Earlier this month, I had the opportunity to attend Money20/20 Europe to witness an engaging panel with some of technologies leading innovators, including Marqeta Founder and CEO Jason Gardner. The topic, “Data Dinosaurs: How advances in analytics and machine learning can prevent extinction”, brought a group of panelists together to address challenges surrounding big data, machine learning and artificial intelligence (AI) and their implications on tech giants (i.e. GAFA) and Financial Institutions. I’ve found myself in similar conversations with peers, customers and industry leaders as sweeping changes in regulation on data (PSD2 and GDPR) continue to impact our industry. Big data and machine learning are now being used in virtually every industry as they have the ability to change how we interact and communicate. Analysts have defined AI as a computer system that can sense, comprehend, act and learn; while perceiving the world around it to analyze and understand the information it receives. As a side note, the first topic the panel discussed referenced GAFA and I sat in the audience, confused. It wasn’t until an anonymous audience question referenced Google, Apple, Facebook and Amazon did I make the correlation.
The panel (Dharmesh Mistry, Temenos, Chief Digital Officer; Daniel Kjellén, CEO & Co-Founder, Tink; Kathryn Petralia, President and Co-Founder, Kabbage Inc; Joaquín de Valenzuela, Head of Financial Services EMEA, Salesforce; Dave O’Flanagan, CEO & Co-Founder, Boxever; along with Jason) was unanimous in thinking that the “data quagmire at the bank level” is likely easier to solve than for most businesses. Where banks once lagged, or seemingly wanted to take a wait-and-see approach, they are now conscious of the opportunities data can afford them. However, uncertainty remains on how to package and make this data consumable. Many are embracing a tech first approach with tech partners, realizing that they alone can not solve this. Today, banks (both traditional and challengers) are undergoing cultural and technological shifts which make the banking industry ripe for adding value to the AI ecosystem. Panelist Joaquín de Valenzuela, Head of Financial Services EMEA at Salesforce, estimated that banks have a vast amount of data and that 70% of that data is customer focused. However, he also concluded that only 1% of it is used in some manner today. Marqeta’s Jason Gardner pointed out that tech-forward challenger banks have the most significant opportunity. “If you look at the top 50 brands for millennials (age 17–37), there isn’t a financial institution on that list”, commented Gardner. “Challenger banks are looking at new constituencies in which to market their services. Understanding those constituencies before creating interfaces and experiences to make them custom and appealing, is the way to engage and build loyalty.” When asked what data is the most important, Gardner believed “transactional data is the most important type of decision data out there”. The panel agreed that in addition to transactional data, social data is extremely powerful because of its ability to capture an array of interactions, behaviors, and preferences. Examples included Facebook friend lists and picture metadata (where they were taken, when they were taken, etc…). “Understanding where people live, work and play allows data to drive more valuable customer specific decisions and interactions to engage audiences”, commented Gardner.
Still, many businesses struggle with how to capture and understand the data they have and how to do so within the new, ever-changing, regulatory environments. To help guide these discussions, consider the following questions:
What does my business need to do to create a plan around consuming/using data?
The first step is to determine what you want from data. Start by asking a few fundamental questions:
1) Who are you curating the data for?
2) Who is the customer?
3) What do they care about most?
These may sound basic and over-simplified but they will help your business focus on what matters most to you and your customers.
How do we do it?
We are accustomed to thinking that all data is good data, but data can often be incomplete, old or inconsistent. As one panelist pointed out, AI will only add fuel to the fire if it’s not a core competency of your business. Trying to solve these issues without local expertise, while also understanding global impacts becomes an issue unto its own. Companies looking to make critical decisions on strategies involving the use of data must first address local regulatory rules and then larger global consequences. Finally, it is essential to ensure that you are building systems for scale that can flex with the ever-changing regulatory environments and the growing availability of data.
What does success look like?
I think the real question here is “what is your business trying to achieve with the data you have”? Ensuring that you are protecting your customers is success factor #1. What we’ve learned this year, from tech giants to financial institutions, is that customers are willing to share their data as part of the user interaction. Data can ensure unique and custom experiences so the upside of sharing their data outweighs the perceived risks. Success for a business is finding a way to protect and use data in a responsible manner that brings value and loyalty.
Should we buy or build?
Buy. If data is not your core competency, identify and leverage partners and resources to solve for the challenges and opportunities that data and regulation often provide.
Renata Caine is the Head of International at Marqeta and an active member in the payments industry since 2005. As a global payment and technology executive, Renata has spent the last 13 years working for a worldwide issuer helping businesses to implement payment solutions for regionalized regulatory environments. Renata’s expertise in virtual payments, international strategy and growth are leading the way for Marqeta’s international expansion.
Interested in Marqeta’s solutions for international? Contact Renata: