As banks are now looking towards monetizing data, experts suggest that it offers very small incremental revenue
Banks are racing to monetize the vast volumes of data they hold. In this digital era, information about customer preferences, spending patterns, and preferences is worth its weight in gold. Banks are also focusing on trading data to predict stock moves as well as collaborating with retailers and use AI to speed up credit decisions.
With tech giants like Google and Amazon leveraging customer data to boost revenue, banks are not far behind and Barclays, HSBC, and JPMorgan are trying to narrow the gap.
Observing the trend, experts believe that this data use and monetizing has increased, as banks understand their clients better than anyone else. A lot can be done with the personal data collated from the clients.
This change is due to the EU rules that were introduced last year that allows technology companies to have access to customer’s bank data if they have permission. Experts believe that even though the law places emphasis on the security of data, sensitive data can still be exploited as customers are not aware of how protective strategies.
According to a recent poll of 27,000 EU citizens, less than a third are aware of their data rights, and only 13% read privacy statements fully. Though banks do not disclose the amount, they receive from analyzing and marketing customer data as well as the other ways in which they monetize the information. Experts believe that compared to the billions that banks earn from lending and trading, the amount generated from data is quite small. However, it is an excellent low-cost way to generate some marginal incremental revenue.
One of the ways banks are monetizing data include tie-ups with retail firms. According to Reuters, Lloyds and Santander can get exclusive offers from retailers post joining a digital loyalty scheme that is run by Cardlytics, a US-based data-advertising firm. As per the scheme, spending data is used to give customers discounts at shops, to which in return, banks get a percentage of the fee charged by Cardlytics as it runs the campaign. Cardlytics uses insights on consumer behavior that help retailers tailor as well as fund the offers and discounts.
Another example is BBVA that operates an online marketplace for other companies to purchase the anonymous transaction data generated from BBVA cards and PoS terminals.
Although the data is shared only after the permission of the customers to receive offers and they remain anonymous, privacy experts warn that the scope for abuse still exists, for example, to target indebted people with offers for high-interest loans.
Though these efforts are aimed at making use of data for highly targeted initiatives, there are quite a few barriers to effectively monetizing data in the industry. From IT and organizational silos to a shortage of data science skills talent and organizational structures built around monetizing transaction services rather than data hinder data monetization.
In addition, most banks do not have full visibility into data. According to an Accenture survey, almost 70% of banking respondents agreed to hold hidden value within their operational data and capabilities that have to be leveraged.
Reaping the value for hidden data requires banks to catalog their full inventory of data assets and map out a strategy to use those assets to the highest extent possible to benefit. Failing to which, consumers can flock to FinTechs and tech companies as they provide cheaper transactions.