Red background with text Loan Acceptance Prediction. Successful targeting is about individuals, not customers.
Lukáš Dvořák

How can banks increase loan uptake among their client base? (Hint: the answer is data-driven.)

When it comes to lending, banks are increasingly harnessing the power of machine learning to drive targeted campaigns. But to offer the right loan at the right time, you need to understand how customers behave.

A map of the Czech Republic marked with pins, where you can get vaccinated for COVID-19, featuring the Profinit logo.
Peter Čmelík

Where can I get vaccinated? The application from OpenDataLab will tell you!

Go to the website ockovani.opendatalab.cz to get an overview of the openings to get vaccinated against COVID-19. The goal of the application is to give Czechs a quick overview of vaccination capacity, which, until now, hasn’t been available anywhere. The application…

Petr Paščenko, Profinit's Head of Data Sicence giving lecture on Social scoring and credit forecasting with Profinit logo in the corner.
Lukáš Dvořák

Social Scoring and Credit Forecasting: Data Science Breakfast

We held another professional breakfast, this time on the topic of credit forecasting. The breakfast was mainly directed at professionals from the fields of AI, data analysis, and modelling, but we also gladly welcomed directors and managers, especially from the banking sector as they are…

Webinar titled Banking transactions predictive analytics by Dominik Matula, Senior data scientist, hosted by Profinit.
Peter Čmelík

WEBINAR: Revealing clients’ behaviour from transactional data

We are living in a world of relations. Every click on a link, every article, image or video you have seen, every like you have given – those all make relations between you and some content. This fact is not applicable to social media exclusively.

Teal graphic with white text reading Advanced data analytics: How likely is your clients default?
Barbora Fuksa

Managing credit risk with advanced data analytics

The traditional approach to quantifying credit risk in retail banking often relies on the most obvious variables such as annual/monthly income, employment length, employment title, etc. While these are still valid indicators for calculating…

Graphic showing the phrase Machine Learning in Finance alongside a 3D cube illustrating applications like customer segmentation in banking
Lukáš Dvořák

Customer Segmentation in Banking

Every company doing business in retail has been dealing with customer segmentation, and so have banking organizations trying to describe their client base effectively. Customer segmentation in banking is key to the success of marketing campaigns, product cross-selling and risk scoring. That’s why it’s critical…

Abstract digital network with data points, connected lines and icons symbolizing the importance of accounting; and PROFINIT logo.
Barbora Fuksa

AI in Banking – 4 major pain points in the DACH region

by Barbora Janulíková, Business Development Manager Despite the common thrashing German, Austrian, and Swiss banks often get at conferences relevant to the topic; they do put a significant amount of effort into adopting AI for meaningful use cases. However, as with all…

Cartoon of airport checkpoint with officer checking documents and screen labeled BIG DATA — illustrating data evaluation in data science.
Bohumír Zoubek

4 most important applications of Data science in Banking

The Banking/Financial sector is just one of the many industries, which benefits hugely from data science-driven insights. With a natural affinity for numbers and quantitative methods, it surprises no one that it was one of the early adopters of Data Science, Machine Learning, and AI…

Text: instalment detector
Dominik Matula

Data is the new oil

Have you ever tried digging deeper into your company data warehouse? Perhaps you found one or two skeletons in the cupboard, but maybe also a hidden golden vein. If you haven’t, then it’s about time you roll your sleeves up and start the data mining!…