Artificial Intelligence Driving Digital Payments

04 / 04 / 2022

As far as the payments space (payments for goods and services) is concerned, AI has primarily been deployed in transaction monitoring engines (for fraud), automating workflows and processes, chatbots for customer service and to some extent KYC processes.

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As far as the payments space (payments for goods and services) is concerned, AI has primarily been deployed in transaction monitoring engines (for fraud), automating workflows and processes, chatbots for customer service and to some extent KYC processes. There have been instances of AI deployment in stores such as Amazon Go but that has been in a small(ish) scale and not necessarily deployed across the board, but it is the potential forerunner of things to come.

However, the real leap in the application of AI in the field of payments will come when it starts making fully autonomous choices on behalf of buyers of goods and services. It is already happening in a small way with IOT devices.

A recent white paper by Worldline (The IOT Payment Revolution: The Future of Autonomous and Invisible Transactions) highlights how this is set to grow largely in the coming years across multiple years. The paper shows how the confluence of constantly improving AI, the independent rise in people preferring to pay digitally and the increase of IOT-enabled devices is leading to the rise of autonomous payments. Why IOT devices? They are going to be what push consumer digital payments onto a different plane. Why AI? AI is going to be making decisions on behalf of the buyer albeit safely and securely.

In the paper, AI along with blockchain is going to be the key technology enablers for IoT payments. They write: “IoT devices collect large amounts of data that can fuel AI machine learning algorithms and neural network systems to predict consumer behaviour. Extensive training on user behaviour and the transactional context is needed to effectively implement the capability to execute truly autonomous payments on behalf of and with the full confidence of a human user.” To be clear, AI is not some dystopian technology running amok; it is there to assist buyers.

According to the authors, there are 4 levels to fully autonomous payments.

1. Level 0 (Informational): The device has permission to access a user’s bank account. The outcome of such a transaction is only to provide information regarding the permissible data available in this bank account around payments. Example: voice assistant.

2. Level 1 (Permissioned):  The device must request the explicit consent of the user before triggering a payment. Payment permission must be granted by authentication means (e.g., biometric, or non-biometric). Example: Tolls, connected appliances.

3. Level 2 (Conditional): The device makes a payment automatically (without asking for the explicit consent of the user) under pre-defined deterministic conditions set by the user to trigger the payment. Example: smart printer ordering ink

4. Level 3 (Fully Autonomous): The device conducts a payment automatically using a combination of pre-defined deterministic conditions (as per Level 2) and, additionally, uses adaptive behaviours of the device depending on the context. Example: smart fridge ordering.

While there are multiple conditions that should be met for autonomous transactions to happen such as frictionless payments as well as trust, security etc, it is clear that Artificial Intelligence is set to grow at a rapid pace changing the face of payments in a positive manner.

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Sunil Rongala

Head of Strategy, Innovation & Analytics, Worldline India – Member of the Worldline Scientific Community
Sunil Rongala is the Head of Strategy, Innovation & Analytics in Worldline India. A Ph.D. economist, Sunil has deep experience in the digital payments domain, macroeconomic research, product innovation & execution, analytics, risk management, and thought-leadership. He was part of the founding management team of a payments start-up till final exit.

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