Companies like Amazon, and Facebook are setting the standard for customer expectations and customer experience.

This includes everything from understanding the whole customer journey, defining the context and personalizing it, to ensuring the payment experience is seamless and frictionless without compromising security.

Personalization and contextuality in the mobile payment domain is evolving with Machine to Machine payments. As the popularity of in-app experiences grow, like those used by Uber, there’s a corresponding need for a streamlined IoT enabled payment system. Billions of IoT devices are connected all over the world, and it won’t be long before almost all of our devices and technologies are connected through IoT.

Our technology is communicating with each other, or Machines are exchanging data with other Machines without the help of people. IoT improves this Machine to Machine interaction significantly, changing the experiences that we’re having as consumers.

The Machine to Machine, or M2M, connections market is predicted to reach $27 Billion by 2023, so we’re going to see an increase of IoT and M2M payment solutions. M2M is a term that is sometimes used interchangeably with IoT. But they’re actually different concepts. IoT technology is how devices communicate between diverse systems, and M2M refers to isolated systems that don’t communicate with each other.

When applied to M2M, Artificial Intelligence and Machine Learning enables systems to communicate with each other and make their own autonomous choices. So M2M payments can include a multitude of scenarios, like transactions based on customer behavior without our knowledge. Regulations, ethics, and business rules can be included in intelligent machines through smart contracts, which are stored on blockchain technology. This increases the security of M2M transactions and enforces contract performance. Device agnostic solutions, like automatic SIM activation for telecom, also helps to support M2M capabilities and communication, and optimizes network resources. Furthermore, contextualizing payments with data and analytics helps facilitate fraud detection and terminal tracking, defines customer profiles, and blocks stolen devices.

The M2M payment system is going to continue to significantly disrupt the payments industry, simplifying transactions in emerging markets. The combination of IoT, AI and Machine Learning, and smart contracts are creating opportunities for new, different purchasing behaviors. And integrating the user experience with apps like mobile wallets, will cause M2M financial activities to be even more commonplace in the future.

I’d like to thank Mahindra Comviva and Srinivas Nidugondi for their insight.

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Ronald helps data driven companies generating business value with best of breed solutions and a hands-on approach. He has been recognized as one of the top 10 global influencers by DataConomy for predictive analytics, and by Klout for Data Science, Big Data, Business Intelligence and Data Mining and is guest author on leading Big Data sites, is speaker/chairman/panel member on national and international webinars and events and runs a successful series of webinar on Big Data and on Digital Transformation. He has been active in the data (process) management domain for more than 18 years, has founded multiple companies and is now director at a Data Consultancy company, leader in Big Data & data process management solutions. Broad interest in big data, data science, predictive analytics, business intelligence, customer experience and data mining. Feel free to connect on Twitter or LinkedIn to stay up to date on success stories.

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