How To Make Your ML Algorithms Think Like A Human

The finance industry is a prime use case for machine learning, thanks to the abundant data sets, access to capital and strong incentive for efficiency and predicting future outcomes. While rule-based workflows are well embedded within the industry, many businesses are now turning to machine learning to automate the algorithm building process, especially when it comes to fintech.

As digital services become more widespread, financial organisations need to move beyond rule-based mechanisms and manual data analysis to ensure compliance, security and customer service. Machine learning is more scalable, flexible and reliable when implemented properly, but requires the right data to deliver actionable insights.

This is especially the case when it comes to making predictions about human behaviour. At a recent developer meetup, I heard from Ben Houghton, Head of Data Science for Barclays Payments, about his data approach and how he makes his algorithms think like a human.

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Credits: Finextra

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