What makes changes in FinTech? FinTech as such is changing, and the latest technologies being updated are changing the course of its actions. However, Finance and technology have become interdependent- the very term ‘FinTech’ proves this fact!
Other technological paradigms are also making strong effects on FinTech and the latest we have in this line is Machine Learning. What is Machine Learning? How is it making impressions in the FinTech sector? Let’s have a brief understanding.
Machine Learning (ML) technology analyse data, learn from data, identify patterns and make intelligent decisions. ML is basically a data analysis method that automates analytical model building and minimizes human intervention and effort.
FinTech has an extensive customer database that has a variety of processes to handle like banking, transactions and credit scoring, to name a few. FinTech’s probabilities of fraudulent activities are on a high scale, the failure to curb this will eventually lead to a disastrous status quo. With Machine Learning subsisting through FinTech, we can carry out activities like Credit Scoring and Fraud Detection.
As far as customer studies are concerned, ML can conduct data analysis on customer behaviour to make their services more customized, which eventually leads to individual customer satisfaction. This means that FinTech companies using ML can manage user experience, suggest new products and equip chatbots to critically study the customers’ transaction and bill details.
Insurance companies also endorse ML as it has proved to create a connected network of the company with its customers, allowing deeper understanding of them. The Insurance companies have claimed to fix premium plans to customers and decide on pay out details based on the collected data. InsurTech sector which is considered to be one of the subsets of FinTech is on the edge of a technology-driven industrial shift.
Let us hope that this harmony between technologies continue to grow and create overpowering outcomes as always!