GeFi is a term that refers to “generative finance“. This technology has an ace up its sleeve: it is capable of deciphering mountains of data and discovering patterns and trends that might go unnoticed by us mortals. Now, instead of relying solely on our judgment, generative finance helps us make more informed decisions and make more accurate predictions.
What do you think?
Óscar Barba
Co-founder & CTO of Coinscrap Finance
The practical applications of generative finance
In addition to understanding and managing the risks associated with different investment strategies, GeFi optimizes your portfolio and makes predictions. It is also capable of promoting financial inclusion and increasing the population’s knowledge of economic issues. It can even help you optimize your trading strategies! But the most striking thing is their ability to design customized financial products, as if they were reading our minds.
Let’s see how it does all that: Generative finance uses artificial intelligence and machine learning algorithms that get wiser the more training they receive. With the arrival of Big Data, the daily training of these algorithms in the financial sector reaches unimaginable levels. Millions of transactions are a matter of seconds for them. That is why the precision is so high.
Bankarizing as many citizens as possible
Of course, like any magic trick, GeFi also plays with illusion. An illusion understood as the second meaning of the RAE:
“Hope whose fulfillment seems especially attractive.”
Entities are fulfilling the dream of understanding the complex data generated by their customers thanks to generative finance. Not only that, once organized and “translated” they help both the bank/insurer and the users to achieve their goals.
In countries where many people see their loan application systematically rejected, generative finance can be of great help. Due to access to different sources of information, such as Social Security records for example, this part of the population can access financing adapted to their needs and their capacity to pay it back.
Financial education in the era of digitalization
Leonardo Becchetti, professor of Economics at Tor Vergata University in Rome, conducted a study on the impact and obstacles to financial education. He established as barriers the negative reputation of finance and the lack of interest of most of the participants. Stimulating curiosity, giving learning a concrete meaning and scope, would be a possible solution.
Providing relevant data about your financial situation, as well as advice and alerts at moments of special importance (insurance expiration, end of subscriptions, investment proposals in the event of an extraordinary income) can awaken interest in economic issues. The experience of generative finance is a shock for all of us who work in the sector.
Challenges when connecting with banking and insurance customers
Some people are concerned about data privacy or simply having to talk to a bot instead of a person when they want to communicate with their entity. Banks and insurers know that data security is vital and use all means at their disposal to protect it. Above all, it is important that they have strategic allies who help them stay up to date on developments in this field.
The rise of generative AI applications is leading to exciting innovations that benefit consumers. This is the case of large language models, which allow a new era of personalization, turning each customer’s digital interactions into a unique “digital footprint”. What do we get with this? That the distance that separates a financial institution from its user is reduced.
Get closer to the final customer, easier than ever
Artificial Intelligence loves to chat and its integration with search engines is affecting the way they search for your financial institution. The same goes for your products and services. Everything is much more interactive and you have to look for new ways to position yourself as a leader in innovation so as not to lose relevance.
The new generations know more about your company than you do!
More importantly, both the depth and value of the relationship increase based on the number of digital interactions you have with your customer. Their commitment will depend on the value these experiences have for him/her. Therefore, you need to optimize every touchpoint in their journey to close the gap between their expectations and your product or service.
The positive impacts that this technology has demonstrated in different areas leaves no room for doubt: with the advancement of artificial intelligence, these magical techniques can become extra sophisticated and precise. As we have access to additional data from different sources, GeFi could become even more accurate.
About the Autor
Óscar Barba is co-founder and CTO of Coinscrap Finance. He is an expert Scrum Manager with more than 6 years of experience in the collection and semantic analysis of data in the financial sector, classification of bank transactions, deep learning applied to stock market sentiment analysis systems and the measurement of the carbon footprint associated with transactional data.
With extensive experience in the banking and insurance sector, Óscar is finishing his PhD in Information Technology right now. He is an Engineer and Master in Computer Engineering from the University of Vigo and Master in Electronic Commerce from the University of Salamanca. In addition, Scrum Manager and Project Management Certificate from the CNTG, SOA Architecture and Web Services Certificate from the University of Salamanca. He recently obtained the ITIL Fundamentals certification, a recognition of good practices in IT service management.
