Unbundling Smart Banks With Location Intelligence on Big Data and Blockchain
AI and blockchain are galvanizing banks into action. Banks incorporating assets like location intelligence to build intelligent and intuitive products and services will win.
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"Wells Fargo CEO Tim Sloan is seeking to improve earnings even under the Fed cap. To do that, he’ll have to choose his spots carefully, focusing on the businesses where Wells Fargo can squeeze the most profits. He thinks he can most easily improve on the consumer side — precisely where bank’s reputation has suffered." — Laura Keller and Shahien Nasiripour, Bloomberg Businessweek (March 5, 2018)
Improving on consumer side need not be a practice reserved for tier 1 banks. Institutions such as tier 2 banks and credit unions have now begun to realize enhanced profits by improving customer experience with adoption of AI. As a social proof, one can just walk into a PNC branch and notice the gradual dispersal of manned teller stations in favor of in-office portable ATMs catering to a personalized banking experience. I say that’s a "good win" when you listen to the customer.
As consumer landscapes continue to evolve and analytics awareness for AI becomes mainstream, I believe that staying ahead of competition will remain contingent on the bank’s capability to embrace a portfolio approach towards AI rather than one "good win." Banks that will succeed are the ones that remain open to "unbundling" with a focus on learning and readiness for change.
Through my experience and advancements with client engagements, I can unfold three ways for banks to follow an enterprise-wide unbundling framework and to make sure they are not running just a siloed data science project.
Follow Customer Experience Down, Not Technology Up
While banks are gripping to information more openly, areas sensing incomplete or unrealized datasets continue to persist and need attention from banks working their way customer experience down. Let’s talk about one such gap: location intelligence (LI). With the advent of efficient and accurate geocoding, banks now have the opportunity to know their customers better based on LI and to delight them with products and services resulting in improved net promoter scores.
The figure below shows the various subunits where a bank can monetize benefits by appending unexplored datasets with LI. Some of them are as follows.
- Automating appraisals with LI and property-rich information allows banks to deliver a cost discounted and hassle-free closing experience to customers.
- Applying location analytics by appending economic vitality, crime index, and demographics data enables banks to make customer-centric decisions on branch optimizations and commercial real estate portfolios.
- Using LI helps banks track customers and gain their share of wallet with instant cashback on transactions at points of interest in the vicinity of their identified location.
Fail Fast and Fail Forward With Big Data and Blockchain
Unbundling decades of business built over traditional technologies calls for a technology up approach, which can be an expensive undertaking. Nimble frameworks like big data and blockchain help fail quickly and economically, allowing room for 90-day sprints and faster growth.
For instance, building a customer-centric LI architecture on big data takes no more than half a day and involves installing and analyzing over 100 million new data points to deliver meaningful results for bank VPs to take action.
Another way of delivering award-winning customer experience is through blockchain applications. Travelling customers’ banking experience can easily transform into a tedious process due to unlinked branches across the globe and differences in currencies. Blockchain can make the experience of banking transactions seamless, eliminating the stress from high transaction fees, lack of transparency, and vulnerability to manipulation of figures.
Moreover, interaction with blockchain applications lessens risk due to real-time settlements, leaving a high level of expectation from customers on convenient experience. Critics argue that blockchain does not deliver performance, but then again, did a customer ever care about the performance of their bank’s blockchain architecture in favor of transparency, security, and lower fees?
Consumable Datasets: Better AI With LI
In the world of LI, an important byproduct of geocoding is what’s known as a unique identifier (UID). UIDs not only help append customer location with unexplored datasets, discussed earlier, but also remain persistent as those unplumbed datasets grow in category. In other words, banks will no longer need to undertake cost-prohibitive measures to simplify their data consumption models to achieve desired outcomes.
The figure below reveals a vision of how big data technology can be leveraged to simply join the desired datasets with UID and power the AI engine to make accurate and timely recommendations.
"We see our customers as invited guests to a party, and we are the hosts." — Jeff Bezos
There is little doubt that AI and blockchain are galvanizing banks into action. However, a bank’s CIO can perceive that they are moving twice as fast and yet feel the need for improvement at boardroom meetings. Banks with a DNA for organizational unbundling will be best positioned to win by incorporating customer-centric information assets such as location intelligence to build intelligent and intuitive products and services.
If you have questions, comments or would like to learn more about location intelligence on big data, please feel free to reach out to me or connect with me on LinkedIn.
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