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Increasing the efficiency of claims processing and precise risk assessment

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With Machine Learning, insurance operations can be optimized by

decreasing your time to process claims by automatiion while ensuring fraud detection
assess risks accurately in underwriting, e.g. by automated satellite imagery for building insurances
estimate property damages after natural catastrophes from satellite data

Projects in Insurances

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Legal Review of Rental Contracts

Different methods from the field of NLP helped us to create a software that spots errors in legal contracts

Automatic Checking of Service Charge Statements

Semantic Search for Public Administration

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

Blog Posts in Insurances

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Project proposals - the first step to a successful ML project

By Emilius Richter July 18th, 2022

For a software provider, the project proposal is the first step toward meeting the needs of the customer. In this article, I will describe the most important modules in machine learning project proposals.


Ethics in Natural Language Processing

By Marty Oelschläger (PhD) December 20th, 2021

I explain why language models tend to reproduce stereotypes and prejudices with potentially harmful consequences - and how to use them with care.

Natural Language Processing

GPT-3 and beyond - Part 2: Shortcomings and remedies

By Fabian Gringel October 24th, 2021

Here I explain in which situations GPT-3 fails and why it is far from having proper natural language understanding, which approaches can help to mitigate these issues and might lead to the next breakthrough and what alternatives to GPT-3 there are already.

Natural Language Processing

GPT-3 and beyond - Part 1: The basic recipe

By Fabian Gringel September 27th, 2021

In this blog article I will explain how GPT-3 works, why some people think it’s dangerous, and how you can try out a GPT-3-like model yourself for free.


21 questions we ask our clients: Starting a successful ML project

By Emilius Richter May 21st, 2021

We discuss what questions should be considered and answered up front to launch a successful machine learning software project.


Enhancing Search with Question Answering

By Angela Maennel April 26th, 2021

Here I show how open-domain question answering systems work and how they can enhance search engines. We will have closer look at one specific type of system, DrQA.

Natural Language Processing

How to extract text from PDF files

By How to extract text from PDF files August 17th, 2020

In the following I want to present the open-source Python PDF tools PyPDF2, pdfminer and PyMuPDF that can be used to extract text from PDF files. I will compare their features and point out some drawbacks.


The best free labeling tools for text annotation in NLP

By Fabian Gringel March 30th, 2020

In this blog post I present the three best free text annotation tools for the manual labeling of documents in NLP projects. You will learn how to install, configure and use them and find out which one of them suits your purposes best. The tools I'm going to present are brat, doccano and INCEpTION.

Use Cases in Insurances

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