By Amanda Greenwood,  Myriad Associates & Tax Cloud   

Imagine walking into your office block and – without having to rummage through your pockets for your access fob – the door just swishes open. As you step through it, a friendly voice welcomes you by name. Then, as you’re walking towards your desk, the lights switch-on with every step you take. And, right before you take your coat off, a heater starts to circulate warm air around your desk.

Smart offices, like this one, use the Artificial Intelligence of Things (AIoT) to control access, heating and lighting, and they’re a reality for companies such as Beijing based Terminus Group.

But what exactly is the AIoT? How does it work? And how is it affecting the world of Banking and Finance?

What is the AIoT & how does it work?

The Artificial Intelligence of Things is the brains of Artificial Intelligence (AI) combined with the connectivity of the Internet of Things (IoT).

“While the IoT connects ‘dumb’ devices to the internet, artificial intelligence gives them a ‘brain.’” – Electronic Design

AI makes intelligent decisions by completing tasks, learning behaviour and creating algorithms. Once it’s learned a behaviour it can make intelligent decisions. These decisions are then passed onto a network of connected IoT devices which are embedded with sensors and software so they can perform human-like tasks accurately.

Take Tesla’s, for example. They use connected radars, GPS and cameras to make proactive decisions based on the current driving conditions and environment. For instance, if it’s cold, wet and raining, the AIoT will make the intelligent decision to turn on the windscreen wipers and activate the heater, without any human involvement.

Or look at smart shops: connected cameras use facial recognition technology to identify customers and collect data based on their shopping habits and preferences. This data is then analysed and used to predict their future behaviour which retailers can then use to make informed decisions on product development, marketing and purchasing.

So, that’s what AIoT is and how it works, but how will it affect banks and financial institutions?

The future of AIoT in banking

Around 80% of banks are aware of the benefits that the AIoT is likely to bring to the sector: increased efficiency to processes, the chance to provide frictionless customer experiences and the opportunity to beat the competition.

But how? What does the future of AIoT in banking actually look like?

Examples of what the AIoT can accomplish in banking

“FinTech is combining industrial IoT as well as AI to test banks in giving immediate support to customers.” – Tech Native

Fraud detection
Several innovative companies have started to develop a form of Behavioural AI designed to help financial organisations spot unusual or fraudulent behaviour, through the detection of abnormalities.

It’s a machine learning model that’s trained to pick up abnormalities. It tracks, analyses and collects data from thousands and thousands of customer bank transactions. These transactions are linked to IoT devices such as smart ATMs, mobile apps, smart cards, or paywear items.

Some transactions will contain incorrect information or information that doesn’t match what’s in the system. These transactions will be labelled as fraudulent, and the suspicious behaviour will be logged and learned. An algorithm will then be created so that the Behavioural AI model can establish which transactions are fraudulent and which are genuine.

Operations

Other companies are investing in R&D to build smart ATMs. Smart ATMs are multi-channel solutions for banks which include things like physical ATMs, asset financing services and fleet management for the ATMs. This connected solution will help banks and financial companies improve the operational productivity and security of their ATM fleets.

It works like this: AI collects business insights and provides recommendations to banks on how they can improve their operations to increase both the productivity of their ATMs and the security of their customers.

Similar to the fraud detection model, this machine learning model is trained on millions of ATM transactions. It collects, analyses and builds algorithms based on things like:

• How many cards have been declined
• How long transactions take to complete
• How fast the ATMs are serving customers

The algorithm will establish what’s causing the longest customer wait times and the reasons that cards are being declined. It will also determine how long customers are spending at the ATM screen, how much traffic the ATM is handling and how fast it’s dealing with transactions.

The system can then use these findings to recommend changes that will improve business operations.

“By using IoT and AI in payment methods, banks are working to transform their back-end processes and integrate them with front-end systems to develop a holistic and robust finance operation.” – ISG

AIoT is set to take the banking world by storm. Soon, you’ll be able to provide your customers with efficient end-to-end solutions, that are safe, without needing to lift a finger.