Avo Tech extracts structured data (data in tables and defined fields such as Policy transactions), and/or unstructured data (such as social media postings, typed reports and recorded interviews), which is loaded into the Avo Tech's warehouse.
Avo Tech's Data Warehouse integrates multi-source data by transforming it to align with Avo Tech's enterprise data model. This model is fully compliant with GDPR, IFRS 17 and other insurance related data models. Data from the warehouse can be accessed programmatic via REST API.
Data visualisation enables users to easily uncover actionable insights by presenting a rich set of interactive dashboards and visualisations in graphical, and often interactive graphs, charts, and maps, enabling users to quickly navigate and understand the complex analytical data generated.
Avo Tech's descriptive analytics concentrate on historical data, providing the context that is vital for understanding information and numbers. Descriptive analytics can cover a diverse range of purposes, from operational reporting to benchmarking yearly revenues and sales.
Avotech can provide the predictive Machine Learning insights that can power your customer centric retailing strategies. Avotech has developed proprietary machine learning algorithms optimised for insurance. Our algorithms encompass Life Scores, Propensity and Clustering.
Avotech's Life Score algorithm estimates the monetary value of a customer by predicting their spend. Our Clustering algorithm segments customers into clusters, based on recency, frequency, as well as spend. The Propensity algorithm predicts the products or categories of product that customers are most likely to purchase next.