You're now leaving O-IM

O-IM’s website and/or mobile terms, privacy and security policies don’t apply to the site or app you're about to visit. Please review its terms, privacy and security policies to see how they apply to you. O-IM isn’t responsible for (and doesn’t provide) any products, services or content at this third-party site or app, except for products and services that explicitly carry the O-IM name.

Cancel Proceed

Coming soon ...

Close

Embracing Hyper-Personalisation in Financial Planning

The recent State of the Advice Nation Lang Cat research report predicted 58% of advisers would adopt AI in the next five years. But how and why?

AI in Financial Planning is a fascinating concept and is already making huge in rows. Seemingly the centre of every event I attend, AI is clearly going to revolutionise how Financial Planners can deliver advice to their clients. Understanding how AI can be used effectively now and ensuring you have a partnership with specialists in that field to take advantage of future AI developments is key.

One of the major issues in Financial Planning currently is the amount of people in the country that do not receive financial advice. It is estimated just 10% of UK adults work with an adviser and that needs to change. Why is this the case?

Well for multiple reasons but, in my opinion, the main one is that it is not worth an adviser’s time currently to work with clients that don’t have considerable investable assets and that is fair enough. Advisers I speak with want to help more people, but they are restrained by only having so many hours in a day.

So, the theory is using technology to remove the administrative burden placed on advisers and free up more time for them to work with more clients. However, Financial Planning is a hugely personal endeavour and scaling up client to adviser ratio is great for reducing the advice gap but we need to continue to be able to provide a very personalised serviced to individuals and families at scale.

AI will allow advisers to reduce their admin time, freeing up more time to spend with more clients and provide an ever more personalised service to those clients than perhaps they even can do now. That is where the concept of ‘hyper-personalisation’ comes in.

 

Understanding Hyper-Personalisation in Financial Planning

What is hyper-personalisation?

Hyper-personalisation refers to the process of using data, machine learning and large language models to deliver fully personalised services to individuals based on their habits, data and interests, but at significant scale.

It is the next iteration of data segmentation which groups individuals based on their profiles to enable businesses to create a ‘customers like you’ style approach to personalisation. A good example is recommended products on shopping sites like ASOS.

Instead, companies can utilise data around the individual to produce a fully bespoke and personalised service to each individual consumer. A prime example of this is Spotify Wrapped, the yearly round up of individual activity on the music streaming service which provides a bespoke summary of the user’s habits to millions of people. This creates a highly personalised feel to a mass market product.

Imagine this in practice in Financial Planning. Instead of the approach being based around mass consumer trends of generalisations around age, gender and occupation determining where someone may way to invest or what objectives are most likely to be relevant to them, AI can collate thousands of data points very quickly to recommend very specific investment and planning angles for advisers to explore. This represents a shift away from demographic based segmentation to individualised, data-driven insights in financial planning.

Now this is largely the essence of Financial Planning as it is now, an adviser meeting with their client, establishing a relationship, understanding what they want to achieve and producing a financial plan accordingly, but this approach has the potential to produce even more personalised solutions on a mass scale. After all, large data institutions probably know us better than we know ourselves.

 

Benefits of Hyper-Personalisation

The benefit to advisers of hyper-personalisation is clear: being able to provide a fully personalised financial planning proposition to more clients, increases the commercial capabilities of a firm. Furthermore, being able to use large data sets and AI to sift through the thousands of investments, and other product options, in the market will enable advisers to truly be whole of market moving forward and in a seemingly ever-expanding market. How else are advisers supposed to reconcile all the options available in the market and identify the right one for that specific client?

A further benefit for advisers and advice firms is the ability to support different types of clients and engage future clients, way earlier. I’ve written previously around low-cost Financial Planning approaches and how most people of my generation don’t need highly personalised advice as the needs are common and simple: saving for a house or getting into investing for the first time for example. But AI can take a low-cost solution advisers can implement but with it being fully personalised to the client. Game changing!

Lastly for advisers, AI can unlock new lead generation opportunities by sweeping data, identifying specific niches and adviser operates in and connecting a fully personalised list of new prospects. Plug that into something like Apollo.io or Hunter.io and those leads can be contacted with no engagement from the adviser at all. Warm, verified, and personalised leads done for you with tech capabilities that are already available.

But what are the benefits to the client?

Financial Planning is a hugely sentimental process and the client feeling like they are completely understood throughout the planning is essential in building trust as well as an accurate and reliable plan to ensure specific objectives are met. For the client, being fully understood through both a quantitative analysis of their data and engagement with an adviser will lead to being better understood and producing better results.

I am sure there are situations where human bias or a reluctance to share all the information necessary with an adviser to produce the best results occur. AI could remove difficult or unknown areas of data which prevent the best plan being put in place by sweeping the millions of data points we each have on us on the internet.

 

Challenges and Considerations

There are of course considerations around this integration to be aware of. Data privacy and security is essential in building trust around technology, as is ensuring the large language models and machine learning systems do not have biases in them. This can only come with time so whilst the software is available for advisers to implement these plans now, they may be waiting for peers to take the first leap and test the water. I think this is a risky approach. AI is moving so quickly; firms might not be able to afford for others to get ahead and stay there.

The other consideration is the regulator. Advisers need the regulator to up to speed with AI to build trust and provide guidance around implementation. So far, we have had some comments from the FCA but not much since the Culture and Conduct Forum in November 2023. Just last week the Government wrote to the FCA (15th February) giving them 10 weeks to issue an update on work done towards frameworks, procedures and how AI sits within current regulation. Watch this space!

 

The Future Landscape of Financial Planning

AI as an enabler for larger scale advice on an even more personalised basis. AI is not a replacement for adviser relationships, and I am a firm believer that clients want human interaction before taking meaningful action on their plan and this isn’t going to change anytime soon but some clients don’t need a full financial planning proposition.

Unlocking the next generation of clients through and AI integrated ‘incubator’ style approach is a very interesting way of utilising AI. Creating a hyper-personalised low-cost solution that ties in the next generation of younger clients will enable advisers to connect and engage with children of existing clients or those that don’t yet have enough investable assets. Advisers are tight for time as it is, let alone having time for business development so let the tech do it for you!

 

Conclusion

AI is already here in Financial Planning. Ensuring you are aware of all the opportunities, both current and future, will enable future proofed planning businesses to be built. The pace of which AI is developing and burrowing itself into every industry is mind blowing so early adoption is going to be essential in getting ahead and staying there.

Hyper-personalisation is a result of AI integration into Financial Planning, and I think it is the key to unlocking the advice gap in the UK to provide financial planning.  We are in an era of unprecedented wealth transfer and change in our market which is very exciting. This advancement in technology unlocks human-like responses and interactions at scales that have not yet been possible.

I would love to get feedback on this and discuss your thoughts on where you see AI being deployed in Financial Planning and the wider Financial Services industry so please do message me for further discussion!

Your capital is at risk, and you may not get back the amount originally invested. Investors should remember that past performance is not a guarantee of future results.
Please see the O-IM Glossary for any definitions.