To improve the performance of any organization the role of data is integral. An ability to process the right data by Fintech companies provides them a huge competitive advantage . This is because artificial intelligence (AI) algorithm can process these data and provide opportunities for (i) better allocation of resources (ii) identifying demographics of target clients (ii) realizing the client needs and allow quality customer decision making. Hence organizations are allocating a portion of their investment on data management.
However there are different types of fintech companies, including: Personal finance, Wall Street, Crypto, Investment, Lending, Payments and Real Estate. Each of these categories require different sets of data volume that requires updating at different frequencies. There ARE an approximate 52% increment in Fintech startups by February 2020 according to statista.com. Hence having knowledge on the _“useful”_data gives a competitive advantage over other startups in the same field.
The different fintech sectors according to their capital startup [data source: Forbes 2019]
Examples of big corporations or organizations that depend heavily on data would be amazon, google and facebook. They collects data of their users/clients as they navigate through their platform. This census gives them advantage to acquire information regarding their target audience demographics and their interest. Businesses can easily utilize these data and with the application of AI and machine learning (ML) they can create better products and perhaps improve their services to their clients. Also regression analysis and programming can allow to forecast future events. These can eventually help companies to plan ahead and allocate their resources accordingly.
Basic terminology used in data science
- Data volume: It is the amount of data that is collected and stored by the organization that can be utilized for future processing by their developed AI algorithm.
**_2. Data velocity: _**It is the rate at which data is being processed. There are five different data velocity categories. Real time, near real time, batch, custom and analytical. To get a competitive advantage fintech companies need their data velocity at real time or near real time. However, it also depends on the category of fintech companies. For example, data pertaining to wall street, crypto and investment needs to be executed at real time or near real time because of the volatility involved in the process. However, payment and lending companies can allow 1–2 business days to settle any transactions of funds. This gives additional advantage to avoid any fraudulent transactions.
#data-science #fintech-startups #data-management #data analysis