Finance
In the financial industry with a large amount of data, the introduction of artificial intelligence and big data analysis can bring new changes to the business models of banking, insurance, and securities industries. The introduction of artificial intelligence can provide tailor-made investment solutions based on the background information of consumers. It can also assist banks to predict personal and company credit scores, market risks and development trends based on public information on the Internet, and create new business models and customer value.
Technical Description
Natural Language Processing (NLP) model training is carried out through a large amount of data provided by financial institutions such as the economic environment and social trends, so that the system can understand the key factors before and after economic changes in the past. Then, through the Convolutional Neural Networks (CNN) of deep neural network technology, the key information in the financial statements, news, newspapers and magazines publicly disclosed by individuals and enterprises is detected and converted into readable structured information for application systems. Through massive data analysis and continuous optimization of NLP models, financial institutions can analyze future trends and make comprehensive indicator forecasts, as well as track credit scores and potential risks from external consumer information.
Digital Watermarking
Digital Watermarking can be used to control digital intellectual property rights and detect digital image attacks. Encoding specific information into digital signals such as pictures, audios, images, documents, etc., except the legitimate owner, other people cannot decode or detect the digital watermark contained in the image, which is a trend of protecting intellectual property rights today.
If a file containing a digital watermark is copied, the embedded message will also be copied. If the original data is tampered with, it can also be detected at the receiving end, and the tampered part can be accurately identified. This technology can also be used to identify composite photos, or subsequent data recovery work for the forensic analysis.
