Engineering Data Platforms
and Actuarial Applications
for Insurance and Finance
Specialising in enterprise data governance, regulatory compliance, productionising actuarial models on Azure Databricks and more for the insurance and finance industry
Our Services
Data Engineering
Build robust, scalable data ELT/ETL pipelines and infrastructure tailored for insurance operations.
Data Governance
Ensuring PII protection, data lineage, reproducibility, and metadata management, with UAC and cataloguing for full compliance with FCA, PRA and more.
Data Ingestion
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 Optimisation
Performance tuning and optimisation of data platform, parallelisation, actuarial models and more.
Custom Applications
Development of front end and backend solutions for in-house actuarial models, optimised with user-friendliness and performance in mind.
Analytics Solutions
Generate automated reporting and build dynamic visual dashboards from your data platform.
About Us
We are a specialised 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 organisation stays ahead in the digital age.
With a deep understanding of insurance industry challenges, we deliver tailored solutions that drive efficiency, compliance, and innovation.
Why Choose Us
- Industry-specific expertise
- Proven track record
- End-to-end solutions
- Compliance-focused approach
- Scalable architecture
- 24/7 Support
Meet the Team
Case Studies
A New Data Platform
- Transformed from spreadsheet silos to enterprise-wide data model
- Established foundational data governance guidelines
- Designed scalable architecture for centralised data platform
- Implemented proper data ownership and access controls
Client D had traditionally operated as a spreadsheet-driven organisation, 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 organisation 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 standardisation. 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 centralised 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 organisation.
Build and Optimise an Actuarial Model
- Reduced model runtime from 3-4 days to 20 minutes
- Implemented gradient-descent algorithms for optimisation
- Preserved manual judgment steps in the automated solution
- Delivered proof of concept before full implementation
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.
To address these challenges, we engaged key stakeholders across the organisation 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 standardisation. 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 centralised 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 organisation.
Regulatory Reporting Automation
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.
- Implemented automated data validation
- Created comprehensive audit trails
- Developed automated report generation
- Reduced reporting time by 75%
Recent Insights
Challenges in Delivering Production-Grade Actuarial Applications
Ready to Solve the Hard Problems?
We work with insurance and finance teams to build scalable systems and solve technical challenges others avoid, whether it’s actuarial-grade models or AI-enabled platforms.
Our expertise also extends to designing robust data infrastructure that ensures strong governance, seamless accessibility, and secure data democratisation.
If you’re tackling something complex, let us help you make it manageable and make it happen.
Give us a message.