November 30, 2021
Santander Spain – Self-driven Finance: AI driven data to create engagement
INNOVATION PRESENTATION
Santander Spain uses deep & fresh data (historical records of the client transactions, and a snapshot of the products & balances) to create predictive patterns that may impact our customers in the near future. With the pattern detected, Santander Spain uses its digital channels to create an insight for the customer, so he/she can evaluate the possible situation, and to solve it before it really happens.
Thus, on the other hand, from Santander we have extended the use of prediction to not only anticipate customer events, but also provide them with the best tools with that prediction: predictive push notifications (that notify you of upcoming movements, for example, a periodic transfer that is going to be executed soon), a section of upcoming receipts within the Receipts and Taxes area of the digital channels, and especially, a tool called Financial timeline, available from the app and the web, where the client can take control of everything that will happen in the next few days in your accounts (your most relevant financial events in the past and the next to occur: the receipts and subscriptions that are going to charge you, the installments and settlements of loans, cards, insurance, periodic transfers…) so that the consultation of future events through this Financial timeline has become the top 3 of consultations in digital channels.
UNIQUENESS OF THE PROJECT
Back to basics: it is needed to raise confidence between the bank and its customers, and one of the ways to increase confidence is to give the customers pieces of real advice to the customers.
Our market research shows that:
– 89% an IA framework that creates personalized insights using the unique data from each customer.
– 1 in 5 Customers say they are willing to pay their banking provider to know them better.
– Customers are seeking meaningful insight and advice on demand. They want and need to be understood as individuals, and they expect served based on their unique needs.
For that reason, using an IA framework that creates personalized insights using the unique data from each customer. That insights need to match:
– Focus in the person, not on the product. And focusing in the person implies using the customer transactions, in order to detect his/her hidden patterns.
– After the analysis, the insights should enlighten the customer to realize his/her hidden patterns. Such as “your expenses in “dinner” are skyrocketing”, or “check this payment, it may be duplicated”, or “check your balance, because with the regular payment pace it may be turn negative” (in this case the bank giving real advice to the customer, so in the case the balance turn negative, it won’t be charged).
– And finally, Santander Spain is offering an honest advice, and in some cases, it may bring a solution to that possible situation. Such as “check your balance, because with the payment of your car insurance it may be negative”, may include a shortcut to transfers, o money from the cart to the account, or so…
The concept of Self Driving Finance is a mindset where Santander provides each customer insights that enlighten customers to full manage his/her finance.
Technology is a breaking point to get back to the retail banking industry origins: To create a real trust between our customers and the bank (engagement), and it would create an exit barrier.
THE REASON BEHIND
In our customer obsessed strategy, we want to provide the best possible customer experience to our users by leveraging data to add value to our customer’s personal finance.
The initiative is currently deployed to all digital customers in all digital channels (app & web) and the response of our customers is being great. In every insight we set a five-star scale to allow the customer to rate the quality of the insight: our average rate is 4,5 out of 5, so it is perceived as a utility that adds value to their personal finance. Also, there is a box in every insight to allow free text.
In this moment, the project is focusing in two goals:
– Integrate most of the insights into the push engine. Currently it is deployed for thee cases. This feature will allow to communicate the insights in real time to the customers, as the situation happens. This is a game changer in the way Santander Spain have a conversation with its clients.
– Integrate most of the insights in timeline. The timeline is a feature that show the events and transactions of the customers when happened in a timeframe, also shows the probable date in the future of a probable event (as a negative balance predicted by predictive cashflow). As all insights have a date of possible taking place, they can be shown in the past (ie, a duplicate charge un the supermarket two weeks ago).
Some verbatim from our customers:
– I thought my spending was lower!
– Very useful! …It’s like having an inbox for my personal finance.
– Very useful It would be great if the merchant name was the same as the commercial name. I feel this is a bank taking care of me.
CHALLENGES
RESULTS
This kind of AI generating automated insights will be deployed by most of the banks. It makes possible to give personal advice to the customers, also honest advice (not based upon products, but upon the client needs), and finally allows to use and monetize the customers data, but only in the perimeter of the bank, so not allowing data breach or selling data to third parties.
The conjunction of the use of such AI and prediction models together with the creation and exploitation of such useful tools as push notifications or the financial timeline gives rise to use cases that are truly useful for our users.
So, as an example: based upon your past transactions, our technology can create a pattern in a customer’s payments for his car insurance. That happens in May, so the month before the AI knowns that a new payment may happens, with a value of the mean of past payments. So, the technology creates a predictive cashflow analysis, and it may happen a negative overdraft in the client’s account. So it creates automatically an insight (using push notifications and a note in the timeline) to communicate with him.
Originally published: https://innovationinbanking.efma.com/self-driven-finance-ai-driven-data-create-engagement
