Protection of personal data
Employers are now subject to certain obligations towards their employees with regard to the protection of personal data. One of them is to inform employees about processing operations and possible violations thereof.
Aqsone has developed a tool based on advanced deep learning technologies that allows documents containing personal data, such as e-mail addresses, personal identifications, banking or health data, to be identified on the company’s various servers. These developments were carried out in python language, and use different techniques of Machine Learning, Deep Learning, and automatic language processing, as well as character recognition (OCR). The company thus has full control over the content of its directories, whether public or private, and is in compliance with the general regulations on data protection (RGPD).
Detection of expense claim fraud
The management of expense claims in the majority of companies is inefficient and fails to counter fraud, despite fairly significant investments (manual workload, dedicated tools, etc.). Beyond the financial amounts, which are very important, it is the image and ethics of the company that are at stake.
Aqsone is developing data analytics techniques to improve fraud management and detection by directly analyzing receipts using advanced Machine Learning and Deep Learning algorithms. There are numerous use cases: categorisation of scanned tickets, identification of duplicates, extraction of data from the scans, analysis of the location of the expense claim, verification of deductible VAT, etc. The technologies involved range from NLP (Natural Language Processing) to Neuron Networks.
The solutions implemented allow a significant reduction in the costs of expense management for the company and an improvement in performance.