Turn raw data into
forward‑looking, actionable insight.
ARGenesis designs and deploys Machine Learning and predictive models that help organisations understand risk, demand, behaviour and value with the governance and explainability required in regulated environments.
Actuarial & data‑science led
Predictive model snapshot
Risk score
Policy‑level loss propensity
AUC 0.78
70%
Churn score
Likelihood of lapse or non‑renewal
AUC 0.81
76%
Demand signal
Quote‑to‑bind conversion
AUC 0.84
82%
Severity uplift
Large‑loss propensity
AUC 0.87
88%
Example business output
“Targeted pricing and retention actions on the riskiest 20% of the portfolio deliver a projected improvement of +3–5 pts on loss ratio while protecting growth.”
Turn raw data into
forward‑looking, actionable insight.
ARGenesis designs and deploys Machine Learning and predictive models that help organisations understand risk, demand, behaviour and value with the governance and explainability required in regulated environments.
Actuarial & data‑science led
Built for production, not just proof‑of‑concept
Predictive model snapshot
Risk score
Policy‑level loss propensity
AUC 0.78
70%
Churn score
Likelihood of lapse or non‑renewal
AUC 0.81
76%
Demand signal
Quote‑to‑bind conversion
AUC 0.84
82%
Severity uplift
Large‑loss propensity
AUC 0.87
88%
Example business output
“Targeted pricing and retention actions on the riskiest 20% of the portfolio deliver a projected improvement of +3–5 pts on loss ratio while protecting growth.”
What is Machine Learning & Predictive Analytics?
Models that learn patterns from data to predict risk, behaviour and outcomes.
Machine Learning and predictive analytics use historical data to estimate the probability of future events. At ARGenesis, we combine classical statistical techniques with modern ML methods, anchored in actuarial and business reality, to deliver models that stakeholders can understand and trust.
Where we help
- Pricing and underwriting refinement.
- Loss, lapse and fraud risk prediction.
- Demand, conversion and utilisation forecasting.
- Identifying high‑value and at‑risk customers.
How we work
- Clear problem framing and success metrics.
- Rigorous data preparation and feature engineering.
- Champion‑challenger model strategy.
- Deployment with monitoring and feedback loops.
We bring together actuaries, data scientists and engineers to design predictive solutions that connect clean data pipelines, robust models and business‑ready dashboards.
ARGenesis capabilities
From proof‑of‑concept models to production‑grade decision engines.
Supervised models
• Classification and regression.
• GLMs, tree‑based models, ensembles.
• Calibrated probabilities and lift curves.
Unsupervised & segmentation
• Clustering and profile discovery.
• Anomaly detection and outlier flags.
• Portfolio segmentation for strategy.
Time‑series & forecasting
• Premium, claims and demand forecasting.
• Capacity and staffing forecasts.
• Scenario and stress‑testing support.
Pricing & risk analytics
• Technical price and risk‑based rating.
• Elasticity and price sensitivity analysis.
• Portfolio mix and profitability insights.
Experimentation & uplift
• Test‑and‑learn design.
• Uplift modelling and treatment effect.
• Optimising offers and interventions.
MLOps & monitoring
• Deployment into cloud and on‑prem.
• Drift, stability and performance monitoring.
• Governance, documentation and model review.
Cross‑industry use cases
Predictive intelligence across risk, demand and behaviour.
Insurance
• Risk‑based pricing and underwriting.
• Claims frequency and severity prediction.
• Lapse, churn and retention analytics.
• Fraud and leakage detection.
Healthcare
• Readmission and deterioration risk.
• Utilisation and capacity forecasting.
• Population health stratification.
Retail & digital
• Demand and sales forecasting.
• Propensity‑to‑buy and next‑best action.
• Basket and channel optimisation.
Education & public sector
• Engagement and dropout risk.
• Demand planning and resourcing.
• Outcome and impact analytics.
Part of the ARGenesis technology framework
Machine Learning powers the predictive core of your AI stack.
We integrate ML models with Classic AI rules, GenAI interfaces, Agentic workflows and high‑quality data pipelines, forming one coherent decision‑making ecosystem.
1. Classic AI & Rule Engines
3. Deep Learning & Transformation
5. Agentic AI (Evolutionary)
7. Applied AI (Industry)
Next steps
Not sure where to start with Machine Learning?
We can help you prioritise use cases, assess data readiness and design a roadmap covering discovery, modelling, deployment and governance.