INSUBCONTINENT EXCLUSIVE:
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
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
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
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
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
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
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
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
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)
