FinTech is transforming finance as we know it and businesses are struggling to find new ways to reach customers. How will it affect you?
There is a lot of buzz about FinTech and new exciting startups are emerging everywhere. But how is financial technology affecting traditional business models and how fast will it happen? Sanjiv Das is Professor of Finance at Santa Clara University’s Leavey School of Business. He visited the Swedish House of Finance FinTech conference to talk about the future of FinTech and how it will transform the financial landscape.
– There are about 1,400 FinTech companies operating in the US right now with about 33 BN USD in funding. As a comparison, losses from credit card financial fraud were 31 BN USD so in general, FinTech startups are lean organizations not requiring huge investments, said Sanjiv Das.
Data changes the game
Financial intermediation is a segment of finance that has grown since the emergence of the financial industry in the 19th century. It is a labour intensive industry that adds a lot of costs to the end consumer and this is an area where we are already seeing a lot of disruption. Efficient FinTech startups being able to deliver value to consumers without the high costs for financial intermediation have an edge. Data driven technologies are able to reduce some of the costs associated with traditional finance while at the same time delivering services as good as, or better, than traditional finance solutions.
In fact, banks could potentially tap into this market as they are already sitting on a lot of data they aren’t using. Some example of benefits for large traditional banks of using the data they already have is that they can understand the more profitable customers or products, enhance customer retention, detect market manipulation, target new clients and automate the financial analyst-role. The problem is not obtaining the data in many cases, but being able to use it efficiently. That requires an open mindset and courage to do something completely new.
10 areas of FinTech for the future
Sanjiv Das outlined the major areas where FinTech is being used already. Among these are; machine learning, AI, deep learning, personal and consumer finance, cybersecurity, payment and funding systems, automated and high-frequency trading, blockchain and cryptocurrencies, and text analytics.
AI is an area that has received a lot of attention. AI has in fact been around for quite some time but the technology has improved and is currently delivering on a new level.
– In the old days we had rule based AI. It replicated what a human would do. Now we have data driven AI. You have masses of data and you train an algorithm to do something smart with that data. The algorithm learns by itself. Data driven AI is much more powerful because it is not bound by human logic. You can teach the algorithm to do better than what a human could do because the algorithm can, in a very short time, learn what would take many years of experience for a human to learn. Companies are now starting to implement this, said Sanjiv Das.
Jobs on the line
Jobs that generate data will be on the line, since the algorithm easily can take over these types of tasks.
– Trading jobs are one example of jobs that are going to disappear. Traders have emotions, they are not predictable and they make mistakes. Machines don’t have those problems. The big financial companies are now replacing traders with algorithms on a large scale, said Sanjiv Das.
While some job categories have a tough time in the finance industry, engineers on the other hand are in high demand.
– Eventually I think many finance companies will become technological companies as more and more of their operations are digitalized and engineers take the front seat. And the transformation will be fast.
But as companies are integrating new FinTech-solutions into their businesses, there are pitfalls to avoid. Sanjiv Das showed that too much data can make it difficult to find the right information. And data cleansing is another important action before using data as a basis for business. Knowing how to handle the data will be crucial for survival in the coming years.
Sanjiv Das is the William and Janice Terry Professor of Finance at Santa Clara University’s Leavey School of Business. He previously held faculty appointments as Associate Professor at Harvard Business School and UC Berkeley. He holds post-graduate degrees in Finance (M.Phil and Ph.D. from New York University), Computer Science (M.S. from UC Berkeley), an MBA from the Indian Institute of Management, Ahmedabad, B.Com in Accounting and Economics (University of Bombay, Sydenham College), and is also a qualified Cost and Works Accountant. He is a senior editor ofThe Journal of Investment Management, co-editor of The Journal of Derivatives, and Associate Editor of other academic journals. Prior to being an academic, he worked in the derivatives business in the Asia-Pacific region as a Vice-President at Citibank. His current research interests include: the modeling of default risk, machine learning, social networks, derivatives pricing models, portfolio theory, and venture capital. He has published over eighty articles in academic journals, and has won numerous awards for research and teaching. His recent book “Derivatives: Principles and Practice” was published in May 2010. He currently also serves as a Senior Fellow at the FDIC Center for Financial Research.