Advanced Analytics Insights
by Zaid Kamhawi, CEO, Qarar

In our final article exploring the impact of Artificial Intelligence (AI) in the banking and finance sector, Zaid Kamhawi reveals how hyper-personalised recommendations can help customer success.

Hyper-personalised recommendations are one of the greatest and most profitable value propositions achieved by AI.  That is because banks and finance companies can now offer customers the right product, service or interaction at the right time and therefore increase turnover success and customer lifetime value and equally importantly, is that they can do so while also achieving an enhanced customer experience.

These days, customer centricity is vitally important for many industries and business sector — specifically banks and finance companies — because of their customers’ rising expectations of wanting to bank anytime and anywhere, and they want instant-this and instant-that.  The age of instant gratification has never been more prevalent, together with the obvious migration towards a predominantly online consumer experience since early 2020.  Therefore, the ability for banks to transform by offering intelligent workflows and reinventing their relationships with their customers is the key to success.  This is where AI came in and played the major role.

Firstly, there is no doubt that AI is a big enabler for digitisation.  There is no digital banking journey out there that is not being supported by AI, whether it be tools such as identity verification, virtual assistance, or AI-driven support, to name a few.  Moreover, AI has been able to pick, recognise, decode, and decipher the many thousands of signals that customers are now leaving behind digitally, which previously was not possible.  What this massive gathering of intelligence culminates in is a host of AI tools excelling at their job.  These tools have the capability to analyse and use the data at hand to enhance product offerings or enhance the customer experience by generating and communicating personalised ideas.  

In the Middle East, Qarar has seen first-hand an example in Saudi Arabia where banks are applying this hyper-personalisation at play.  They are bringing in large amounts of external data about their customers from credit bureaus and other available external sources, and then using that data to provide personalised and pre-approved product offerings to their customers.  They are doing that by looking at a number of influencing factors:

  • The customer’s share of wallet
  • Their affordability
  • What banking products they have with other providers
  • What products they have been applying for
  • Looking at the customer’s risk profile. 

Through AI tools, this entire process just takes a split second, then immediately going back to the customer in real-time with a pre-approved credit card, for example.  That pre-approved credit card is completely personalised to that individual; they know their affordability, they know what they can offer them, they know that they want that product — because they have been shopping for it — and they know their risk profile.

Can you imagine the customer satisfaction when they receive a pre-approved product without the need to go through a lengthy application process?  It means a greatly enhanced experience in the whole interaction between the customer and the bank.  In this era where customer-centricity is king, AI tools are a total game-changer.

Another good example that Qarar has noticed is bespoke product offerings.  Many credit card issuers provide customers with the same type of card offers.  In general, everybody that has a particular credit card from a particular provider has the same type of offers on dining, or shopping, or travel etc.  Taking it to the next level — looking at and analysing the large amounts of transactional data and comparing customers — lenders can push customised offers in real-time for customers based on their lifestyle and what they would need.  That means one customer would probably get discounts on travel, while another would get discounts on shopping, or vice versa.  The real-time offering would be highly customised and personalised because AI has the ability to analyse all of that information and immediately push it to a customer’s App or other channels for customer interaction.

There are many other examples of this hyper-personalisation in terms of e-wallets and budget apps that also provide that heightened level of customer satisfaction and personalisation.

So, just how far can hyper-personalisation go?  There may come a day when AI will be considered a ‘virtual crystal ball’.  As the data universe continually expands perhaps AI tools will be able to precisely predict and suggest which service or product a customer wants next — even before the customer realises it!