By Segun Saromi

An ongoing hot topic in the financial technology sector is the integration of novel technologies for developing data-powered FinTech solutions that support a paradigm shift for serving a personalized user experience to young people needing customer-centric financial services.

Thanks to the advancement of big data and data analytics, FinTech organizations can now create novel ideas that are targeted to the specific requirements of young adult clients. However, it’s equally important that you comprehend how preceding generations have developed in terms of their requirements and financial inclusion.

For the old generations, it was practically hard to access financial services and core education. For instance, our parents who are now in their late sixties and seventies, experienced the absence of financial literacy and limited access to good financial services. To buttress my point, our parents were heavily trained in the traditional way of keeping money at home while those that lived in the city could make use of limited banks available at the time.

Due to their complete reliance on traditional financial institutions, the majority of which charged exorbitant fees and provided limited services that could take days to complete, they were only minimally able to adapt to FinTech alternatives.

Gen X, on the other hand, has to cope with a distinct set of problems that are exclusive to their generation. With the polarization of the internet and technology, it changed the way Gen X accessed financial services.

They were the first generation that have access to digital banking and credit cards, making them more likely to use online payment methods. Even then, adverse consequences including the increase in consumer debt and financial fraud have been cited.

While the Millennial generation, sometimes known as Generation Y, had unique problems. The effects of 2008 & 2016 economic recessions, had a significant effect on their ability to achieve financial stability and saving culture.

Most of the Millennials had problems getting jobs, and those who eventually got them were forced to take jobs with low remunerations. Many Millennials felt pressured to delay significant life milestones like becoming homeowners or starting a family as a result.

The first generation to have grown up with mobile phones and social media platforms is the post-millennial generation or Gen Z. They are also the first generation of children to see firsthand the repercussions of the 2008/2016 financial crisis on Gen Y, which has improved their financial literacy and prudence.

In essence, consumers of Generation Z are distinct from other generations in terms of their financial services requirements and preferences. They are the current generation of customers that are more likely to use digital banking products or services with a user-friendly interface and personalized customer experience.

In order to meet this new demand by young adults, fintech startups are making use of algorithms that analyze data to offer personalized financial services that cater to the needs of their young clients. For instance, some FinTech institutions use machine learning algorithms to examine customer data and offer tailored financial advice. Data is being used by other FinTech service providers to create new finance and investment solutions that are aimed at specific Gen Z market segments.

Gen Z users’ experiences are being improved because of the usage of data by FinTechs. This is because this age group’s likes and behaviors tend to change oftentimes. As an illustration, some companies use data to adapt user interfaces and make them more simple to use. Others are using data to build chatbots that can immediately provide support and answer questions in real time. Thanks to the advancement of technology.

As posited that data-driven models can help FinTech companies better serve Gen Z clients, it’s important to keep in mind that these models would not be possible without high-quality data. It is like a GIGO – “Garbage in Garbage Out”.

These models would definitely be affected by biases and errors in the absence of accurate and trustworthy data sources. A more reason that FinTech companies verify the fairness and accuracy of their data-driven algorithms and be honest about them is that they are only as trustworthy as the data they are trained on.

In summary, combining innovative models to develop data-driven financial technology products and services with a focus on improving the user experience of young people for personalized financial services is a potential area of innovation that needs urgent solutions. A trend that will continue to support Gen Z and the coming generation to have unrestricted access to individualized financial services and education.



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