Conversational Data Intelligence is helping cut costs, boost growth and strengthen client relationships
Re:infer enables asset managers to extract key insights from their communications data to drive process efficiency and a better client experience.

Asset Management relies on communication, but managers lack insight into what’s being said
Asset managers are under great pressure to find cost synergies and make intelligent strategic investments quickly. These decisions need to be based on insight, but client interactions and counterparty conversations are hidden within masses of unstructured communications data.
Across the middle and back offices, trades fail to settle, grey processes remain unchanged and email is used as the primary workflow tool to manage exceptions. Process automation could greatly boost efficiency, but relevant opportunities need to be discovered first.
The failure to analyse or automate unstructured conversational data prevents client fulfilment, creates latency in operations and raises compliance risk. Rich information on sentiment, performance and product appetite are out of reach.
Re:infer turns any message into actionable data, enabling intelligent decision making and guiding automation
In operations, Re:infer highlights process inefficiency and boosts middle and back office performance, driven by real-time actionable data.
Asset Management firms use Re:infer to quickly develop NLP solutions, unlocking the value of conversational data
Advanced client and broker analytics
- Monitor sentiment: real-time analytics on wants and needs
- Discover demand: detect the drivers of value and failure demand
Compliance
- Detect operational risk
- Monitor adherence to regulatory requirements from KYC to AML & GDPR
- Monitor third-party adherence to SLAs
- Alerts to low frequency high risk events
- Perform surveillance at scale
Operation analytics
- Discover and quantify manual processes
- Detect root cause of exceptions and process, systems and people failure
- Monitor and improve settlements
Automation
- Make all communications data structured and actionable in the wider IT real-estate (RPA, CRM, CMS, SCV, ERP)
- Deliver straight-through processing of requests
- Cognitive + RPA: amplify existing robotics installations with a cognitive front-end that can trigger processes
“When I joined Farfetch I was totally cynical about text analytics. Re:infer has really changed my mind on that. The power of taking detailed qualitative feedback data and quantifying it is really special. Re:infer has definitely been good value for Farfetch.”
To remain competitive, insurers should accelerate underwriting transformation. They can do this by automating routine tasks and augmenting teams with emerging technologies and alternative data sources to empower underwriting professionals to become "exponential" - more valuable than ever.
“The enterprise is built on communications. It should be no surprise that, to digitally transform, NLP is not just a nice-to-have, it is a must-have, which is why our partnership with Re:infer is so important to us and our clients. Re:infer's deep learning platform allows us to unpick customer intents and unlock understanding in unstructured processes across the business.”

"Re:infer gives us a clear signal of what conversations result in a purchase and which don’t. At the scale we’re operating at, this provides hard, statistical evidence on what is going on in these conversations and attributes that to the most effective sales behaviours."
The Re:infer platform truly follows the low-code/no-code mantra with rapid models created in hours by process SMEs, not data scientists. Re:infer is at the cutting edge of the Intelligent Automation spectrum.
“Re:infer's AI platform lets us understand what our customers tell us – at scale. Ultimately it helps us make better product decisions.”
Re:infer enables us to hear every customer and plays a critical role in our customer-centricity strategy. With Re:infer we can continually improve our product, service and support to meet the demands of our customers.
"Re:Infer enables us to have a more data-driven approach, giving us the chance to digitise qualitative customer feedback, and even to embrace the so-far ignored silent majority of customers. As a CX leader, I feel much more empowered when our analysis is linked to revenue."