Data agnostic, automated search across third party, internal, and open sources datasets in near real time concurrently.
Multiple data sources are essential to detect and assess risk around claims and underwriting. Our automation platform, Scout®, takes a data agnostic approach, aggregating Synalogik, third party, open source and internal data – and eliminating the need for manual integration of additional data sources that are a challenge of other solutions.
The result is we can maximise the operational efficiencies from automation, saving 85% of your team’s time.
Discover more fraud with less effort – For a Tier 1 Motor Insurer Proof of Value Scout® identified in excess of £1.6 million in annual fraud savings and saved 288 hours compared to manual processing.
Better Customer Experiences – Reports compiled in less than a minute enable your business to make decisions on validating claims more quickly, ensuring genuine customers stay happier and more loyal. While simultaneously detecting more fraud to ensure premiums can be kept lower.
Single Intelligence Environment – Along with Synalogik, internal data and open source, Scout® has out-of-the-box third party data integrations with CRIF, Creditsafe, TransUnion, LexisNexis, Equifax and the the Claims Underwriting Exchange (“CUE”) data set.
Better Analyst Decisions – Automated search and risk workflows, entity link visualisation, data clasher, open-source tools and standardised, in-depth and clear reports, free of human error, give your team the tools and time to focus on decision making.
Synalogik datasets – Synalogik datasets include standard, enhanced and premium personal identifiable information (PII); global commercial data; PEPs and Sanctions; credit application; disposable phone and email; credit address links; CCJ and bankruptcy; land registry; and compromise checker, among others.
Scout® completed the whole validation process in only 6 minutes, delivering incredible operation efficiencies in terms of speed and cost and resulted in projected annual savings of around £1.02M.