Racing Into Machine Learning: Data Readiness & the Developing World

Let's Talk Payments · Aug 1, 2017

Machine Learning (ML) technology can help us draw important insights from data, but it is imperative to recognize a model is not an end in and of itself. Based on BFA’s experiences engaging with early-stage partners in emerging markets, such as Catalyst Fund investees, we have seen the consequences of rushing into machine learning without a clear understanding of the underlying data.

As a business, misreading this data can cause you to chase errant hypotheses around the needs of your core set of customers, which in extreme cases, can cost you everything. To this point, we recommend here that FinTech startups and other financial institutions focus first on producing and refining this data as the fuel to get an insights engine running, before exploring increasingly sophisticated models.

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