Yapı Kredi is a technology company established in 2015 to deliver innovative and patentable products and solutions with high added value. We develop innovative and R&D oriented comprehensive software projects, especially for banking and finance sector. For the solutions and products, we mostly employ artificial intelligence, machine learning, natural language processing, data mining. Several AI projects deployed so far has always been leader ideas in the era of bank operation models. We focus on the functions, application, systems that better translates AI results to the customers. Among all AI applications better results come out of customer centric solutions. We put ourselves in the customers’ place and focus on AI at key dialogue points.

We also cooperate with academic institutions, domestic and foreign R&D companies for the projects developed. We share the project outcomes in scientific articles and at national/international conferences with our industry partners and academia.

Yapı Kredi Teknoloji is a subsidiary of Yapı Kredi Bank which was established as the first national bank of Turkey in 1944.

Our main projects:

• SAFİR is an artificial intelligence application that classifies transaction orders that come from various channels (i.e. fax and email) and removes manual data entry by automatically providing transaction information from these orders. Thanks to SAFIR, you can increase work efficiency and minimize human errors.
• FOCA is a data discovery and value creation project that aims to support both operational process of corporate/commercial/SME sales and financial analysis departments by digitalizing free format trial balance documents in order to raise sales targets and automate financial analysis with a hybrid combination of natural language processing, machine learning and pattern recognition.
• SİDE is a machine learning project, based on credit card usage behavior and fraud methods in Turkey, which aims to boost success of current detection system that Yapı Kredi uses by improving detection of fraudulent transactions and reducing false detections.