Analytics, ML and Data Science Help FinTech Offer Better Services

The use of big data, machine learning, data science in FinTech space is not a new concept (at least from the sound of it). The growth in data or data explosion is a function of multiple technological advancements. Adoption of cloud, mobile technologies and apps, wearable devices, intelligent/smart networks and systems, Internet penetration and usage are some of the major factors for growth in the overall data. We wanted to understand how FinTech players are making use of it (or not). Some of the areas in financial services that are applying analytics, ML and big data are listed below:

Credit Scoring: Undoubtedly, one of the major sectors that have seen unprecedented new solutions leveraging big data is lending and credit scoring. For decades, credit scores provided data based on basic financial transactions and served as the norm for all credit activities in the financial services space. Essentially, these new sources go beyond the available quantitative data from banks and assess qualitative concepts like behavior, willingness, ability, etc. The growth in segments such as P2P lending, SME financing is a result of these innovative scoring models. Examples of such startups include Credit Sesame, Faircent, OnDeck, Kabbage, LendingClub, Prosper, ZestFinance and Vouch ...

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