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The impact of Artificial Intelligence (AI) on the Pensions and Insurance Industries

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Looking forward to 2024, the trajectory of AI technology and how it will transform innovation, trust, security, and efficacy in financial services is very exciting. Here, Stuart Breyer, CEO of Mallowstreet which is an online social network and educational events portfolio for professionals in the UK institutional pensions community, talks about how AI will, and already is, impacting our pensions and insurance industries. 

Artificial Intelligence has arrived. Welcome it.

Like it or not, Artificial Intelligence (AI) is now part of our personal and professional lives. It has arrived in a big way – changing the way we work, live and interact with the world. There have been huge advances in recent years, with conversations around AI shifting from questioning ‘what is it?’ to asking, ‘how can I harness AI’s power to actually apply it in real life?’

The answer lies in AI’s amazing ability to process vast amounts of data at an unprecedented speed. It can analyse complex data sets to extract meaningful insights – it is currently being used in healthcare to detect cancer and in biotech to develop new drugs that are currently in human trials. It is insanely powerful.

Applications to Pensions and Finance

In our industry, everyone is looking for practical ‘user cases’. For me, the answer is twofold – what are the biggest things taking up most of your time that can be automated or outsourced to a computer? And what are the things only you can do?

As humans, we are incredible at building relationships, listening to our clients, understanding their needs, and connecting the dots. We understand the motivation behind the spoken words and know the questions to ask to really get to the heart of the issue.

We all recognise it as a truism – in a professional context, the more time you can spend with your clients, the better you can understand their needs and so can help them achieve a better outcome.  A huge win for the client. Now imagine that you could spend all of your time with clients. This would be the ultimate ‘win-win’.

I hear you – ‘hang on a minute, I need to write up my notes, synthesise my ideas, send the client a report’ – effectively hours of work are required to support each hour I am with a client. The dream I’ve just outlined is bonkers. 

But here’s where AI can help. Today, in the institutional market, asset managers are using AI to write up their internal call reports, allowing for consistency across teams. Trustee Boards are using AI to produce their draft minutes and flash action points immediately after a meeting. Investment consultants are using AI to ensure consistency of messaging and advice.

And I’ve seen IFAs start to adopt similar techniques. By simply recording a meeting and using AI-powered tools, it is possible to get a full (and accurate) summary of the conversation, capture all the questions, identify action points, and even draft an initial report to send back to the client. All done in minutes. All the IFA has to do is review, make any necessary corrections, and they are off to meet their next client. The efficiency gains are incredible. 

Start finding your own use cases

With so many tools available, it can be an overwhelming and complex landscape to navigate. Begin with the end in mind – define the problem you are trying to solve, and find the tool to help. Take one step at a time. Speak to colleagues and friends and get their advice. Start experimenting – trial and error will quickly help you see what helps, and what is a gimmick.

To solve our AI challenges, my business built SOFI – a tool designed to help save time, check messaging, improve delivery, monitor performance, and capture questions. We use it every day. And every day, we come up with ways to make SOFI better. New applications. New ideas. New use cases.

I encourage each of you to do this too. Identify the problem you are trying to solve, and start testing with different tools to help you solve it. Simply spend a few hours each week, and I think you will be amazed at the results. And start today – be creative and be open to being wrong and, most importantly, fail fast and move on to the next solution. I have no doubt you will find your way to do AI and never look back.

Are humans ultimately going to be replaced?

With the introduction of any new technology, the question of ‘what will the role of the human be?’ always quickly surfaces. The exact same question was asked with the invention of the steam engine, the calculator, the fax machine, the personal computer, and the smartphone. Each time there has been a step change in productivity. While some jobs were certainly destroyed, far more new jobs were created as a result. In the world of AI, you now have ChatGPT Prompt Engineers in high demand. This job didn’t exist 18 months ago, and I believe many more such roles will be created in the coming years.

Ethical considerations when using AI

How many times have you downloaded something from the App Store, clicked ‘accept terms and conditions’ and simply carried on? I’ve done it countless times, with no real idea of what I’ve signed up to. We all have. Consumers must be able to understand what companies are doing with your data. In our business, we make it really clear upfront: this is your data, and you own it.

I’ve been talking up until now about AI as a force for good. Of course, there is another side of the coin. People can use AI to hone scams, generate fake material, intimidate and create ‘deep fakes’ (computer-generated lifelike images), among other things. The sad truth remains – those people who want to commit malice or fraud will always do it, and AI is simply another tool they can use to do so. To this point of misuse, I don’t have an answer – perhaps in the future AI itself can be used as protection against malicious AI programmes – I’m sure (and I hope) something like this is in the works.

We must also understand the principles behind the way an AI model is constructed. How is it trained? What biases are embedded in the model (conscious or unconscious)? What dataset was the model based on? How accurate are the results, and can I trust them? For the user of AI tools, it is so important to validate the results and output from a model. Nothing generated by AI is going to be perfect, but approached with the mindset ‘how can I let AI do 80% of the heavy lifting for me’, will free you up to spend most of your time on the last 20% – providing true value and insight on whatever task or project you are working on.

The role of regulation and governance of AI

When it comes to regulation, I feel like the horse has already bolted and we are still looking to see where the barn is, let alone locate the door or the latch. It is going to be tough, if not impossible, for regulation to catch up to AI – the pace of innovation is like nothing I’ve seen before. 

So, in the absence of regulation, governance must take the lead. Not only how firms of AI tools govern themselves, but how businesses purchasing and using these tools govern themselves. Very soon I believe we will see shareholders start to put forward motions at company AGMs demanding more transparency and accountability on AI. I sincerely hope so. Having a simple principles-based approach about how your firm is adopting and implementing AI at your firm is equally as important.

I encourage you to enquire about this the next time AI is discussed or used at your firm – because, as with AI itself, only by asking the right questions can we get the best answers. Create the conditions for its success, and welcome what comes.

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