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.
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.