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As people use more and more connected devices, the world of online data is growing at alarming speed. Investment banking and hedge funds management is exploring how to incorporate this data to make better business decisions. Machine learning and statistical modeling is the future. It enables companies to analyze data and use these insights to make predictions. By tracking patterns of customer activities and looking for unusual data points such as people accessing accounts at strange times, for example, machine learning can predict which transactions may be fraudulent. 


The Role of Business Translators

With this disruption in traditional banking models, interest in data science is growing. The data scientist creates the statistical models, trains the models and then applies the models to real-life situations. By tracking patterns of customer activities and looking for unusual data points such as people accessing accounts at strange times, for example, machine learning can predict which transactions may be fraudulent. But hiring pure technical analytics talent is only the first step.

According to the McKinsey Global Institute, financial institutions must also find and train business “translators,” who help data scientists understand business problems and ensure that analytics insights are communicated back to business units. These translators must be fluent both in the business language and the data scientist language.

"Financial institutions must also find and
train business “translators,” who help data scientists
understand business problems and ensure
that analytics insights are communicated
back to business units.

These translators must be fluent both in the business language and the data scientist language."

McKinsey Global Institute



The marriage of both talents can lead to transformative changes enabling businesses to:

  • Predict which services or products a customer would most likely need and when it would be needed.
  • Prevent and protect customers from fraud.
  • Analyze customer spending patterns and issue an alert if that customer is likely to exceed their credit limit.

These are just a few examples of what can be accomplished. But to excel in the future of machine learning and artificial intelligence you need good data scientists—data scientists trained in financial applications. That’s where the FDP Institute comes in. We offer the most comprehensive training for the data science financial professional.

To learn who should pursue the FDP Charter, see Who Should Enroll?


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