‘Digital disruption is creating data at an unprecedented rate.’ True.
‘Companies who use data effectively to chart their business moves and deliver superior customer experience will succeed.’ Sounds logical.
‘Financial services institutions should use Big Data to deliver the experience their customers desire.’ Now, wait a min!
It is not lost on Financial Services (FinServ) institutions that data will rule in the years to come. They have seen several Fintech entrants using data more effectively – mostly external data – to deliver superior customer experience (faster, convenient, customized) and gain market share. So, to compete, many incumbents are looking to Big Data to deliver the silver bullet for their customer experience gaps. While Big Data could help in certain circumstances, it will not be the panacea they seek. Here’s a better approach.
Start with the end in mind; and look within before venturing out
In an earlier post, I stressed the importance of Customer Experience strategists for FinServ incumbents. The ‘end’ here is the customer experience you wish to create and/or the customer experience gaps you wish to close. Defining the problem better – with immediate term and longer term goals – will help focus the organization’s effort on making steady progress with small steps.
Done this way, FinServ incumbents will realize quickly that the data they need to to fix some of the immediate Customer Experience gaps is already available inhouse.
Pascal Bouvier (Venture Partner, Santandar InnoVentures)’s recent post highlighted that FinServ institutions fail to link multiple accounts held by the same customer and cause customer frustration. Such a gap in today’s day and age should be considered a travesty. Historically FinServ institutions have been structured around products rather than customers.
Now that they have loads of customer and transaction data, getting a 360-degree view of their customer based on this internal data would be worthwhile effort. After all, in the customers’ minds, they were providing data to a single place, not several siloed departments.
I can’t speak for others, but a FinServ institution who ignores relevant information I have already provided and goes chasing my social media account for more information loses my trust and business. Instantaneously.
Some FinServ sectors may seem more ‘privileged’ than others when it comes to data access but there are ways to level the playing ground
This week, my credit card (CC) company sent me offers from merchants (several local) who provided services/products similar to my recent purchases. No surprises here. My CC company has details on each of my CC transactions and where I live. Was the CC company tracking my online footprint to send me these offers? Probably not; a simple propensity modeling exercise would have suggested appropriate offers for me.
Some FinServ sectors have access to more customer data than others. CC companies and banks who issue CCs/ debit cards are at one end of the spectrum; they have detailed accounts of the customer’s spending habits. Life Insurance companies and mortgage companies are at the other end; and have information collected for underwriting and premium payments. Though limited in volume, they will have other information related the ‘asset’ they are insuring. Somewhere in between lie the traditional financial advisors who refresh their client’s asset, liability, risk profile, income, expenditure, and financial goals data normally once a year.
When consumers are increasingly expecting businesses to provide timely/proactive, contextual, personalized cost-effective products and services, payment companies with access to more data seemed to be better positioned than others. But this data gap can be closed, based on the type of data needed to deliver the aspired client experience.
Data aggregators can close this gap, especially for Personal Financial Management (PFM) tools and Financial Advisors. And for Insurance players, other sources of data – like those being collected from wearables (for Life and health insurance) or IoT/telematics (P&C insurance) – will help the personalized customer experience.
Tug of war on the ownership of this data will play out in the months to come between the aggregators, creators and customers – as we are witnessing between banks and data aggregators. Either way, as the industry landscape shifts, data aggregators will continue to have a prominent role to play.
But before FinServ incumbents get ready to jump on the Big data or IoT bandwagon for data advantage, there’s this one thing.
Data <> Insights and Insights <> Action
All the data in the world at your finger tips will not help unless it cannot be translated into insights or intelligence that can influence your business moves. And this translation from data to actionable business intelligence involves moving the dial on several dimensions of the organization’s analytics maturity including organization culture, talent, infrastructure, insight distribution, etc. (a topic for another post).
So, before pursuing more external data – be it through Big Data, IoT, Aggregators or any other source – FinServ institutions should candidly assess if they are ready to effectively use the data avalanche that will follow to improve the customer experience.
It will suffice to say that if the FinServ institution has a strong intent to pervasively use data-driven insights to improve its customer experience, there is plenty of external help (consultants, niche analytics players) to support that endeavor.
There is no doubt that data is key in this digital age. Ready or not, data from all quarters will come flooding in. FinServ institutions should not be focused on more data, but rather on identifying the right kind of data needed to solve their particular issue, acquiring it and using it effectively to meet customer expectations.
Last month, I called my bank to inquire about the fees I was charged for overseas money transfer. I was transferred between departments. For now, I would have been delighted if the second person had some context from his/her predecessor and I did not have to repeat my request every single time. I can say with high level of certainty that Big Data was not the solution in this case.
[Author is the CEO and Founder of S2E Consulting, LLC]