Raw transaction data, whether internal or coming either form Open Banking or PDF statements, is often noisiy, unstructured, and difficult to interpret at scale. Yet hidden within are powerful signals about financial behavior.
Our multi-vector categoriser maximises the collection of attributes and signals contained in each transaction string — turning raw account data into structured credit and behavioural intelligence.
6 tags associated with each transaction to obtain both credit and behavioural indicators.
Over 40 mapped tags for SMEs and over 60 mapped tags for consumers.
Ability to customise tags and retrain our models to match your specific risk logic.
Coverage in Italy, Germany, the United Kingdom, and the USA — with the ability to easily expand into new geographies.
Process data from Open Banking, PSD2 feeds, and PDF bank statements — all through a single API.
Prestatech’s enrichment engine turns raw transactions into structured, context-rich intelligence by applying six multi-vectorial tags, extracting key counterparties, and clustering behavioral patterns over time.
Raw transaction data, whether internal or coming either form Open Banking or PDF statements, is often noisiy, unstructured, and difficult to interpret at scale. Yet hidden within are powerful signals about financial behavior.
See financial behavior in context.
Detect income, rent, debt payments, subscriptions, and discretionary spending through granular semantic tagging.
Tailor decisions and offers.
Segment users with precision and personalize your credit products, pricing strategies, and customer journeys.
Act on ready-to-use datasets.
Skip manual categorization: get clean, normalized data prepared for analysis, scoring, or system integration.
Enhance internal scoring models.
Strengthen affordability checks and risk logic with enriched behavioral insights derived from actual account activity.