Specialising in enterprise data governance, regulatory compliance, productionising actuarial models on Azure Databricks and more for the insurance industry.
Get StartedBuild robust, scalable data ELT/ETL pipelines and infrastructure tailored for insurance operations.
Ensuring PII protection, data lineage, reproducibility, and metadata management, with UAC and cataloguing for full compliance with FCA, PRA and more.
Seamless integration of various data sources both internal (spreadsheets, databases, enterprise software, API) and external (e.g. Bank of England, FCA etc) with automated pipelines.
Performance tuning and optimisation of data platform, parallelisation, actuarial models and more.
Development of front end and backend solutions for in-house actuarial models, optimised with user-friendliness and performance in mind
Generate automated reporting and build dynamic visual dashboards from your data platform
We are a specialized data consultancy focused on transforming insurance companies through advanced data platform solutions. Our team of experts brings years of experience in insurance data management, ensuring your organization stays ahead in the digital age.
With a deep understanding of insurance industry challenges, we deliver tailored solutions that drive efficiency, compliance, and innovation.
Client D had traditionally operated as a spreadsheet-driven organization, with individual business units functioning in silos. This fragmented approach led to limited visibility across the enterprise, making it difficult to access reliable, real-time data or foster cross-functional collaboration, leading to many bypassed processes.
To address these challenges, we engaged key stakeholders across the organization to gain a clear understanding of the various business units and their roles. Through a series of workshops and discovery sessions, we mapped the operational landscape and initiated the development of an enterprise-wide data model. This helped identify overlaps, gaps, and opportunities for standardization. Alongside this, we introduced foundational data governance guidelines to bring consistency and accountability to data management practices.
We also focused on education and alignment, introducing stakeholders to the capabilities and value of a centralized data platform. This included the design of a scalable architecture tailored to Client D's operational needs, as well as a thorough analysis of data ownership structures and user access controls. These components laid the groundwork for a secure and efficient data ecosystem, ensuring that data could be both trusted and appropriately accessed across the organization.
Client J built an Asset Liability Matching model in Excel for pricing a product that requires an analyst to manually adjust nominal amounts to generate the right cashflow profile to match against the expected liabilities.
It usually takes the analyst 3-4 working days to find the optimal asset mix.
We listened to the problem, understood the existing model, devised a mathematical solution by using gradient-descent algorithms, while incorporating some of the manual judgment steps into our design.
With the spec in mind, we attempted a Proof of Concept to demonstrate the accuracy of the results.
Once the client is satisfied with the results, we performed an optimised implementation, running the model in no more than 20 minutes at each run.
Built an automated regulatory reporting system for a major insurance provider, ensuring compliance with FCA and PRA requirements. The system provides audit trails, data lineage, and automated report generation.