The number of everyday tools for data science keeps growing, covering an ever increasing spectrum of tasks. We at Swedbank use part of our daily scrum meetings to introduce and discuss some of these new tools. Below, we present a selection of recently “discovered” flavors.

In our team at Swedbank we work based on the agile principles and during the daily stand-up sessions we have introduced something we call “tech tips”. Essentially, it means that each team member can share technical tools or information that might be useful for the whole group. …

On 30th of January this year we will be presenting some of our work at the sTARTUp Day, one of the biggest business festivals in the Baltics. The sTARTUp day gathers regional enterprises, entrepreneurs, and academia in Estonia’s renowned university town Tartu.
In our talk we will introduce Analytics & AI at Swedbank, discuss shortly our efforts on anomaly detection, and dive a little into Natural Language Processing (NLP).

As the name suggests, NLP is of great use when working with large amounts of semantic data. In banking, knowledgeable insights from such type of data allows for a better understanding…

TL; DR: In instances of missing data, a rather common task is to build binary classification models for customer types based on their corresponding names. Such models can be built in a variety of ways. In this brief walk-through, we look at three distinct approaches each with a set of benefits and drawbacks. We use data from the Estonian Tax and Customs Board and deploy our final model as an open web application.

Problem statement

In most incoming bank transactions the bank is able to differentiate if a payment is coming from a private person or from some institutional (e.g. …

Lehar Oha

Data Scientist at Analytics & AI @ Swedbank Group

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