In a world that’s perpetually evolving, the marriage between modern technology and real-world finance has become more than just a partnership – It’s a revolution. Gone are the days of manual, time-consuming banking operations. Modern technology, through the implementation of artificial intelligence (AI) and machine learning (ML), has ushered in a new era of automation in finance. Routine tasks such as transaction processing, customer service, and fraud detection are now streamlined, allowing them to allocate resources more efficiently and provide faster, more accurate services.
To talk more about the recent advancements in this field we have David Sánchez Molina, professor at EADA and CEO of the WealthTech company Baboon Technologies.
Please tell us more about the latest developments in fast-moving technology and how you see its growing significance in finance-related applications.
We are fortunate to live in a time when finance as a sector is getting disrupted that far. Most of us in the 2000s were not expecting this industry to shift into FinTech that fast. After 2008, faith in the traditional banking industry was severely damaged. 2008 is the year of so many FinTech innovations such as neobanks or bitcoin. Nowadays, paying with contactless technology with your smartphone using NFC is something we do regularly, and this technology just appeared in 2016!
In the context of financial inclusivity, how is technology being leveraged to provide banking services to underserved populations, and what role do cryptocurrencies (DeFi) and blockchain play?
Good question. Related to the “underbanks”, FinTech has meant the great opportunity of having an affordable alternative to traditional banks. In the world, there are almost 2 billion people who have no regular access to banking services. FinTechs have made it possible for anybody with a smartphone to be able to access basic banking services and start planning. The great scalability of digitalized FinTech projects makes it possible to offer services to as many people as possible. One of the great examples of this is the case of M-Pesa in Kenya and their bet on SMS mobile banking in 2006.
Regarding decentralized finance in a financial context, there is an important growing interest. We need to understand that decentralized finance promoted by a FinTech project could provide three main purposes: Cybersecurity, Digital Autonomous Organizations (DAOs), and Legal Tech. Regarding cybersecurity, blockchain adds an exceptional security barrier that could consolidate financial businesses as data businesses, being able to store their client’s financial data as safely as possible. As per the DAOs, another interesting application of blockchain is the rise of smart contracts, using DeFi blockchains such as Ethereum to automate most of the decisions inside an organization, such as salaries or any contractual obligation. Finally, related to LegalTech, blockchain has tremendous power in offering an alternative to notaries and registries, certifying that an asset such as a house has been transferred from one person to another and being certified by all the blockchain members.
What collaborative efforts or challenges are arising in the pursuit of offering innovative financial services to a tech-savvy consumer base? How are traditional banks adapting to the emergence of fintech startups?
Big Techs such as Apple or Google are very good at understanding consumer habits and making perfect user experiences. We must understand that banking has never been about user experience, innovation, or disruptions. Banking is a regulated industry where the main value proposition was not being the innovator but being safe, trustable, and secure. However, because clients are getting used to the way Big Techs present user experience, FinTech apps must emulate the principles of Big Techs. Regarding traditional financial businesses and FinTech startups, you can not ignore them. I remember the famous quote of Jaimie Dimon, the CEO of JPMorgan in 2014 saying “Silicon Valley is coming for us”. The current approaches are to compete against neobanks and new FinTechs or cooperate in what is called “coopetition”.
With the increasing popularity of robo-advisors and algorithmic trading, how do financial professionals view the balance between automation and human expertise in managing investment portfolios, and what implications does this have for the broader financial industry?
The appearance of robo-advisors is great news for the industry as a whole (including financial advisors). Let me give you an example. If as a financial advisor, I charge a 0.5% annual management fee on the assets under management of the client, it is only affordable for me to accept clients that have more than 50.000€ in savings (at least). Therefore, similarly to the underbanked that we previously discussed, there is a great majority of people who have no access to a private financial advisor. The algorithms that inspire robo-advisors are based on general investing principles such as diversification, periodic portfolio rebalancing, and the purchase of passive investment products such as ETFs linked to the main global index and bonds. Therefore, robo-advisors can offer immense value for small investors with no financial foundation. However, once this investor reaches sufficient wealth I highly doubt that their financial needs will be satisfied by a generic algorithm like a robo-advisor. Imagine a family office of €10M, for instance, with a basket of real estate investments, stocks, venture capital, and a family business. This complexity and particularism cannot be handled by a generic algorithm because some decisions are not black or white and it is the informed client who has to make decisions of uncertain investments.
What are your suggestions to students who want to learn more about this industry and what skillsets they should develop?
I strongly recommend starting to learn Python and mastering Excel. Python will give FinTech candidates the logical and algorithmic tools that will structure their financial minds into the cold world of programming. Furthermore, automating your financial decisions using Python will force you to transform your intuition into a methodological process built over lines of code, which will help you make a robust decision-making process avoiding subjective human biases. On the other hand, I believe that 99% of the population do not realize the great potential of MS Excel and just know the pure basic. Mastering Excel and similar software can have tremendous power in data analysis and productivity.
Concerning the methodological and algorithmic approach to investing, how would you describe your future investment fund, Systematic Value Investing?
Systematic Value Investing is the future fund, we’re currently opening with AndBank Spain and MyInvestor. This fund seeks to empower investors looking for passive investing such as buying the indexes of the United States market by offering an alternative, combining the best active management and passive management: better returns than the average market combined with algorithmic and transparent decision-making using algorithms. The philosophy of the fund is to maximize the quality at a good price and automatically create a basket of 40 companies that can outperform the average market returns of the other 3.000 companies publicly traded in the American market. I believe that Systematic Value Investing will change the way ETF investors think about investments: Why do I bother buying the SP500 ETF if I can buy the SVI-SP500 ETF that systematically removes the worst companies of the index: the expensive ones and the less competitive ones?
Indeed! In a world of financial possibilities, Systematic Value Investing stands as a testament to the ongoing revolution, challenging investors to rethink their approach and embrace innovation.
In closing, this conversation with Prof. David Sánchez Molina underscores the indelible imprint of technology on the finance landscape. As we reflect on the rapid evolution of the financial sector, one cannot escape the realization that we are witnessing nothing short of a revolution, a paradigm shift from traditional banking to the dynamic realm of FinTech. This aptly highlights that the personalized and nuanced decisions required for substantial decision-making demand the touch of human expertise, and the balance between automation and human insight becomes the linchpin for the financial industry.
Author
Saminul Minhaj
Student of International Master in Finance 2023-24
About Saminul
Before joining the program, Saminul Minhaj did work as an associate for Carelon Global Solutions in Bangalore, India. He holds a Bachelor’s degree in Business Administration and finds challenging Business-related problems exciting.