Underwriting solutions for the insurance industry
Data visualisation for underwriters
Whether you need help developing a new data visualisation solution, one off reports, online chat, customer portals and apps or machine learning and AI capabilities we can help.
If you have legacy systems, no problem. We can help with their management, integration and future development. Our team of experts can support most underwriting businesses, large or small. We are also working on a number of machine learning, AI and predictive analytics solutions that help insurers predict risk using data from a range of internal and external data sources.
Policy admin systems
Develop a system that integrates with your existing work flow and puts your underwriters in control of the issuing of policy documentation.
Put your underwriters in control of rating and product management with no requirement for third party intervention.
It can often be difficult to access and pull together data from different departments. We can help develop dashboards and business intelligence reports so you can gain a clearer view.
Provide clients with access to key documents such as policy wordings, certificates, schedules and claims forms.
Most clients expect their providers to offer some form of app, we can develop complex systems which include quote and buy, policy management, document management, and risk improvement monitoring and reporting.
Do you need a single data view across other functions to help with your underwriting decisions? We can help by providing consulting and developing interfaces for use with different suppliers and systems.
Power BI consultancy and implementation
As a Microsoft Partner our preferred business analytics service is Power BI. It provides insights to enable fast, informed decisions.
We can provide lightning fast data warehousing solutions with Microsoft Azure on even the most complex insurance data workloads.
Make an enquiry
We’d love to discuss your data and software requirements. Drop us a message and we’ll get back to you shortly.