The augmentation of raw transactional data is a key step in building financial apps that assist consumers in understanding their financial spending patterns. CaaS makes this pain free and frictionless by combining big data driven AI for auto categorisation and a 'nifty' data structure that persists personalised category preferences via ‘assisted categorisation’.
The CaaS data structure enables eWise to map category consensus over time, geography and language to produce the highly performant and accurate truth API.
Companies can now plug straight into eWise's globally aware truth API via the fully managed service of CaaS API. CaaS lets businesses focus on their core business strategy.
The platform transforms and processes all of a users' transactions from their bank, credit card provider, brokerage firm, pension, utility provider or loyalty programme and augments that raw data with categories, merchant and payment method. eWise’s Data Science team developed optimised algorithms that parse and construct data structures that enable language agnostic auto-categorisation of transactions.
eWise understands through experience that auto-categorisation can never be 100% accurate using a fully automated AI tool. Machine learning models have a degree of error, spend attribution can be extremely personal and CaaS turns these attributes of the process into a feature and not a problem. “Assisted Categorisation” allows users to control their preferences and work in collaboration with auto categorisation. CaaS has all the components to intelligently and fluidly manage categorisation; coverage, category calibration and custom categories.