How three global technology trends are shaping Fintech

How three global technology trends are shaping Fintech  - CIO&Leader

In the past, investing or managing money was left to professionals since the tools and know-how was limited.


Over time, there has been a lot of movement across various spaces but our interactions with money have been pretty much the same for a really long time.


The advent of Fintech is changing that rapidly. Today, what makes Fintech especially exciting is the fact that the finance industry has not changed significantly in the last few decades.


What interested me the most about the space was the move towards the democratization of the trend. Today, a lot of exciting movements that have commenced in the Fintech space are being promoted by banks. I think there are tremendous opportunities for synergy between startups and established banks. For one, banks can create a healthy merger and acquisition market in the fintech space; as consolidation occurs and winners in segments emerge, banks may be able to encourage innovation by providing exits and liquidity to entrepreneurs.



Another area where banks excel is the financial infrastructure that they have already put in place. Banks may be able to offer a plug-and-play API into this backend to innovators who want to build on top of this. Some companies are already doing this! This would allow banks to remain an integral part of every innovation while being able to grab a slice of every innovative new technology that entrepreneurs come up with. In the long run, it is difficult for large companies to keep moving quickly while it is difficult in the space of finance for small companies to have the compliance, assets and infrastructure figured out. These comparative advantages offer a lot of opportunity for mutual benefit.


However, technology and innovation will need to work hand in hand. It is a well-known fact that the three global trends namely, artificial intelligence (AI), blockchain, and big data are shaping the Fintech market.


AI is special, since in the past, human intelligence to solve problems of money allocation or intelligent investing was limited and the best people were those with industry experience or an uncommon insight. Today with AI, it is possible to have machines that exceed human intelligence and ones that can draw on far greater data than any single human or company could store. AI, therefore, has the promise of giving us better tools and abilities than sizable teams of humans.


Imagine being able to draw personalized recommendations based on the entire human history of investing; this is something that would not be possible without AI. Similarly, if we want to derive more accurate models of risk and prevent fraud and financial crime, AI is an extremely powerful asset in being able to see attack vectors as they emerge.


However, the concern is around developing trust for the outputs of AI algorithms. If you observe the AI landscape, there have been a lot of deep learning and AI models built on top of neural nets have had results that can’t entirely be explained. I think over time, trust will emerge just as it does for a variety of other products and entities that we interact with. Conventionally, trust is a very human-to-human idea. However today, we routinely trust brands, products, companies and even institutions. It is not uncommon to say that you “trust” coke. My guess is that trust in AI will also emerge as a product of results and not any inherent reasons why it should be trusted. Similar to most processes in a market system, competing AI technologies will offer people differing results and trust will accumulate with entities that give the best results. Eventually, we may need institutions that regulate AI.


Blockchain, on the other hand, offers a radical new way of extracting this trust in a completely decentralized manner. Consider this: Money and transactions have value because there is trust that is conferred upon it by some central authority. In the case of money, it is governments and in the case of transactions, it is banks. A user only accepts what one pays him/her because of the trust in these institutions.


Financial institutions today are adopting technologies such as Ripple and Lumens because it is the only way to remain relevant in a rapidly evolving industry. The day is not far when no intermediary will be needed for any transactions at all: A kind of like cash without the physical barriers of cash.


The third big trend is big data that has been shaping various industries. Fintech companies and financial institutions generate so much data on a daily basis that it is often times beyond the scale of regular data technologies to deal with. This petabyte scale data has caused the emergence of an entire industry around it: Big data technologies and analysis techniques.


In fact, the AI revolution has only been possible because of the amount of data companies are able to harness today. Increasingly, data is being used to personalize, provide security to, and make more intelligent everyone’s financial lives.


India has seen some incredible developments in the space of fintech. Companies such as Paytm have become ubiquitous and it is exciting to see all that is happening in the payments space. A couple of companies that excite me are FinAskUs and Finomena. One is trying to revolutionize personal investing and finance while the other is trying to revolutionize access to credit.


However, I see regulation and cross-border financial controls as the biggest challenges to fintech. For example, it is entirely possible that countries may crackdown or try to prevent the rise of crypto currencies. Similarly, there are very few if any truly international fintech companies due to the capital controls and challenges of moving money around. If Fintech is to become a truly global phenomenon, it would need larger collaboration between countries to develop a framework of innovation in the realm of finance and access to finance. 


The author is a technologist, investor and data scientist based in the Bay Area. He grew up in India and did his bachelors and masters from Stanford university focusing on Systems and Data.He currently heads data engineering at Robinhood, one of the most successful Fintech companies in the Bay Area and has been responsible for developing a lot of their core infrastructure and data science.He also advises and invests in startups. In India, he runs an investment firm called Virtu Propdeal Pvt Ltd.


(As told to Shubhra Rishi)


Add new comment