The AI revolution is here. And as a matter of fact, this transformative era is defined by two monumental milestones. Firstly, the astounding speed of data indexing, backed by the vast improvements in computational resources we’ve witnessed recently. Secondly, the ever-swelling ocean of information, growing exponentially each day. But this data-driven revolution isn’t just about quantity—it’s about discernment. It demands tools that can sift through the noise to unearth truly relevant information or, in simpler terms, the art of information enrichment. Let’s dive deeper into this narrative where organizations are tirelessly trying to innovate, not just in data collection, but in meticulously analyzing and preparing this data for models that mitigate risks for specific use cases.
Artificial Intelligence (AI) primarily pertains to models and algorithms designed to generate new and meaningful data based on patterns and insights that reality produces, which are derived from existing data systems. Information that doesn’t accurately reflect the realities of challenges or risk assessments that insurance and financial companies face is unhelpful in improving performance. Therefore, the challenge isn’t just about collecting relevant data but also aligning this information with an organization’s existing records. This integrated data, which is often a combination of internal and external information, forms a comprehensive whole. As the saying goes, “the whole is greater than the sum of its parts”.
So, what is “relevant data enrichment” exactly? Data enrichment involves enhancing existing datasets by adding information, attributes, or additional connections, thereby increasing their value and usefulness for analysis. Data enrichment focuses on creating data points that align with the characteristics and patterns of the original dataset. At Seenity, we know how to expertly accomplish this and connect every piece of information to the correct row within all datasets. Seenity’s enriched information is partly analyzed in real-time, while some of it is based on predefined models using enriched data, which in turn enhances the company’s performance.
At Seenity, we are deeply immersed in risk assessment and the data that impacts the accuracy of these assessments. This is a specialized field in its own right, based on numerous studies and the historical investigation of millions of data records. As such, we are laser-focused on delivering the most relevant information and integrating it with internal data, both during model creation and prediction stages.
