Cabecera

Big Data & Machine Learning Strategy in Banco Santander

In recent years, Banco Santander has made a clear commitment to being a "data-driven company", putting data and advanced analytics at the center of all its decisions. The better use of the data allows the bank to give a better service to its clients, to give better working tools to its employees, and as a consequence to contribute more value to its shareholders and society.

 To this end, the bank has worked on a series of axes that have allowed it to position itself as a leading company in this field, recently receiving the award for "Best Big Data Corporate Strategy" in Spain.

During the presentation we detail the advances that the bank has made in all these areas:

  • First, through the creation of the Santander data lake in Spain, which has allowed to have a 360º vision of the client in a single environment, improving the quality of the data, saving costs by amortizing dozens of information silos, and democratizing access to the data.
  • Secondly, to work with much more powerful tools, which allow a faster exploitation of the data, with better algorithms and at a lower cost (open source).
  • Having better data and more advanced algorithms, the bank is developing a new set of models that allow it to make more accurate decisions in the areas of risk, commercial, fraud detection, and so on. In Santander we are committed to the models (85% of risk decisions are automatic) and the important improvement of the models through Big Data and Machine Learning is having a direct impact on P&L
  • These new methodologies are also helping us in the digitalization of processes. Through API-fied processes, which automatically read data from different sources, and with better models, we provide the client with simpler processes that allow an improvement in satisfaction and a higher level of sales.
  • And all of the above is done with teams that are in full transformation. The bank has just launched the fourth edition of the Big Data training program, where current employees and scholars from different universities participate to learn the new methodologies of Big Data, Machine Learning and Artificial Intelligence.

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