Data as the New Revenue Source for FinTech
Fintech’s booming presence and the disruptive waves it has been creating in the financial industry for years now, is something global finance leaders had been expecting for a long time now.
They knew it was time now for technology to take over the financial industry and do what it does best: make lives easier. That is exactly what fintech companies, around the globe, try to do for the common man. They made mundane tasks like saving, applying for loans, and every day payment processes easier. In the entire process, they ended up creating not only trust and a feeling of comfort among individuals when it comes to finance and banking. A feeling that is otherwise not really common when it comes to the finance and banking industry.
When people start trusting a brand, a process, or a certain technology, they become more open to exploring further. They are more open to share information in exchange of these services at a nominal fee. The information that they share, is nothing but pure gold for companies who are planning to introduce new products and services into the market; whether they are financial products or services, or consumer goods.
In order to ascertain whether a product or service will thrive in the market, it is important for companies to find out:
• How consumers perceive the product offering
• Their purchasing power
• Whether they need the product, and
• If they are willing to invest into the product or service.
All this information can be acquired right from the consumers, and this is the kind of data fintech companies around the world are looking to capture and use to generate more revenue.
Mobile payments vs. data as revenue
It is not just fintech companies that are adding to their list of consumer-based services. Ecommerce companies and other tech-companies are following suit, too. For example, Grab, a Singapore-based company that provides ride-hailing service, raised $200 million to add more fintech offerings to its list of services. Currently, Grab is southeast Asia’s largest non-banking financial services firm. It provides a host of other services such as a payment platform, micro loans etc, and handles over $1 billion worth of transactions, every year.
Providing a mobile payments platform gives fintech companies the ability to access the purchase history and patterns of millions of users at a time. The sheer amount of data flowing in with specific information about who is buying what and how much of it, how are the purchases timed and how they are buying more or less of something is giving fintech companies accurate and actionable insights.
In fact, Alan Qi, VP and Chief Data Scientist of Ant Financial, an Alibaba initiative, mentioned that the term fintech should be actually replaced by techfin, given the extensive use of AI in the sector to churn data to learn more about consumer mindset. With a valuation of $150 billion dollars, Ant Financial is currently the most valuable unicorn in the world.
Ant Financial has shown the fintech world that there is clearly a much more lucrative path beyond the usual fintech services of easing banking and payment processes and providing micro loans to small-scale industries and individual consumers.
With singular focus on intensive research on AI and by expanding their credit and technology services to client companies, Ant Financials has posted over $611 million of pre-tax profit in the recent fiscal quarters. The company also managed to obtain an impressive $14 billion in its series C funding.
Finance industry has never been so customer-centric as it has become now. Competitors at the very top have now expanded into service businesses such as beauty services and grocery delivery. The reason why they can maximize revenue and expand based on this business model is because they have been collecting and aggregating data for a long time now. AI and ML can now help companies track patterns and identify which product to push to which consumer. Hence, it should be noted that payment technologies and gateways did go a long way in helping these companies gather the consumer data required to make this possible.
How specific data can help companies?
Ride-hailing services like Grab and Go-Jek have database of their consumer which clearly lists their pick-up and drop destinations and schedules. If the consumer only uses a certain app, like Grab through-and-through for all their transport requirements, then Grab will even have access to information such as, how much time the customer spends at a certain location and to a certain extent their financial habit, too. This will help third party service providers push targeted ads and increases chances of conversion.
The secret ingredient to ensure success for any company is providing specific, bespoke service to customers, at the right place and the right time. People differ and so do their purchasing power or behavior when it comes to spending, but data that they have entered themselves will seldom be wrong. This is the power of data that fintech companies are now wielding and using to provide customized products and services to customers, which would otherwise be a niche market where no one would want to wander.
Tech companies that are entering the fintech zone, stand to collect huge amounts of consumer data, too. They can create an additional revenue stream by selling this data to third parties for whom this niche information could be particularly useful.
Pros and cons of data as a revenue model
While data does seem promising as a revenue model for fintech companies, there’s always the risk of data redundancy. It is estimated that the sole cost of data redundancy would be close to an astounding $3.3 trillion by the year 2020. In the process of handling this data redundancy, about 21% of businesses dealing in handling this data will suffer reputational damage.
This can be avoided by addressing data redundancy. Companies are talking more and more about Big Data and analyzing this master data set, but what they need to do first is find out what they want out of Big Data. They might want to reduce costs, improve processes, or introduce new product/service offerings using this data, but the gap between Big Data and monetizing it require careful strategizing and planning. Companies should try to enhance their data to turn it into a more valuable asset. By using the initial data obtained, they should try to upsell and cross-sell further to gain further insightful data about their client, thereby gradually increasing the economic value of the data and turning it into valuable asset.
In order to ensure that fintech companies do not suffer from data redundancies, they need to ask these three questions:
• Do we need to clean this data?
• Do we need to run this data through analytics?
• Do we need to understand the context of this data better in order to be able to use it in an appropriate manner?
Tech companies have been using data as a revenue model for quite some time now. Fintech companies have also adopted the process and are branching out further into new service lines and business models based on the data they have been gathering through their fintech initiatives.
Although the shift from financial transactions to data might seem like marching into an unfamiliar arena, to other fintech firms, but the truth is that the data driven method is more likely to provide success in ensuring customer satisfaction and building a loyal customer base. This will in turn help companies that master this technique grow and expand faster and further.
