Finance
ML models that forecast market movements, customer behaviour, and portfolio performance — turning historical data and real-time signals into actionable financial insight.
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Industry overview
Statistical and machine learning models that forecast market conditions, customer behaviour, and portfolio performance using historical data, macroeconomic signals, and transaction patterns.
At a glance
Spreadsheet forecasting breaks under volatile markets. ArrayMatic builds predictive analytics systems that ingest structured financials, alternative data sources, and real-time market signals — producing forecasts that improve as more data flows through them.
From multi-horizon time-series models for treasury teams to customer lifetime value engines for retail banks, we build, validate, and deploy models that sit inside existing workflows. Automated variance reporting flags when actuals deviate from forecast, so finance teams spend time on decisions rather than data preparation.
Key capabilities
Engagements are scoped to your business context — these are the core capabilities we bring to finance clients.
Multi-horizon time-series forecasting (daily to 5-year)
Scenario modelling and stress testing frameworks
Customer lifetime value and churn prediction
Portfolio risk attribution and factor model construction
Alternative data integration (satellite, web scrape, sentiment)
Automated variance reporting and alerting dashboards
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