May 21, 2017
This week, I’m inspired by Ben Thompson and James Allworth’s podcast, Exponent. A pitfall of our technology-obsessed business culture is that we forget technology itself is never enough. Technology must be applied in the right situation, in a sustainable business model, and with reasonable checks and balances. Financial services have learned a few things over the decades. We shouldn’t throw out every customer insight and business process we’ve developed. The trick is, what should we keep and what is obsolete?
"Can would-be attackers try as often as they like until they get it right?
Let’s get this out of the way up front: this story shouldn’t shake your trust of new authentication technology. Keep implementing or looking for better security measures and learn from HSBC. Why? HSBC’s controls and process share some blame. The reporter had seven failed attempts before breaking the system. Another researcher had 20 failed attempts! It seems HSBC put too much faith in the tech – an easy thing mistake these days. Their faith was so great they didn’t think common sense controls were even necessary. New technology feels and seems magical (like voice mimicking AI) – particularly for non-engineers. That said, business owners are critical to making technology an enabler of new customer experiences.
We quickly realized that demand-side policy problems could not be solved by supply-side solutions.
It’s inspiring to talk with someone who is on a mission to change the world. The BanQu team is committed to doing just that with leveraging blockchain (which has its own world-changing reputation.) BanQu’s solution has three major components to fulfill their mission: 1) customers with a big problem to solve 2) truly disruptive technology 3) a revenue-generating business model. Take those ingredients, sprinkle in a passionate founding team, and suddenly changing the world seems (a little) easier. What’s most exciting is that we’re just at the beginning of FinTech’s impact. We’re just at the start of companies experimenting with new technology and business models to solve the world’s biggest problems.
Where, when, and how machine learning will be integrated into the business also has strong implications for how the business will be managed.
There is no doubt machine learning has tremendous potential. Google continues to bet their future on it. Machine learning is required to make use of (and make sense of) the increasing amount of data we produce and track. So what’s the best application of machine learning in payments outside of authentication and fraud detection? McKinsey’s examination of the collection value chain highlights how machine learning application impacts the entire process. Machine learning’s focus may not be a new payment tech or chatbots but rather the supporting operations, business processes, and customer insight that augments today’s team. It’s easy to forget you need to address the world as it is, not as it should be.
We plan on sharing several articles each week. Tag LTP on social media if you think there is a ‘must-read’ from the week!
See you next week!