Nimbus Direct Insurance — Operations & Technology Platform

The operating-model philosophy, the technology architecture across the core insurance platform, data and analytics and infrastructure and security, the target operating KPIs, the vendor and reinsurer ecosystem and the headcount plan.

Nimbus Direct Insurance Business PlanSection 8 › Operations & Technology Platform

Section 8 · Business Plan

Operations & Technology Platform

The operating-model philosophy, the technology architecture across the core insurance platform, data and analytics and infrastructure and security, the target operating KPIs, the vendor and reinsurer ecosystem and the headcount plan.

8.1 Operating Model Philosophy

Nimbus’s operating model is built on three principles: automate
everything that can be automated, design for the customer’s simplest
journey, and protect against tail-risk through redundancy and
disciplined data governance. The Company will not attempt to build all
capabilities in-house; rather it will select best-of-breed third-party
platforms and integrate them through its proprietary data fabric and
orchestration layer.

8.2 Technology Architecture

The Nimbus technology stack is cloud-native and built around a modern
microservice architecture. Key components:

Core Insurance Platform

  • Policy administration & billing — a
    configurable, API-first policy core (vendor selection from a shortlist
    including OWLS Software, Sapiens IDIT, Root Platform’s low-code
    framework, or a custom build on AWS managed services). Final selection
    based on total cost of ownership and configurability over a five-year
    horizon.
  • Claims management — automated First Notification
    of Loss (FNOL) intake via app, web and WhatsApp; automated triage and
    segmentation; straight-through processing of low-complexity motor and
    contents claims; integration with assessor and panel-supplier
    networks.
  • Underwriting engine — proprietary risk-scoring
    service integrating third-party data (TransUnion credit bureau, eNaTIS
    vehicle data, geospatial risk from Geospatial AI, weather-event
    probability).
  • Customer engagement layer — single customer view
    across web, mobile, contact centre, and partner channels; embedded chat
    and conversational AI assistant.

Data & Analytics

  • Lakehouse architecture — Snowflake or
    Databricks-based data platform combining warehoused and streaming
    data.
  • Machine learning models — production models for
    pricing, churn prediction, fraud detection, claims severity prediction,
    and lifetime value optimisation. All models versioned, monitored, and
    governed under a formal Model Risk Management framework aligned with PA
    Prudential Standard GOI 3.1.
  • Business intelligence — self-service BI for
    product, finance, and underwriting teams; daily executive dashboards
    covering GWP, loss ratio, expense ratio, NPS, and capital
    coverage.

Infrastructure & Security

  • Cloud provider — AWS, with primary deployment in
    the af-south-1 (Cape Town) region and disaster-recovery in eu-west-1
    (Ireland).
  • Information security — ISO 27001-certified
    Information Security Management System; alignment with NIST
    Cybersecurity Framework v2.0; quarterly external penetration testing;
    annual third-party SOC 2 Type II audit.
  • Privacy & data protection — full POPIA
    (South Africa) and Data Protection Act, 2018 (Botswana) compliance;
    appointed Information Officer; data-minimisation by design.

8.3 Operating KPIs (Target Steady-State Year 5)

Operating KPI Year 1 Year 5 Industry Benchmark
Straight-through claims (motor, < ZAR 25k) 50% 85% Industry: 40-60%
Average claim cycle time (motor own damage) 12 days 5 days Industry: 10-15 days
Quote-to-bind conversion rate 18% 26% Direct industry: 18-22%
Self-service transaction rate 55% 82% Industry: 35-55%
Net Promoter Score (transactional) +25 +50 Industry: +10 to +35
First-Call Resolution (contact centre) 75% 88% Industry: 70-85%
Policy-administration headcount per 10,000 policies 12 5 Industry: 8-15

8.4 Vendor & Reinsurer Ecosystem

Critical third-party relationships are summarised below. All vendor
engagements will be governed by formal Operational Risk Management
policies, including a tiered vendor classification (Tier 1:
business-critical; Tier 2: significant; Tier 3: standard) with
corresponding due-diligence, contractual, and ongoing-monitoring
requirements.

Vendor Category Provider Type Role
Cloud infrastructure AWS / Azure Compute, storage, networking; AWS preferred for African region presence
Policy admin core Sapiens / OWLS / Root Configurable rating, policy & claims management
Reinsurer panel Munich Re / Swiss Re / Hannover Re / Africa Re Proportional and excess-of-loss programmes
Credit & risk data TransUnion / Experian Credit-based rating factors
Telematics Cambridge Mobile Telematics / Octo Smartphone-first UBI scoring engine
Payment & collections DebiCheck / Stripe / Adumo Premium debit-order and card collections
KYC / sanctions screening ThomsonReuters / Refinitiv Customer onboarding due-diligence
Vehicle data eNaTIS / Lightstone Vehicle valuation, write-off, and ownership history

8.5 Headcount Plan

Function Year 1 Year 2 Year 3 Year 4 Year 5
Executive & Group functions 12 14 16 18 20
Underwriting, Actuarial & Product 18 26 34 42 48
Claims operations 25 55 115 180 245
Technology & Data 42 62 85 105 118
Marketing & Growth 15 26 38 48 55
Contact centre (sales & service) 60 145 295 445 560
Risk, Compliance, Legal & Audit 10 14 20 26 30
Botswana team 0 0 12 22 32
Total Headcount 182 342 615 886 1,108

Confidential — this business plan is provided to prospective investors and lenders for evaluation purposes only and may not be reproduced or distributed without the written consent of Nimbus Direct Insurance Group (Pty) Ltd.