Basiq and Verrency enable banks to drastically improve the quality of their data

Verrency taps Basiq’s platform to enable personalised experiences

Basiq and Verrency have joined forces to enable banks to store clean, categorised and enhanced transaction data – in real-time, at point of purchase. This will uncover new opportunities for banks to offer their customers innovative, and personalised products and experiences.

We are all aware of how ‘unclear’ transaction data can be.  Think of how often customers call banks with queries – they have no idea what an item on their credit card statement called ‘HT Willis Brook’ is.

You may have heard the term ‘garbage in – garbage out’. If a bank stores unclear transaction data when a customer makes a purchase, this data is then passed downstream to other areas of the bank – meaning that inaccurate data gets multiplied across platforms (customer service, internet banking, data warehouse, etc).  

When a customer sees a transaction on their statement that they can’t remember making, they contact the call centre, which often ends without resolution and even more customer frustration. Further to this, the bank is not able to use this customer data to innovate in areas such as credit decisioning, real-time rewards and personalised customer engagement.

Basiq improves the customer experience via expense categorisation

The Basiq API enriches bank transaction data in real time, via the Verrency connection into the payment stream.  This enables customers to immediately see their transactions tied to a merchant and location, as well as an array of additional information.  

Further, by seeing merchant name in real-time, banks can enable real-time rewards, paying with points, white-listing and black-listing transactions, without any POS integration or merchant training required.

For the bank, this enriched transaction data is then leveraged through a customer’s banking lifecycle. Basiq enhances the transaction data real-time using over 50 different data sources. It cleans up the transaction, providing business information, exact location of purchase and type of expense and also applies industry standard classification of expenses, which enables banks to analyse spend by category.  

Example:

Banks can then use this enriched transaction data downstream to:

• resolve call centre/online banking queries related to unclear transactions
• personalise communication and products for their customers based on location data and spending patterns
• pre-fill forms and assist with credit decisioning for home loans
• create partnerships with merchants based on customers historical spending habits

This exposes a phenomenal opportunity for banks to offer their customers innovative and personalised products and experiences – tailored down to a merchant and location level – that they have not been able to in the past.