The future of AI in banking and bancassurance

15 Dec, 2022

No conversation about the digital journey of banking and bancassurance would be complete without touching on the application and use of Artificial intelligence (AI) and machine learning (ML) within the industry from a functional and ethical viewpoint. 

AI is not new technology, with the concept first being explored in 1950. However, AI quickly evolved into machine learning and, more recently, deep learning. 

The exploding adoption of this technology in the past ten years has brought to light some complex questions. 


Applications of AI and ML in banking

AI has been part of the banking landscape for several years. Many online actions that occur are a result of a conversation initiated by a chatbot. Chatbots work 24/7 and can handle the bulk of everyday, mundane tasks such as balance enquiries, mini statements, resetting passwords etc. These repetitive, low-risk tasks are perfectly left for AI to perform, reducing the load on human resources and freeing them up to handle the more complex transactions. 

The other integration of AI into banking that is mature is fraud detection. Anyone who has ever received an alert or had their credit card frozen due to what their bank considers ‘suspicious behaviour’ has been on the receiving end of this intelligent algorithm, designed to pick up unusual spending patterns and report it for further investigation. AI can also pick up on internal fraud and employee theft of data and money.

Application of AI and ML in insurance

As with banking, the main application of AI in insurance is chatbots, fraud detection and processing immense amounts of data. 

As AI technology becomes widespread, it will enable the gathering of an enormous amount of data that will reshape claims, distribution, underwriting and pricing or insurance. 

By 2050 experts estimate there will be up to one trillion wearable devices, all tracking and gathering information that can help determine the individual's insurance risk. They can also enable insurers to drive and reward healthy habits, such as discounts and incentives for walking over 10,000 steps daily. Robots are likely to be a large part of the future of the automotive industry when driverless cars become mainstream, and the risk of collision will be heavily reduced.

The future of insurance could look very different; new insurance applications could take mere minutes with very few questions, as enough data is available for AI to do split-second risk assessments. Smart contracts could set up payments immediately, and annual renewal could be a thing of the past, with AI guiding customers through any suggested changes to their insurance portfolio in real-time based on the data collected. Claims are processed the same day when they are lodged; AI will advise what, if any, proof is required. Drones can be dispatched to take images, funds are automatically transferred for any claim being paid out, and service agents are automatically notified and booked for repairs. 

The questions about AI

Nearly 80% of banks know of AI’s potential benefits to their sector. These benefits include a better customer experience and increased efficiency and profit. This makes AI technology very attractive, but some questions must be considered before it is adapted into all aspects of mainstream banking. 

Two main themes underpin the more complex constraints surrounding the use of AI.

First, in a highly regulated environment, banks and insurers cannot currently abdicate responsibility for their actions to service providers. This means that the organisation is responsible for every decision the software makes.  

Second, as computers are created, designed and programmed by humans, they inherit human bias, conscious or otherwise. These biases affect everything the machine learns and processes and can have severe and unintended consequences. 

A high-profile example of such a problem was in 2019 when tech entrepreneur David Heinemeier released a scathing series of tweets when he received a credit limit 20 times higher than his wife’s after applying for an Apple Card even though she had a higher credit score and they filed joint tax returns.

If we use Heinemeier’s example, the company was accused of being sexist in their decision-making processes – however, it was the algorithm, not an individual, making the decision. The developers programmed the bias into the software, but the appropriate checks and balances were not in place. So where, then, does the blame lie for the decision? With the algorithms creator? Or with the organisation that uses the algorithm. 

“Responsibility is one of the core issues of AI ethics. The question of who is responsible for any piece of tech at the point of its use becomes very complex within organisations.” 

Giles Cuthbert, Chartered Banker Institute

Let’s assume that the institution is entirely responsible; they then need to protect their integrity by thoroughly supervising the development of AI tools to ensure they comply with regulatory requirements – but who within the current framework has the expertise to function as the watchdog?  

And what about the driving force behind AI’s decisions for the organisation? For example, would this influence the outcome if the software is conceptualised to assess creditworthiness, but its role is to make money through lending?

What is the future of AI?

Whilst there are many issues to work through, AI as technology is not going anywhere. A report released this year by Business Insider claims that 75% of respondents at banks with over $100 billion in assets say they're currently implementing AI strategies. McKinsey & Company estimates that AI technologies could deliver up to $1 trillion in additional value each year. AI is expected to have a disruptive effect on most industry sectors to a level not seen since the invention of the internet. 

Until the legislation surrounding these questions is in place, regulators, banks, and insurers will continue grappling with AI applications' implications. If New Zealand doesn’t look to the future and see a place for AI, we will quickly be left behind on the world stage.

Once AI does become a more significant part of the total portfolio of bank and insurance offerings, it will be essential to partner with providers who understand and appreciate the inherent risk and the regulatory environment that will evolve. 

With over 20 years in the bancassurance industry, AMS is uniquely placed to be that partner. Contact us today to discuss your current and future bancassurance needs.