Imagine a small collision the bureaucratic process for compensation. A fragmented process, slow and that can take weeks, if not months, before a sum is actually liquidated.
Now, we rewind the ribbon and imagine a radically different scenario. From the same parking, take out your smartphone, open the app of your insurance, take some photos of the sticker following the instructions on the screen. Even before you put up behind the wheel, a notification warns you: your practice has been developed, the damage has been estimated and the compensation is already traveling to your current account. Total time: less than three minutes.
It is not science fiction but but theInsurtech, enhanced by the AI. A sector that promises a radical revolution in the insurance field: from long processes to instant and transparent experiences based on data.
Summary
How does the automatic report with AI work?
The beating heart of this system is a branch of artificial intelligence called Computer Vision (artificial vision). In simple terms, it is a field of study that aims to teach machines to interpret and understand the visual world starting from images and videos, in a similar way to how the human being does. The election tool to achieve this purpose are the Condicuctional neural networks (CNN), Deep Learning algorithms particularly effective in recognizing visual patterns.
Step 1: the AI eye, the computer vision
A conscolition neural network is a complex mathematical model that is inspired directly by the functioning of the human visual cortex. Think about how a child learns to recognize a car: he does not learn a definition by heart, but observes thousands of examples. His brain, in an almost magical way, learns to identify recurring characteristics (features): four wheels, headlights, a certain general shape. A CNN does the same thing, but on a much wider scale and with mathematical precision. It is "trained" on a huge dataset, which can contain tens of millions of photographs of damaged cars, each meticulously labeled by human experts.
Step 2: Training with the Condicuctional Neural Networks (CNN)
During the training phase, the network learns to break down an image into increasingly complex elements. The first layers of the algorithm recognize simple elements such as lines, curves and corners. The next layers combine this information to identify more complex shapes such as a light, a tire or a mirror. Finally, the deepest layers are able to classify not only the model of the car with extreme precision, but also the nature and severity of the damage. When I upload the photo of your accident, the AI performs this analysis process in a fraction of a second, diagnosing the problem with a surprising level of detail.
Step 3: the economic estimate of the damage
Once the AI has formulated its visual "diagnosis" (e.g. "dents of medium entity on the right front fender of a Fiat 500 Model 2021"), must translate it into an economic value. To do this, question a second intelligent system: a Estimate engine. It is a dynamic database that contains millions of constantly updated information, including the cost of each individual spare part for thousands of vehicles of vehicles, the standard labor time required for each specific repair and even the average cost cost of the bodies in the different geographical areas. By crossing the visual analysis with these economic data, the algorithm calculates a preventive for repair that is often more objective and coherent than the human one.
Who is already using this technology? Concrete examples from the market
This revolution is not only a future hypothesis, but it is already an operational reality for many of the main insurance companies. Large groups are investing massively in artificial intelligence to transform their processes and offer more efficient services to customers.
Axa Italia and the partnership with Microsoft for customized policies
A striking example is the strategic collaboration between Axa Italia and Microsoft. As reported by several newspapers including Forbes, the company is using cloud technologies and the computer giant to accelerate its digital transformation. In practice, this allows Axa to analyze enormous quantities of data to create increasingly personalized policies And to drastically speed up the management of claims, going from a reactive model to a proactive and predictive.
Helvetia group and the analysis of complex claims
Even the Helvetia group, as highlighted by sector newspapers such as Simplybiz, is implementing artificial intelligence solutions not only for simple claims, but also for the more ones complex. The AI supports human experts in the analysis of the damages, crossing data and images to provide a more accurate evaluation and, at the same time, identify with greater effectiveness of any streams of fraud that could escape a traditional analysis.
Generals and tariffs based on driving style
The General group It has long been pioneer in the use of machine learning. A great impact application is that of the dynamic rate car policies. Through the analysis of the telemetry data collected by devices installed on board the vehicles, AI's algorithms can evaluate the driving style of an insured. The most prudent and safe drivers are rewarded with lower rates, creating a fairer system and encouraging virtuous behaviors at the wheel.
The concrete advantages of the insurech for customers and companies
The adoption of artificial intelligence in the management of claims creates a virtuous circle of benefits for everyone.
For the Insured: compensation in real time and transparency
The most evident advantage for the customer is the drastic reduction in waiting times. A process that took weeks ends in a few minutes. This enormously improves the Customer Experience, transforming a moment of stress into an efficient interaction and without friction. Transparency also increases, since the estimate is based on objective data, reducing the discrepancies and long negotiations that sometimes characterize the relationship with the experts.
For insurance: Cost optimization and FRODE Fight
For companies, the economic benefits are enormous. The automation of the management of slight claims allows to reduce operating costs, freeing human experts who can thus focus on more complex and greater value cases. Furthermore, AI is a very powerful tool in Fight against fraud. Algorithms are able to analyze thousands of images and data to identify suspicious patterns: they can recognize if a photo has been downloaded from the Internet, if the damage described is not consistent with the dynamics of the declared accident, or if the same damage is reported several times. This allows you to identify fraud attempts that would be very difficult to find for a human operator.
The financial implications
The application of AI to the management of claims is only the tip of the iceberg. This technology is opening the doors to increasingly personalized and predictive insurance. In the future, insurance premiums could be calculated in real time based on the driving style (electronic), and the AI could be used to predict the risks and prevent them, instead of simply compensating them.
However, such a powerful technology also raises important regulatory issues. Authorities from all over the world are working to create a framework of rules that guarantees an ethical and transparent use of artificial intelligence, especially in critical sectors such as financial and insurance sectors. The European Union is at the forefront of this front with its AI Acts, the first attempt to the world to regulate the AI horizontally. This regulation classifies applications to their risk levels, and systems such as those for credit assessment or insurance rate tariffs are considered "high risk", imposing severe transparency and control obligations. Understanding these dynamics is crucial. The impact on the market is enormous and for those interested in the economic and investment aspects of this revolution, portals how Business They offer detailed analyzes on the evolution of the insurance sector (Insurtech) and on the new frontiers of the market.
A future already present
The artificial intelligence that evaluates damage from a photo is the perfect demonstration of how this technology is coming out of the research workshops to enter our everyday life, solving concrete problems. It represents a paradigm change that goes beyond insurance: it shows us a future in which the services will be increasingly instantaneous, personalized and guided by data, with the aim of simplifying our lives. The next time you see a small dent, therefore, do not think only of annoyance, but also of the complex and fascinating technology that, silently, is already working to solve it.