, calls and chats happening externally in the market with clients or counterparties and internally in operations channels.

Today, capital markets firms are unable to extract value from these conversations and insights remain hidden. The data is unstructured, non-actionable and there is no capability to process it at scale.

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THE SOLUTION

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.

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The Solution

re:infer creates opportunities for growth

Automatic capture of management information

Automatic capture of management information

Machine-driven discovery of client and operations behaviour in real-time across millions of interactions.
Client-centric services

Client-centric services

Data-driven relationships that revolutionise the client experience.
Minimising the sources of latency

Minimising the sources of latency

Speed up understanding and processing from days to minutes.
Automation of manual processes

Automation of manual processes

Address the high and inefficient cost of human capital with straight through processing of repetitive manual tasks.

Every conversation counts.

Pre-Trade Communications Analytics

Monitor client sentiment: real-time analytics on clients wants and needs Discover client demand: detect the drivers of value and failure demand Discover and act on product, pricing or research feedbackUnderstand how clients talk about the competition

Sales Optimisation

Discover the conversations leading to up-sell and cross-sell moments Discover the attributes of high performing relationship managers Correlate sales events with the exact contents of conversations Create a real-time feedback loop from market signals into trading, sales and research

Post-Trade Operations Analytics

Discover and quantify manual processes Detect root-cause of process, systems and people failure Discover instances of incorrect reference data Real-time monitoring of quality of service with counterparties Reduce the the operational cost of communicating by ~50%Visibility into process bottlenecks and a route to operational process excellence Align front, middle and back office performance

Compliance

Detect operational risk Monitor adherence to regulatory requirements from KYC to AML & GDPR Alerts to low frequency high risk events Perform surveillance at scale

Automation

Make all communications data structured and actionable in the wider IT real-estate (RPA, CRM, CMS, SCV, ERP) Deliver straight through processing of requestsCognitive + RPA: amplify existing robotics installations with a cognitive front-end that can trigger processes

Advanced Client Analysis
Advanced Client Analysis
Connection

Tangible results.

Group Operations

Challenge

COO was tasked with implementing a board-level change programme: cut the operational cost base by 50% within 5 years.

Our Role

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.

60 Million

Conversations Automated

$ 135M

Projected Annual Savings

1,200,000

Employee Hours Saved

72

Process Automated End-to-End


Improve your results with re:infer