Today, customers can be in touch with their bank using a laptop, a tablet, a smartphone or a smart watch. The advantages of such connections are pumped up by the development of the market of the innovative IoT in banking and finance, which allows banks to collect more data about their customers’ preferences, behavior, and needs. The use of IoT technologies ensures the collection and analysis of large amounts of banking information. Banks can use the obtained data to better understand and track the behavior of their customers.
The Internet of Things is still emerging which generate sufficient and attractive returns for investors. In the future, bank branches will become extinct and banking as a service (BaaS) will become the most important business model, while cloud-based services will become the main banking platform. Though an IoT project will certainly cost a lot to introduce, it will pay off in the long run. When you invest in the IoT, you invest in your future. The winners will be organizations which overcome today’s obstacles to embrace change and capitalize on initial uncertainty.
Banks struggle to soften some negative ramifications of the shift and leverage API, their new weapon, to retain the clients and take banking services to a new level. When done right, Open API has the potential to become a game-changer for banks. Leverage the transformative power of a new age in banking the way top industry disruptors do and see the results soon. Needless to say, technical assistance and consulting should be provided to the bank throughout the whole process of Open API delivery.
The idea of an invisible process seems very attractive, but even then, it’s not truly “frictionless”. As is the case with any new technology coming into the world, we can’t just rush into the invisible approach to the IoT in banking without the right tools and protocols in place. If we want to successfully bring invisible payments to life, an omnichannel environment for end users must surely be on our agenda. Of use will also be such technologies as Machine Learning, Artificial Intelligence, sensors and IoT devices.