Have banks overtaken FinTechs in data science and data engineering?
By Evita Lune - Equity Partner and Global Head of the FinTech Practice Group
January 2026
Recently, I interviewed 30+ Directors of Data Science and Data Engineering across Europe — primarily in Sweden, Germany, Poland, Latvia, and Finland.
To my surprise, candidates from the banking sector — especially modern banks with strong international tech hubs — demonstrated a significantly higher level of technological maturity than our usual suspects: online lenders, scale-ups, and neobanks.
What do I mean by this?
Cloud-native data engineering & AI
Modern banks have largely migrated to the cloud, while some mature FinTechs still rely on proprietary infrastructure. Cloud adoption enables native access to ML platforms and significantly improves model accuracy and speed.
Today, a strong Head of Data Science is expected to master tools such as: Python, SQL, Apache Spark, Databricks, TensorFlow, PyTorch, Airflow, Git, Docker, Linux — as well as GenAI & LLM stacks including OpenAI, Claude, Gemini, LLaMA, Hugging Face, PEFT, LoRA, QLoRA, FAISS, Chroma, OpenSearch, LangChain, LlamaIndex, Haystack, and CrewAI.
LLMs & Generative AI in production
Banks have invested heavily — perhaps even beyond comfort levels — but the results are impressive. Entire parts of the banking value chain have undergone evolutionary change:
from KYC and AML, early warning systems, and document processing, to self-service customer care, robo-advisors, and automated reporting.
More effective end-to-end processes
Banks are applying advanced data science across the value chain:
- smarter prospect targeting within CRM systems
- self-learning credit scoring models using vast API ecosystems and alternative data
- internal LLM tools reducing customer queries and operational load
Leadership and business context matter
Directors of Data Science in international banking hubs are typically well-trained in stakeholder management and understand the full business context of their mission. This is one of the most demanding leadership roles today — combining deep technical expertise, business acumen, and the ability to lead highly advanced teams.
Many thanks to Iana (Yana) Gudima and Valeri Artemov for arranging these conversations.