In commercial insurance, ensuring the accuracy of data is essential. However, it is surprising how often even the most basic data, such as activities, can be incorrect.
This reveals a widespread problem in the industry: inaccuracies abound, and the consequences can be far-reaching, damaging to the customer and to insurers’ profits.
How is this problem generated?
There are two main reasons: errors in data reporting and failure to update data. The most common situations include manual errors during the filing process, outdated information, and discrepancies between submitted addresses and actual business locations. What is the result? Inaccurate data that undermine risk assessment and decision-making processes.
However, in the middle of this challenge lies an opportunity for transformation. The solution lies in harnessing open data and technology to tackle the problem at its source, following three clear steps:
1. Leveraging Internet data
The internet is a treasure trove of information for any insurer. From official sources, such as commercial and land registers, to user-generated content on platforms such as Google, social media and company websites, there is a wealth of data waiting to be tapped. Thanks to this data, insurers can improve the classification of their business clients’ activities by ensuring that they are correctly updated.
2. Filter the data
However, the wealth of data requires a method to properly filter the information, which is crucial to extract the data that we consider relevant and accurate. This involves separating outdated or erroneous data from reliable sources and refining the dataset to ensure its quality and relevance. In essence, it is about removing the noise to find the signal. Here, data analysis algorithms and AI are essential.
3. Apply technology
For the filtering of this data, technology is key. By leveraging advanced algorithms and machine learning models, insurers can automate the process of data analysis and validation. From identifying patterns to classifying activities, technology streamlines the workflow, enabling insurers to provide accurate and up-to-date information to customers with confidence.
In conclusion, addressing the challenge of inaccurate customer data in commercial insurance requires a technological and multipronged approach that combines open data, technology and robust processes. By taking a systematic approach to data acquisition, filtering and application, insurers can unlock new opportunities for risk assessment and customer engagement. In an industry where accuracy is key, these steps clear the way for informed decision-making and sustainable growth.
If you want a technological solution that allows you to take advantage of the potential of Open Data, do not hesitate to contact us or ask directly for a demo.
