By Vinit Sahni
Take note, there is a big push towards personalisation taking hold.
This marks a watershed moment for the financial services industry, with big implications for providers and customers alike. Client engagement evolves, but its time to enter an important phase marked by personalisation of scale.
Personalisation has been mooted for decades, but has proved elusive so far. First came segmentation, in which clients were bucketed according to salient features.
Next came the rise of personas, which aimed to personify segments to get under the skin of clients and understand their psychology and behaviour.
The final evolutionary phase is characterised by high quality, meaningful personalisation, serving the Right Product to the Right Client at the Right Time, tailored solutions not even offered to the ultra-high net worth clients.
But this is where things break down.
Most financial institutions are stuck in the second gear, building personas. This means bucketing people up and pushing (supposedly) relevant content, products and advice at them. Robo-advisors are starting to do this quite well and its an approach with benefits and several drawbacks as well.
It doesn't help. But its the dominant way – till date, the only way – that advisors have been able to get anywhere close to personalised service in terms of scale.
Personas fail clients because its actually very hard to bracket people into groups as everyones different. Its hard to source appropriate information to push to them since taste is highly subjective — even in supposedly monolithic demographics. The result: A lacklustre user experience and even more lacklustre return on investment.
The problem is a foundational one. Before talking about innovative new technologies that can facilitate personalisation, we need to go back to the beginning. We need to talk about clients. Who are they? Where are they? What do they believe? How do they behave?
Financial institutions seeking to scale up their operations tend to club individuals with groups. To make personalisation a reality and reap any attendant commercial benefits, advisors need to take a step back and start thinking about clients, not as statistical groupings with salient characteristics, but as individuals.
Other industries have been doing this for years. E-commerce, for example, has become adept at personalising online experiences, tailoring content, products, even experiences and interfaces according to the characteristics of individual users. While this began with simple cookies and user profiles, its now being optimised with machine learning by giants like Amazon, Google and Tencent.
The rewards are obvious, and big dollars are flowing into this effort.
So is music. Spotify beat Apple and YouTube to become the dominant streaming product of our age because it leveraged machine learning to nail personalised recommendations. Outstanding curation makes the experience of using Spotify far more rewarding than that of its peers. Other players had far more financial muscle, but Spotify deployed its resources more effectively by focusing on what matters most to its customers.
The success of machine learning in other domains is significant. It proves that personalisation is possible with right focus and investment from management. And, perhaps more crucially, it demonstrates that personalisation actually works and people want it.
The success of mass-market consumer products driven by AI has normalised tailored experiences and pushed up expectations. Personalisation is something clients expect, and it wont be long before they begin to reject those who cannot offer it.
You would assume that financial institutions will get this. But they have been slow to adopt new technologies that lead to personalisation and the commercial opportunities that come with it. Thats understandable. Were talking about a big leap, not a small step.
Thankfully, this is now changing. The first move is acknowledging the problem — or, as I prefer to term it as opportunity. The next is taking determined action to address that problem, or capitalise on the opportunity.
As more and more financial institutions hop on to this road, it will set off fierce competition. Forward-thinking firms will capture market share from those who fail to adapt.
The move to personalisation is a game-changer when it comes to client engagement. Were talking about a paradigm shift in financial services, one that most firms will struggle to exploit because they lack the necessary expertise in machine learning to graduate from age-old client segmentation and effectively deliver personalisation at scale.
Codifying sophisticated and nuanced understanding of client psychology and behaviour into algorithms is a big ask. It requires gathering, analysing and delivering huge quantities of data in real-time, by someone with deep domain knowledge.
Its no exaggeration to say meaningful personalisation doesn't currently exist in any financial institution, anywhere in the world. Demand for personalised financial services far outstrips supply. So, the first-mover advantage is huge. The first firms to offer a credible solution to clients are going to win, and win it big.
(The author is co-CEO, Arkera)