Robotic Process Automation with Azure Synapse enables an innovative InsurTech start-up to ensure critically ill people get the care they need.
AUL are an insurance start-up that helps critically ill people get the lifetime care that they need. Their business is underpinned by a sophisticated approach to InsurTech and state-of-the-art Machine Learning models. When they needed to develop a solution for their secure data architecture and business process flows, their Actuarial partner, Milliman, recommended that they turned to endjin.
Medical and financial data
The main challenge for AUL is around data privacy, at scale. Their models depend on a considerable amount of private data, from medical records to detailed financial information, typically shared by the legal and medical representatives of the person making the insurance claim.
Endjin have developed a turnkey InsurTech Data Platform, based on our more general-purpose Azure Synapse Modern Data Platform blueprints, which allowed us to classify and manage PII, PCI, health, and demographic data in isolated stores, with just-enough-administration and just-in-time access controls.
Linear scaling of cost
The data solution is globally scalable, to petabytes of storage, and is capable of supporting mass-market business-to-consumer insurance plays for millions of customers. That's great as the business grows, but it is equally important that it also scales right down, keeping infrastructure overheads to a few hundred pounds a month while they go through the usual development and regulatory hurdles prior to transacting business.
Robotic Process Automation
Any data platform is only as efficient as the processes it enables. The complex insurance cases that AUL deals with require both human and machine analysis. They also integrate with third party services and APIs such as Milliman Mind, the modelling platform, and SharePoint for document upload, storage and remote sharing.
We worked with AUL's domain experts to model the processes and identify opportunities for both improvement and automation. We then built out an implementation of our React-based InsurTech case management UI platform over these workflows.
But that's not the end of the story - we also taught AUL's team how to analyse, design and validate their own automated workflows using those tools, giving their business experts the power to model new processes within the existing platform.
Low cost, high scale, ready for the regulators
By building the solution on Azure Synapse, and endjin's InsurTech Data, Case Management, and Workflow technology, what would typically be a multi-million pound build was delivered at a fraction of the price, with ultra-low operational costs.
Endjin's approach to design and testing also left AUL with rich operational and process documentation, ideal for regulators and internal data governance requirements.