The fintech industry took a big leap during the pandemic. According to a report by Finnovista in partnership with Mercado Pago, published on the Bloomberg Línea website, by the end of the first half of 2021 Latin America already had more than 1,500 fintechs, including five new unicorns: Clip and Bitso in Mexico, dLocal in Uruguay, and C6 and Ebanx in Brazil.
The sector grew in all its categories and counted 601 paytech (payments), 210 insurtech (insurance), 491 lendingtech (loans) and 222 wealthtech (investments) companies.
The reproduction of these types of organizations is, however, leading to a growing need to sharpen their focus in order to convince an increasingly careful and demanding clientele.
That’s why strategic decisions are gradually turning to the correct productization of customer data, in order to gain competitive advantages and generate data-driven decisions.
The power of Big Data
Information is the cornerstone on which any business model is based in this hyper-connected and hyper-technological world. Therefore, Big Data -the information generated, stored and processed in networks- becomes central when it is systematized and analyzed in order to make strategic decisions.
It is important to note that data that does not go through these systematization and validation processes is not productive, and that is why it is essential to resort to data science and, consequently, to data management tools.
The fintech sector has the most active users, generating millions of daily transactions. While the global financial system generates an enormous amount of data every day, it is also true that the data is better systematized and for this reason more reliable. This means ‘productizing data’, or in other words, make it profitable.
To this end, Data Management services that store, classify and organize data are essential.
With platforms such as Conciliac EDM it is possible to automate data management processes, save costs, anticipate and avoid risks, and centralize data management on a single platform to make decisions based on accurate data.
According to an article signed by Bassim Haidar, CEO of Channel VAS, on the site www.fintechmagazine.com, Big Data gave the final push to the growth of fintechs and made it possible to expand the offer in emerging countries with frequent economic crises and poor credit systems.
Haidar points out that this is so because data management “allows companies to complete complex tasks like risk assessment, providing financial access to groups of people who were previously inaccessible”. In addition, the competition for customers is driving efforts “to innovate and improve their tools, services and offerings to enhance customer loyalty and surpass their competitors”.
Automated data management tools, among many other benefits, allow fintech companies to complete normally time-consuming and costly credit scoring and credit risk assessment tasks more quickly and cost-effectively.
Their use, moreover, enables new credit risk models for nano and microfinance that benefit the unbanked and underbanked users by providing a wider range of options and access to the financial highway.
A marketing study conducted by PwC in 2020, points out that customer experience beats price and product as the main differentiator of brands.
According to the analysis led by 7puentes, company specialize in big data, this concept was crucial to the development of digital service applications that focused on personalized customer relationship strategies, the so-called hyper-segmentation.
The idea is that “when the marketing department offers three or four star products horizontally, with expensive promotional campaigns, it focuses on a traditional segmentation that sometimes moves away from the individual needs of each one of its customers”.
On the other hand, with 10 to 15 highly personalized product offers per month you can attract individual customers, running campaigns that can be easily executed in a few clicks and are very easy to understand.
This is only possible in a real-time strategy from the use of Big Data, Artificial Intelligence (AI) and Machine Learning techniques.
The Fintech industry is one of the industries that makes the best use of these tools and has enormous opportunities to take advantage of them.
While it is true that banks and financial institutions know the movements of their customers with traditional structured information, the opportunity of having external unstructured customer data, such as social networks, geolocation, internet activity in general, allows them to know more accurately each of their customers individually, anticipate their needs and develop a targeting strategy to achieve greater loyalty.
The analysis of large volumes of data also allows you to detect patterns and behaviors in order to offer personalized financial products, the most appropriate and tailored, that can achieve a better customer experience and greater satisfaction (such as reward programs, loyalty, memberships, premium cards and exclusive discounts).
The key question is: what data management tools can further empower the growing fintech industry?
A complete data management platform such as Conciliac EDM allows to centralize, automate and standardize all the processes involved in data treating, such as integrations, reconciliations, validations, consolidations, extractions and transformations among others.
To learn more, ask for a demo.