Advisory Services
Advisory Services
Transforming business challenges into strategic opportunities through expert advisory services, combining deep domain expertise, data-driven insights, and forward-looking strategies to guide informed decisions, optimize performance, and drive sustainable growth across the enterprise.
What We Do
From complexity to clarity — from strategy to practical execution at scale.
IT Strategy for Growth & Regulatory Change
- Define a 3-5 year IT strategy aligned to growth, regulatory, and London Market demands.
- Create a clear, phased roadmap for digital, data, and AI investments.
AI Strategy, Governance & Risk
- Build an AI strategy focused on underwriting, claims, distribution, and operations.
- Set up Responsible AI policy, governance, and model-risk controls.
GenAI & High-ROI Use Cases
- Identify AI and GenAI use cases with clear impact on premium, loss ratio, and expense ratio.
- Run PoCs and pilots, then scale successful use cases into production.
Automation of Core Insurance Processes
- Design an automation roadmap for policy administration, reconciliations, and finance ops.
- Implement automation to cut manual effort, errors, and cycle times.
Cloud & Platform Modernisation
- Develop a cloud and platform strategy for policy, billing, claims, and portals.
- Govern migrations and modernisation with minimal disruption to operations.
Modern Engineering, DevOps & Observability
- Establish DevOps, Agile delivery, and CI/CD across core platforms and digital channels.
- Implement observability to detect issues before they impact customers or partners.
Future-Ready IT Organisation
- Redesign IT teams for product-based delivery (customer, distribution, claims squads).
- Build skills in cloud, data, and AI for internal teams, reducing vendor dependency.
Cybersecurity & Data Protection
- Implement secure-by-design practices across all digital and partner channels.
- Strengthen cyber posture (Zero Trust, monitoring) for regulatory and client assurance.
AI-Led Distribution & Growth
- Use AI to improve appetite fit, pricing guidance, and distribution performance.
- Build analytics to grow profitable segments and reduce leakage across channels.
AI-Led Customer Experience
- Deploy AI assistants for customer queries, policy changes, and servicing.
- Personalize interactions to improve NPS and reduce call centre and operations load.
AI-Led Underwriting & Claims Decisioning
- Use AI for triage, pre-underwriting, document extraction, and fraud indicators.
- Support underwriters and claims handlers with decision-support, not black-box automation.
Core Modernisation & Legacy Decoupling
- Define a path to modernise or wrap legacy systems without 'big bang' risk.
- Design APIs and event-driven integration for MGAs, cover holders, TPAs, and partners.
AI Adoption Timeline & Engagement Model
Weeks 1–3
Discovery & Assessment
- • Kickoff meeting and stakeholder alignment
- • Current state analysis and opportunity identification
- • AI Readiness Report delivered
Weeks 4–6
Strategy & Planning
- • AI strategy and roadmap finalized
- • Technology architecture designed
- • Implementation plan and budget approved
Weeks 7–14
Proof of Concept
- • First AI module deployed (e.g., Claims Processing)
- • Initial results and ROI validation
- • Team trained on AI operations
Weeks 15–28
Scaled Rollout
- • Additional modules deployed (Underwriting, KYC, Quote Generation, Policy Servicing)
- • Enterprise-wide integration completed
- • Full team training and change management
Month 7+
Continuous Optimization
- • Ongoing monitoring and performance tuning
- • Regular model updates and improvements
- • Strategic reviews and innovation planning
Weeks 1–3
Discovery & Assessment
- Kickoff meeting and stakeholder alignment
- Current state analysis and opportunity identification
- AI Readiness Report delivered
Weeks 4–6
Strategy & Planning
- AI strategy and roadmap finalized
- Technology architecture designed
- Implementation plan and budget approved
Weeks 7–14
Proof of Concept
- First AI module deployed (e.g., Claims Processing)
- Initial results and ROI validation
- Team trained on AI operations
Weeks 15–28
Scaled Rollout
- Additional modules deployed (Underwriting, KYC, Quote Generation, Policy Servicing)
- Enterprise-wide integration completed
- Full team training and change management
Month 7+
Continuous Optimization
- Ongoing monitoring and performance tuning
- Regular model updates and improvements
- Strategic reviews and innovation planning
Implementation Roadmap
01
Phase 1: DISCOVERY & ASSESSMENT
Weeks 1-3
- Business Process Analysis: Deep dive into current operations, pain points, and opportunities
- AI Readiness Assessment: Evaluate organizational maturity, data quality, and technical infrastructure
- Stakeholder Interviews: Engage key decision-makers to understand strategic objectives
- Competitive Benchmarking: Analyze industry best practices and competitor landscape
Deliverable
Comprehensive AI Opportunity Report with prioritized recommendations
02
Phase 2: STRATEGY & PLANNING
Weeks 4-6
- AI Strategy Development: Create tailored AI roadmap aligned with business goals
- Solution Architecture Design: Design modular, scalable AI solutions for identified use cases
- Technology Stack Selection: Recommend optimal tools, platforms, and frameworks
- Risk & Compliance Assessment: Identify regulatory requirements and mitigation strategies
- Resource Planning: Define team structure, skills, and investment requirements
Deliverable
Detailed Implementation Roadmap with resource plan and budget
03
Phase 3: PROOF OF CONCEPT
Weeks 7-14
- Pilot Design & Setup: Configure AI modules for selected use case (e.g., Claims Processing)
- Data Preparation: Clean, validate, and prepare data for AI model training
- Model Development & Training: Build and train AI models with your data
- Integration Testing: Test integration with existing systems and workflows
- Performance Validation: Measure KPIs against baseline metrics
Deliverable
POC Results Report with validated ROI metrics and learnings
04
Phase 4: SCALED IMPLEMENTATION
Weeks 15-28
- Full Deployment: Roll out AI solutions across target departments/functions
- System Integration: Connect AI modules with enterprise systems (CRM, ERP, etc.)
- User Training & Change Management: Comprehensive training for all stakeholders
- Process Optimization: Refine workflows based on POC learnings
- Performance Monitoring: Establish dashboards and KPI tracking
Deliverable
Fully operational AI system with trained teams and monitoring in place
05
Phase 5: OPTIMIZATION & GOVERNANCE
Ongoing - Month 7+
- Continuous Performance Monitoring: Real-time tracking of AI model performance
- Model Refinement & Retraining: Regular updates based on new data and feedback
- Process Optimization: Identify and implement efficiency improvements
- Governance Framework: Establish AI ethics, compliance, and risk management protocols
- Quarterly Business Reviews: Strategic reviews of ROI and alignment with objectives
- Innovation Roadmap: Identify new AI opportunities and emerging use cases
Deliverable
Sustained value delivery with continuous improvement and innovation
Ready to Transform Your Business?
Partner with proven expertise in digital transformation, AI adoption, and enterprise modernisation to drive measurable business impact.