Customized for your Business
Machine Learning Software for Insurances
Risk prediction
Risk assessment of insurance policy applications needs to be calculated carefully. This can be a rather laborious and costly process. ML methods can be used to predict the risk of an application more consistently, faster, and with better results.
Claim processing
Natural language processing (NLP) techniques can extract correct information from unstructured documents, even if it contains some misspelled words or inconsistent data. This increases the number of claims that can be processed automatically, saving time and human resources.
Fraud detection
Given the amount of data, manual detection of insurance fraud can be time-consuming and costly. With Machine Learning (ML) and Natural Language Processing (NLP) algorithms it is possible to develop models that automatically flag suspected cases. Fraud detection can thus be efficiently implemented to work with unstructured data (e-mails, messages, online claims, among others).
FAQ
Why dida?
We are a software company specialized in Algorithms and Machine Learning (ML) and most of our 30+ employees have a scientific background in Mathematics and Physics. We follow the developments in ML research and have multiple years of experience bringing this knowledge to customers and into production.
Why a customized solution?
No Machine Learning task is alike. The data that is available and the requirements always differ and might not be captured by off-the-shelf software. From us, you get an individual solution. You own the code, the data and we integrate it into your current software environment.
What do we offer?
We offer initial proof of concepts and the complete development of production software. Due to the experience and background of our team, we can as well offer larger research projects.
I am new to Machine Learning
In our Tech Lunch, we will give you 45 minutes of information on a ML topic of your choice.
I have a project idea already
In our ML Expert Talk, you will get 1 hour of consultation & discussion about your specific use case.
Not sure? Pick the first option.
Your dida-Partner:
Petar Tomov
ML Project Manager
I am new to Machine Learning
I have a project idea already