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Banks & Insurances

Increase banking and insurance operations efficiency and customer satisfaction

© unsplash/Sean Pollock

With Machine Learning, banking and insurance operations can be optimized by:

  • improving your compliance operations e.g. by backing your Anti-Money Laundering surveillance with ML algorithms

  • decreasing your claim processing times by automation while ensuring fraud detection

  • capitalizing on arbitrage opportunities through accelerated information processing

Case Studies related to Banks & Insurances

Natural Language Processing

Legal review of rental contracts

Different methods from the field of NLP helped us to create a software that spots errors in legal contracts.
Our solution
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Natural Language Processing

Semantic search for public administration

dida developed an AI based algorithm to extract relevant information from authority documents.
Our solution

Webinars related to Banks & Insurances

Recurrent neural networks: How computers learn to read

The webinar will give an introduction to the functioning of RNNs and illustrate their use in an example project from the field of legal tech

Fabian Gringel

Machine Learning Scientist

Automated answering of questions with neural networks: BERT

In this webinar we will present a method based on the BERT model for automated answering of questions.

Mattes Mollenhauer

Machine Learning Scientist