Financial services are the epicentre of the Me2B economy. What end-users buy, sell, save, borrow, and when, are finger-print unique.
For this data to be valuable it must be intuitive, scalable, predictive, and completely inclusive of the consumer’s entire financial position. Above all, in this increasing age of consumer rights and ownership, it must be shared by the end-user. For this to happen, the institutions processing it must be trusted.
The end-user’s growing confidence in the personal data economy is illustrated in the proliferation of personal financial management software, whereby consumers measure their spending patterns against their savings goals, prosecuting a real-time cost benefits analysis of their chosen goods and services. This opens up a range of additional services of value, to the micro start-up to the established retail bank, all designed to give the consumer, (frequently the millennial consumer) control of their financial health, on the go.
Combined with the two-way flow of ideas between businesses and consumers, i.e Twitter, it’s no wonder that end-users are so confident.
Yet rising consumer confidence characterised by the ‘me’ in the equation is not enough. For technology providers to utilise the Me2B economy,the supporting architecture must be in place:
The APIs that collect and translate data must interpret the language in which this data is recorded, and be responsive to the culture in which the transaction occurs
Transaction data categorization must be crowd-sourced and augmented with AI, lending data scale, accuracy, and commercial value
As technology providers, we must find the best metrics to measure the value of our software. We do this not just by measuring transactions and end-user engagement but also by illustrating customer behavior and motivations, obtaining predictive spending choices
Most importantly, as technology providers, we must give end-users ultimate control over their data. End-users must be able to choose who has access to their data, for how long, and for what reward: this could range from loyalty points to a better interest rate on a loan. The challenge, therefore, is enabling this win-win, a fair exchange of value for access to the consumer’s data.
End-user data control was core to eWises creation in 2000, when we wanted to combine the usability and user interface of social platform with the security of a retail bank. eWise invented client-side data aggregation enabling users to aggregate, store and encrypt their financial data on their own device, rather than in the cloud. With the eWise Ageis Personal Data Vault an end-user’s log-in details are never shared with a third party, and financial data aggregation occurs on a user’s personal device; outside of the traditionally more porous interaction between client and server.
eWise is deployed by leading retail banks and financial institutions and our business model is based on end-user take up. Our goal for the near future is to continue to overcome the challenges of our conception: delivering personal financial management products based on secure, pristine data, wholly owned by the end-user.