{"id":6842,"date":"2023-01-17T00:00:00","date_gmt":"2023-01-17T00:00:00","guid":{"rendered":"https:\/\/www.moresophy.com\/new-challenges-demand-new-solutions-artificial-intelligence-identifies-risks-in-big-data\/"},"modified":"2025-04-11T12:54:00","modified_gmt":"2025-04-11T12:54:00","slug":"new-challenges-demand-new-solutions-artificial-intelligence-identifies-risks-in-big-data","status":"publish","type":"post","link":"https:\/\/www.moresophy.com\/en\/blog\/data-driven-business\/new-challenges-demand-new-solutions-artificial-intelligence-identifies-risks-in-big-data","title":{"rendered":"New Challenges Demand New Solutions: Artificial Intelligence Identifies Risks in Big Data"},"content":{"rendered":"\t\t
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Andreas Zwick<\/a><\/p>\n\t\t\t\t\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t

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New Challenges Demand New Solutions: Artificial Intelligence Identifies Risks in Big Data<\/h2>\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t
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Tornadoes and floods such as those currently occurring in the USA, the COVID-19 pandemic and the war in Ukraine have shown how diverse environmental factors not only threaten people in the respective regions, but also have a direct impact on globally active companies. In the age of “just-in-time production”, this quickly leads to interrupted supply chains and a lack of resources. Unstable societies in a globalized world pose further dangers. In short, the diverse risks for globally active organizations continue to increase. <\/p>\n

Monitoring and early detection of these risks is becoming an ever greater challenge for companies. Added to this are stricter laws such as the new supply chain laws or internal company sustainability requirements. Global and company-wide risk monitoring is increasingly becoming a central task in compliance departments. However, without technical support, not all internal company documents and all relevant external websites worldwide can be monitored for potential risks. Artificial intelligence is needed to take over these tasks automatically and issue warnings if a potential risk arises for the respective company or society. <\/p>\n<\/p>\n

MORESOPHY’s new AI models do exactly that: With over 18 risk categories, including sustainability, diversity, pandemic, illiquidity, hate speech, catastrophic events, crime, illegal drugs, military conflicts and many more, MORESOPHY automatically recognizes differentiated risks in huge volumes of text. By semantically understanding texts with the help of AI, potential risks can now be identified even faster and more precisely. This enables companies and organizations to protect themselves more effectively against potential risks. <\/p>\n\t\t\t\t\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t

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The most important corporate sustainability topics in 2022, generated by CONTEXTCLOUD based on CONTEXTSUITE technology. <\/figcaption>\n\t\t\t\t\t\t\t\t\t\t<\/figure>\n\t\t\t\t\t\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t
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How do AI Models Actually Work?<\/strong><\/h2>\n

The AI models for classifying texts are based on machine learning. In particular, they use natural language processing (NLP) methods. <\/p>\n

An important part of these AI models for recognizing risks is the so-called “semantic understanding”.(Read here how a computer can learn to understand natural language use<\/a>) This involves the use of methods such as word vectors (how computers recognize language without a dictionary is explained here using the N-gram method<\/a>) and neural networks to capture the meaning of the words and phrases in a text. This enables AI to understand and interpret textual content accurately. <\/p>\n

The AI models are “trained”<\/a> using large volumes of pre-classified, i.e. evaluated texts (so-called training data), such as news articles or company reports, which are divided into the various risk categories. The models then learn<\/a> which word and phrase patterns in the texts are typical for certain risk categories. However, obtaining this data poses major challenges for many AI companies. MORESOPHY has developed its own innovative processes to obtain large volumes of reliable training data. This not only includes a corresponding infrastructure for web crawling. There is another point that is much more crucial, and which is particularly critical of the large AI models developed by US technology companies. Since a model learns everything it is given to read, it is crucial to take appropriate care when selecting and evaluating content. MORESOPHY therefore develops its AI not only with large amounts of data, but on the basis of an end-to-end process that offers maximum transparency across the database. This transparency is critical to success, especially in a topic as sensitive as risk management. <\/p>\n

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Possible Applications for AI Models to Identify Risks<\/strong><\/h2>\n

There are many fields of application for artificial intelligence models for the detection of risks, as they are able to classify large amounts of data in a very short time. Some examples of the use of these artificial intelligence models could be: <\/p>\n