- Inspite of the current scenario, the surge in demand for data science services in various fields with market researches estimating its potential growth in the near future. According to a market report as per analyticsinsight, the big data market is projected to reach US$103 billion by 2027, up from US$49 billion in 2019. As of now, the market is anticipated to value US$56 billion in 2020. It has also been predicted by several market reports that the data science platform market size is expected to grow from US$37.9 billion in 2019 to US$140.9 billion by 2024, at a CAGR of around 30 percent during the forecast period.
- The coronavirus pandemic has taken a terrible toll on the global economy. The crisis is affecting various industries. However, fintech companies are most certainly prepared and combating well with the circumstances. The shift to a remote working environment has given a boom to digital industries including fintech. Financial institutions will gain a competitive advantage over fintech in this highly uncertain market environment as they are better capitalized, have bigger brands, and benefit from customers becoming more risk-averse, believes Rosenblatt. Fintech’s with recurring revenue and long term contracts will be impacted less than firms with transaction-based business models. As the report suggests, consumer and SME lending platforms: best-adapting mechanism to swiftly and efficiently deliver capital to key segments of the economy will be a winner overcoming pandemic challenges. Mortgage and life insurance digitization leaping forward with technology to disrupt the role of intermediaries, whose role was often face-to-face will also come out shiny. Online alternative lending, digital wealth management, and consumer banking are sectors most likely to see M&A deals, Moreover, fintech ‘enablers’ around AI, IoT, and software solutions are in high demand. These are based on the findings as published by Analyticsinsight
- RBI, the regulatory banking authority in India, announced its foray into the world of big data analytics by opening a data sciences laboratory that would employ professionals with skills in computer science, data analytics, statistics, economics, econometrics, and finance.
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