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Using Big Data and Machine Learning to Transform SME Lending Business

In the Fintech sector, Machine Learning, Artificial Intelligence & Big Data is gaining more popularity because ML can evaluate huge data sets. Banks, Financial institutions & Small business lenders get an ambitious advantage to cope with the changing fintech industry landscape by adopting ML, AI & Big Data.

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Using Big Data and Machine Learning to Transform SME Lending Business

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  1. Using Big Data and Machine Learning to Transform SME Lending Business In the Fintech sector, Machine Learning, Artificial Intelligence & Big Data is gaining more popularity because ML can evaluate huge data sets. Banks, Financial institutions & Small business lenders get an ambitious advantage to cope with the changing fintech industry landscape by adopting ML, AI & Big Data. Alone in the Financial world, In 2019 use of big data & machine learning reached an estimated value of US $6.67 billion & expected to grow over the US $22.6 billion in the coming five

  2. years. By 2025, it is expected that the fintech sector will also reach a CAGR(Compound Annual Growth Rate) of 23.37%. Using machine learning technology in the fintech industry reduces risks with more loan approvals. Numerous factors such as utilities, data from social profiles, rent payments, telecommunications companies, and even health checkup records will now count. Machine language algorithms monitor aggregated data sets with hundreds of other customers to generate an accurate risk score. In Fintech, hackers & thieves can be outsmarted by using machine learning applications. Machine Learning Solutions to Target in 2021-2025? In 2020, the pandemic and constant lockdowns increased the need for digital services. Now In 2021, there is a rapid increase in the demand for cutting-edge technologies in the Financial sector which means we can expect personalized approaches among banks and SME lenders. ML financial services and Big data impact on the Fintech sector In this global economy, the most data-intensive sector is fintech, due to which the impact of Big Data on the sector is very hard to overestimate.

  3. Fintech institutes & Banks have enormous amounts of customer business data including cash flow, income, expenses, behavior, performance, failure, and events, product-oriented industries, utilizing these rich data sets is hard. etc. Due to their It's been More than a decade, the fintech industry is investing heavily in data collection and processing technologies and is one of the prototypes in investments in Big Data technologies. And because of this change & increase in customer expectations, banks, small business lenders & financial institutions cannot leave those huge amounts of data unexploited. Alternatively, small business lenders, banks & financial institutes can take a competitive advantage by using financial data APIs to gather the data & maximize customer business understandings. How to Adapt Big Data & Machine Learning? An increase in the development of technologies tends to machine learning & big data in banking and lending will be more technically smart and adapted to the business lending process. Adopting the new technologies is better to start with a single element, sort it out, and only then pick up the other one. Original https://henrysmith81.tumblr.com/post/657946244340187136/usin g-big-data-and-machine-learning-to-transform Source:-

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