Top 5 Questions that budding Fintech entrepreneur should ask before embarking on the venture
In the broad sense, the old financial industry needs change and technology is definitely the answer to that. “Fintech” — a popular word that frequently appears in the newspaper. For those who are still working in the banking sector, it is never a surprise to hear some of your peers left the banking sector to start a fintech company.
This sector, not just attract the banking professionals, you might also hear a lot of talented fresh graudates run a fintech startup. Given so much interests in market, should you just jump on the bangwagon?
This post, we interview Steve Totman, Big Data Evangelist and Financial Services Industry Lead, Cloudera. He will share some tips on the financial sector and how technology could aid financial insituitions.
- How did you land yourself a “Fintech” job in Cloudera?
I came from a financial services and deep data management background. I was really interested in how disruptive Hadoop was in every industry and was also a huge fan of Doug Cutting (Co-founder of Hadoop and Cloudera’s Chief Architect), Mike Olsen (Co-founder and Chief Strategy Officer of Cloudera), Amr Awadallah (Co-founder and Chief Technology Officer of Cloudera), Tom Reilly (Chief Executive Officer of Cloudera), and most importantly, the Clouderian culture. It was a combination of background and interest, combined with persistence and a little luck — I was sure that the Open Source Apache Hadoop project was going to change the data world and I wanted to be a part of it.
- Do you have to be a banker to develop solutions for banks?
No, you don’t. At Cloudera, we believe that data can make what is impossible today, possible tomorrow, across all industries, and what seems like magic can happen when you bring in data scientists and engineers who can use Open Source based Big Data Technology like Hadoop.
Do you need to understand the business use case and requirements to create a solution? Absolutely, but the key is to combine people, process, and technology. For example, three years ago, one of our data scientists was asked by a large bank to try and write a VAR function (Value at Risk) using Spark running on a Cloudera cluster. As a Mathematics major, he didn’t know much about VAR in financial services but the bank’s subject-matter experts explained the concepts and he made a first attempt. After he was done, his attempt actually made it run ten times faster than their existing code and it was running on 100% of their data rather than the subset they had been forced to use, so they were jumping for joy.
- What is your definition of “A-team”? And where do you find them?
An ‘A-team’ today translates to a data-first culture. Organizations often think they can find and hire such a team, but the truth is, you have to build the culture internally first, starting from the top. Business leaders and executives must see data as an asset and empower their employees.
One of my favorite quotes is from James Governor at Redmonk — Data Ages Like Wine, Apps Age Like Fish — data is your greatest asset but just like fine wine, it must be cared for, stored, and shared to be truly appreciated. Businesses must develop a team with the right set of skills and evolve business processes and decisions to be data-driven.
Most people have the idea that data scientists are a mythical unicorn, but the best data scientists are not just a single person, they are a tightly integrated team of people who know and understand data science concepts, the data, and the business problem. The most important skill that you can’t train up for is curiosity.
- How do you pitch to a bank’s CTO?
The first thing I do is to start a conversation and align on the objectives that make the most sense for the overall business and their customers — understanding what drives their business goals and objectives is key. Within the financial services sector, the common themes are Customer Journey, Financial Crime, Risk, and Product and Service Efficiency. Another topic that CTOs often discuss is digital disruption. Business leaders have realized that customers no longer want to walk into a bank or go on their website to get more information; they want a multi-channel experience. But the problem is, how do banks monitor that experience and understand the customer journey of how people move through different channels and systems?
In today’s consumer-centric world, most financial institutions are now shifting their focus to provide the ultimate customer experience, all with data-driven insights. This is where the technology comes in. One of our customers in the banking sector mentioned that he would like to take customer experience back to the 70’s. In the 70’s, you walk into a local bank they know you, your family, your business, and why you need a loan — today, if you are operating with thousands or even millions of customers, how do you create the same experience? The answer is data.
Many CIOs and CTOs that I meet also seem to be facing one problem — the high costs of managing a data warehouse or data archival. Because of the costs, businesses have had to make compromises about what data is stored and analyzed. Hadoop enables organizations to save tremendously on costs, while providing the flexibility to access data at any point in time.
CTOs from different industries have different problems, but the key is to understand what they really need and set realistic goals accordingly.
- Do you see regulators as an obstacle in the industry?
Quite the opposite. In many countries, especially in APAC, regulators are working directly with the companies to jointly come up with a solution and are even using Cloudera’s platform themselves. Our solutions help them to aggregate data from all the companies they monitor and provide a systemic view across organizations. We are even starting to see the regulators themselves contribute to Open Source projects and running datathons or hackathons. There are definitely some exceptions but the general feeling is that regulators today are thinking about the right issues especially around data privacy
Originally published at The Neo Dimension.