Cytora Launches Unified Risk Reasoning in Major Breakthrough for Complete Risk Workflow Automation for Insurance Professionals

Cytora has launched an industry-first new release for its digital risk processing platform that will enable insurance professionals to completely automate pre-decisioning workflows.  

Unified Risk Reasoning is a proactive reasoning partner that thinks and acts like a human. It solves a longstanding challenge of complete workflow digitization by moving beyond data collection to enable the automated review, choice and finalization of the ultimate fields on which risk decisions are made.

Historically, risk automation workflows have lacked integrated reasoning layers and resulted in the need for insurers to maintain manual workflows. These include the review of different data candidates from submission, internal and external sources, and the refinement and finalization of each field. Unified Risk Reasoning applies a controllable reasoning layer, underpinned by Chain of Thought, to transform these processes and fully automate the entire risk workflow. As a result, insurers, brokers and reinsurers will be able to substantially accelerate pre-decision automation, improve efficiency and reduce costs. 

Unified Risk Reasoning is the latest in a series of enhancements to Cytora’s platform as it continues its mission to revolutionise risk workflows through the application of cutting-edge AI. Recently, Cytora launched ‘Concierge’ to enable underwriters to control and automatically digitize any request that arrives in their intake – across all transaction types including new business, renewals, endorsements and claims.  

Sam Lewis, VP Product at Cytora, said: “Unified Risk Reasoning is a major breakthrough. It cracks one of the biggest challenges in the true automation of risk workflows – finding, choosing and finalizing the ultimate data required to give a complete picture of the risk. This has always required the hard work of a seasoned professional. Now, by leveraging the very latest capabilities of AI, we have developed a system that accurately executes this expertise. As a result, insurers, brokers and reinsurers will see massive efficiency gains and cost reductions.”

Features of Unified Risk Reasoning include: 

Multi source reasoning – schema fields can be fulfilled from different combinations of sources – flexibly defined by configuration users in natural language. Composite fields can be constructed through a combination of submission, external sources and web research. Risk and claim data points are interpreted as a whole, rather than isolated fields allowing one source (e.g. web information) to contextualise another (e.g. the submission) providing improved reliability and control. The platform makes it easy to expand the breadth of sources reviewed yet drives automation by finalizing field values, unlocking straight through processing.   

Comprehensive data library – users can add new external data sources to schemas without any technical resource requirements. This means the platform can automatically reference and consult external data sources to augment and complete fields with added context, as well as refine incomplete or incorrect data. The platform interprets the entire risk or claim to drive enrichment, rather than just the requirements of individual fields.

Agentic web research – underwriting, operations and claims teams often lose time searching the web for the information required to complete risk data. Unified Risk Reasoning can automate these web searches and apply the information found to inform and refine data in the risk submission.

Automated enrichment chains – enables the output of one enriched field to be the input process for another. This capability unlocks advanced data workflows, allowing users to build richer and more comprehensive profiles by progressively enriching data through multiple external sources. In addition, sequence configuration is handled automatically as it understands the relationships between required data points, their sources and, by extension, the order in which data must be gathered to automatically and completely fulfil risk data requirements. 

Transparent Chain of Thought reasoning – Chain of Thought is summarized in natural language, presenting key details and reasoning to underwriters and claims handlers making risks and claims easily understandable and rapidly actionable.