Key areas of opportunity
Fragmented architectures & data models
Legacy systems that operate in silos make it difficult to gain a unified view of customers, risks, and operations, which is critical for making informed business decisions.
Replicated systems
Multiple instances of similar systems perform the same functions, leading to inefficiencies and increased costs for maintenance and integration.
Incomplete data models
Data models that aren't fully accurate or complete can lead to a lengthy and complex decision-making process. For insurers, having reliable and comprehensive data models is essential for risk assessment, policy pricing, customer service, and regulatory compliance.
Use cases
Use Case #1 #1
Use Case #2 #2
Use Case #3 #3
Use Case #1
Rapid insights, impact & decisions
Inability to extract, analyze, and act on data from multiple systems fast enough materially harms decision-making and reaction time.
Opportunity
Empower self-service analytics and systematic use of machine learning for automated, high-velocity insights at the point of impact.
Technical approach
- Cloud data platform structured for analytics with automated pipelines
- Accelerated BI and advanced analytics powered by machine learning
- Instant data discovery and insights consumption by business users in decision contexts
Use Case #2
Trusted metrics powering growth
Misaligned metrics across distribution channels, inability to track performance vs targets inhibits profitable growth.
Opportunity
Enable coherent tracking of operational KPIs linked to growth goals providing full visibility into progress.
Technical approach
- Centralized enterprise data dictionary
- Federated master data approach
- KPI dashboard alignment processes
Use Case #3
AI-powered risk assessment
Industry disruption and emerging risks require continuously updated risk models, impossible in legacy systems.
Opportunity
Consume latest structured and unstructured data in prebuilt risk analysis models rapidly validating new assumptions.
Technical approach
- Future-proof scalable data science platform
- Continuous pipeline from raw data to ML features store
- Library of AI risk assessment models
Our technical capabilities
Platform engineering
Our platform engineering expertise ties together software delivery and organizational prosperity. We architect robust platforms in payments, Know Your Customer (KYC), and customer engagement, enhancing both corporate performance and individual wellbeing in the insurance sector.
AI integration
Exploring AI's horizon beyond automation, we're keen to gauge market predictions for the next decade. Our focus is on integrating AI across industry practices, setting standards for use, and maximizing its benefits for insurers to shape a future-ready market.
Modern data architectures
With cutting-edge data architectures, we empower clients to centralize data capture and transition to real-time insights. Our approach revamps analytics landscapes, ensuring readiness for a data-centric and AI-enabled future within the insurance industry.
Digital transformation & legacy modernisation
We navigate the delicate balance between innovating and honoring legacy systems. Our consultants are adept at driving digital transformation, executing change with clarity, and positioning insurers for transformative success in an ever-evolving market.
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