gini’s enrichment engine has been trained on millions of transactions from thousands of app users over the years. As a result, our Hong Kong data enrichment quality is higher than any other provider in terms of accuracy, scope and speed.
Our powerful enrichment engine is the product of multiple data sources, public and private APIs, complex algorithms, human intelligence tasks and advanced machine learning models that have been refined continuously over the years.
This enables us to deliver an unrivalled level of quality attributes, structure and context to your raw transaction data in real time, saving you the years of effort it would take to label your data manually or train your own systems.
As a unique combination of data sources, complex APIs, algorithms and human intelligence tasks — improved and refined continuously over the years — gini’s powerful enrichment engine delivers an unrivalled level of quality attributes, structure and context to your raw transaction data.
Powered by machine learning, our enrichment engine saves you the years of effort it would take to label your data manually.
Informed by the spending habits of our app users, plus more than 1,000 descriptive tags, the quantity and type of categories we use has evolved to achieve optimal relevance, clarity and workability for the user.
gini’s categories distinguish between each sub-brand of conglomerates, and include even small vendors not equipped for credit card payments.
Plus, gini categorises merchants by their business names, rather than their legal company names which often differ greatly by industry. All this ensures a high degree of accuracy that cannot be achieved by any other provider.
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