Data is not oil, a rare fossil fuel that is finite; data is ever present, ever growing and powering everything we do in this world. It is the air that we breathe, and the more that air is cleansed, the better we breathe.
Another perspective is that you cannot be intelligent if you have dumb data.
These two streams of thought led me to the conclusion that data is the AIr that we breathe. Data is the raw material; AI is the processing; UX is the outcome.
Banks have huge amounts of the raw material to produce the desire outcomes, and believe that AI will save them. It can and it will, but only if the raw materials are delivered in the right state for processing. Too often, banks have raw materials spread over many silos and so the raw material is dirty and, if it’s dirty, it’s dumb. You cannot have intelligence if the data is dumb.
So, what to do?
Build an enterprise warehouse store of data? Send all data through some middleware for cleansing and consolidation? Use a third-party platform to sort it all out?
I guess you could do any or all of these things, but let’s get back to basics first: what data needs to cleansed, consolidated and integrated and why? Do you consolidate all retail customer data across lines of business for a single view that shows all of the customer exposure to the bank across deposits, savings, investments, loans and credit? Should you add into the mix any data from small business or other services where that customer’s name exists? What about their dealnigs with other financial providers or parts of the business that are not retail-related, sjuch as investment banking services? How far do you take this?
It is tempting to say that you need to take it as far as it will go but, pragmatically speaking, the focus has to be on the UX outcome. What is it that the customer wants?
Now, don’t ask the customer this quetson as they most likely don’t know.
Some people say, “Give the customers what they want”. But that's not my approach. Our job is to figure out what they're going to want before they do. Steve Jobs, co-founder, Apple
So, in looking at data and AI, can we intelligently bring together a profile of each and every customer to deliver a single view across their dealings with the bank. Of course, this is simple. Just look up the name and address on every database, see where there is a match, filter this into a data store, homogenize it and cleanse it, deliver the output to the AI engine and ask the AI engine to predict what the customer needs. Then deliver all of that insight into a nice app that tells the customer today, you need to cover a $3,000 mortgage payment and may be underfunded … would you like me to move $3,000 from savings to your deposit account? Swipe left for yes and right for no.
The bottom-line is that banks currently own most of the raw materials to enable intelligent finance through AI engines. The issue is that most banks have left their raw material underground, unextracted, unknown and unloved. Can we fix this? Yes we can.
Chris M Skinner
Chris Skinner is best known as an independent commentator on the financial markets through his blog, TheFinanser.com, as author of the bestselling book Digital Bank, and Chair of the European networking forum the Financial Services Club. He has been voted one of the most influential people in banking by The Financial Brand (as well as one of the best blogs), a FinTech Titan (Next Bank), one of the Fintech Leaders you need to follow (City AM, Deluxe and Jax Finance), as well as one of the Top 40 most influential people in financial technology by the Wall Street Journal's Financial News. To learn more click here...