In 2020, Re:infer joined insurance leaders including LV, Lloyds, Deloitte, and AXA, as a member of InsTech London.
InsTech is renowned for identifying and promoting the best technology, data, and analytics innovations within insurance and risk-management. Since its establishment, InsTech has shined a light on the most promising insurance innovations.
InsTech co-founder Robin Merttens recently joined a video-call with our CCO Stephen Mackintosh to discuss Re:infer’s role in insurance innovation and automation.
Below, we have summarised the key takeaways from the podcast, but we highly recommend you watch the full 20 minute session for more detail and a preview of the Re:infer platform in action.
How Communications Mining Works
Re:infer was launched out of the UCL AI Research Lab, home of widely recognised machine-learning companies including Google DeepMind. Re:infer uses state-of-the-art natural language processing (NLP) and Communications Mining technology to extract business value from business conversations.
Insurance companies run on communications data - from emails, chats and tickets to annotations and CRM notes. This unstructured information is rich with process intentions, sentiment, and semantics as well as key information like policy numbers and trade IDs.
Re:infer’s Communications Mining platform converts this unstructured data into useful machine-readable, structured data, enabling insurers to automatically discover patterns in conversations — finding frequently occurring questions, requests, processes and themes.
The platform's zero-code interface empowers business users to teach Re:infer the specifics of the business, generating real value in hours rather than months.
Re:infer’s Success with Financial Institutions
As Re:infer’s reputation grows, the world’s largest financial institutions are taking notice. When first examining the processes of a large investment bank, Re:infer analysed over 15 million emails across Post-Trade Operations, identifying bottlenecks, inefficiencies, risk events, complaints and exceptions, but also client themes and clear revenue opportunities.
Unstructured data is generally invisible and unusable for banks. However, by extracting, measuring and quantifying operational processes, Re:infer was able to identify those that the client should eliminate, augment or automate. This allowed the bank to achieve levels of organisational efficiency that were previously considered unattainable.
Re:infer’s Success with Insurers
Following well-publicised success with Hiscox, insurance has become a major growth industry for Re:infer.
Re:infer’s initial roll out with Hiscox was focused on automated email triage. 97% of broker requests to Hiscox were incorrectly first routed to underwriters thanks to processes reliant on manual, individual action and admin. This manual workflow created significant intellectual waste for skilled underwriters taken away from the task of bringing in new business for the firm.
Re:infer’s Communications Mining platform allowed Hiscox to streamline operations, liberate senior underwriters from transactional repetitive tasks, and save the company hundreds of thousands of pounds in efficiency gains.
Communications Mining is elevating the broker experience. Re:infer is a capability, a tool that lives inside an insurer's operation, and really helps them to innovate.<small>Stephen Mackintosh, CCO, Re:infer<small>
Re:infer’s platform is proven to provide much faster resolution, efficient processing and a more satisfying broker experience. Broker requests can be labelled, ranked and filtered to discover which brokers are receiving the worst experience, and by what measures they could be improved. Requests that were taking weeks now take only days.
Re:infer’s Client Profile
The clients with the most to gain from Re:infer are large enterprises which send and receive high volumes of daily communications. Since the IPO of Lemonade , NLP tools have begun to transform the insurtech sector. Thanks to SaaS solutions like Re:infer, large incumbents can now embed those same technologies in their operations.
We're not an insurtech, we're a machine learning company, but we help insurers become insurtechs, that's for sure. <small>Stephen Mackintosh, CCO, Re:infer<small>
Re:infer’s Platform
As individual messages are mined for vital details, the Re:infer platform provides a real-time structured data summary that can be consumed by the broader IT real-estate.
Re:infer's UI features helpful tools including reports, filters and a tree map to proportionally represent communications. Together, these tools provide clients with a customisable “30,000 foot” overview from which to reveal the factors driving spikes in activity, and to optimise their operations.
The whole UI is designed to put the business user in the driving seat
<small>Stephen Mackintosh, CCO, Re:infer<small>
Re:infer’s zero-code platform is dynamic and intuitive. Employees need only point and click to add or remove labels, and the machine learning will then automatically begin retraining in the background.
Re:infer also has pre-built integrations for systems including Salesforce and 365 Exchange, as well as downstream connectors for workflow tools like Appian, ServiceNow, BluePrism and UIPath.
The goal is to make the link between unstructured data and action as seamless as possible without the need for technical training or bespoke build-outs.
Re:infer provides a SaaS application that can be played with, tested and customised - by the business for the business.
