Claims Settlement with VIEWAPP: Integration with Calculation Systems and More
Accelerating claims settlement is one of the key objectives for insurance companies. At the same time, automation must be comprehensive in order to genuinely reduce labor costs and speed up decision-making.
VIEWAPP is developing a solution that combines remote inspection, fraud protection, damage marking, preparation of an electronic inspection report, and integration with calculation systems, as well as AI-based damage recognition trained on real data and expert feedback.
From photographs to a ready-made calculation: a single workflow
Typically, a specialist at a calculation center works with several tools at once: reviewing photographs of a damaged vehicle, matching them against parts catalogs, determining the necessary repair operations, and entering data into the calculation system. At the same time, the photographs and the calculation system may be on different screens, and inspection results may be documented separately in the form of a report.
VIEWAPP proposes combining these operations into a single interface. The expert opens the inspection materials, marks damage directly on the photographs, identifies the corresponding parts and repair operations. The resulting information is transmitted to the integrated calculation system, where the specialist continues building the calculation.
For example, the expert highlights damage to the rear bumper on a photograph, selects the corresponding part in the catalog, and specifies the required repair operation. The data is then transmitted to the calculation system, where work on the calculation can continue. If there are multiple damages, they are sequentially added to the claim being processed.
This approach reduces switching between programs and decreases the volume of manual data transfer. At the same time, the expert retains control over the result: the system helps perform operations but does not replace the specialist's professional judgment.
Electronic inspection report instead of paper
Another task is automating the preparation of the inspection report. To this end, VIEWAPP is developing damage marking tools and voice input.
The specialist can record damage, specify parts, and dictate the necessary information. This data is used to prepare an electronic report, which is delivered to the calculation center in a structured format.
This is particularly relevant for inspections at remote settlement points and for the work of field experts. Instead of sequentially filling out a paper document and subsequently transferring information to other systems, it becomes possible to immediately generate a digital result of the work, and the electronic report becomes part of the unified claim processing flow.
Integration with calculation systems
An important feature of the solution is the ability to integrate with the calculation systems already used by the insurer.
The possibility of integration depends on the technical availability of the relevant system and the readiness of its vendor to provide the necessary interfaces.
Depending on the customer's architecture, various interaction options can be considered: direct integration, use of an existing integration bus, or transmission of structured data through available interfaces.
For the insurer, this means the ability to develop automation without having to completely replace the existing IT infrastructure.
Anti-fraud: authenticity of photographs and geolocation
Remote settlement assumes that some materials may be collected by the policyholder themselves. This is convenient for the client but imposes additional requirements for fraud protection.
VIEWAPP places significant emphasis on verifying the origin of materials and identifying signs of possible manipulation.
Photograph protection. Shooting is done using the application's own camera, which does not allow ordinary uploading of pre-existing photos from the gallery. After images are captured, checksums are calculated and additionally verified on the server. If discrepancies are detected, the system signals possible modification of the files.
Geolocation analysis. Along with the inspection materials, metadata is transmitted that allows analysis of the location and circumstances of the shooting. The system identifies signs of coordinate substitution, including through the use of GPS spoofing tools.
Route verification. Geodata is analyzed collectively. The system uses mathematical anomaly indicators that help detect suspicious patterns in the inspection track. For tasks related to real estate, the route can be compared with the location of the property on a map.
Detection of screen photography. Additional checks help detect signs of photographing an image on another device. Such a situation may arise, for example, when instead of an original document or odometer readings, a photo of a screen is provided.
The combination of anti-fraud mechanisms helps the insurer assess the authenticity of materials before making a decision on the claim.
AI in claims settlement: automation based on expert marking
Damage recognition using neural networks can significantly accelerate claim processing. However, to automate calculation, it is not enough to simply identify the damaged area in a photograph. It is also necessary to correctly identify the damaged part, classify the defect, and determine the corresponding repair operation.
VIEWAPP is developing technology based on expert marking of real materials. At the current stage, the specialist manually marks damage on photographs, identifies parts, and classifies defects. The collected data is used to train a neural network model that learns to perform these tasks independently.
The quality of the initial marking is of fundamental importance: errors in identifying a part or the nature of damage can lead to incorrect calculation. Therefore, before assigning to the neural network tasks on which the final calculation depends, it is necessary to achieve the required recognition accuracy on real materials.
The goal of this approach is to gradually move from manual expert marking to automated damage processing. As the model is trained and its quality confirmed, individual operations can be transferred to the neural network, reducing the volume of manual work by specialists while maintaining the required level of accuracy.
It is fundamentally important that automation should not create additional workload for experts. In the VIEWAPP approach, the expert's work becomes significantly more convenient and efficient because, during marking, the required part is immediately populated and the final result of the entire claims settlement process is assembled faster.
An important distinction of the approach is that model training is built into the workflow. The expert is not doing additional work but performing a specific action that results in a calculation. The marking results then help evaluate recognition accuracy and continuously improve the model.
How to organize the process for different claims settlement channels
VIEWAPP does not limit the application of the solution to a single client scenario. Depending on the insurer's objectives, the inspection can be performed by the client independently, by a field expert, or by a specialist at a remote settlement point.
Self inspection by the client. The policyholder photographs the vehicle and damage in the application. The materials undergo the prescribed checks and are delivered to the claims settlement system, where they can be used for further processing.
Inspection by an expert. The specialist independently records damage, clarifies its characteristics, and generates a more complete set of materials. The results are transmitted to the calculation center along with structured inspection data.
Inspection at a remote settlement point. The client interacts with a specialist who helps organize the recording of damage. At the same time, the digital scenario reduces the volume of subsequent document preparation and data transfer.
For the insurer, this is an opportunity to use a single technological foundation across different service models. The specific client journey, set of checks, and distribution of tasks among participants are determined by the company's business process.
When choosing a channel, the level of protection must also be considered. For example, using an application with a controlled camera and server-side data verification provides different control capabilities than shooting through a browser interface, which may be less secure. Therefore, the implementation option should be selected with regard to information security requirements and the acceptable level of risk.
Economic effect and gradual implementation
The potential effect of the solution consists of several components:
• reduction of time spent on processing photographs and switching between systems;
• reduction in the volume of manual data transfer to the calculation system;
• automation of electronic inspection report preparation;
• reduction of labor costs for repetitive operations;
• gradual increase in the share of claims processed using the neural network;
• the ability to identify suspicious materials earlier and refer them for additional verification.
As part of a pilot project, it is possible to start with a limited scenario, verify the operation of integrations, and determine baseline metrics. Then, as statistics accumulate, evaluate quality dynamics and expand the list of operations that the system performs without human involvement or with minimal involvement. This approach allows automation to be developed incrementally while maintaining control over settlement quality and without disrupting the insurer's existing processes.
Frequently asked questions from insurers about claims settlement with VIEWAPP
Can VIEWAPP be embedded into an insurance company's mobile application?
Yes. The platform provides integration capabilities that allow the solution to be used within the insurer's existing digital infrastructure. The specific scheme depends on the application architecture and data protection requirements.
Who should perform the inspection: the client or an expert?
Both options are possible. The client can independently record damage, and the expert can conduct the inspection and clarify the necessary information. The choice depends on the nature of the claim, the quality requirements for materials, and the accepted settlement model.
How can we be sure that the client has not substituted the photographs?
VIEWAPP uses the application's own camera, file checksums, and server-side verification of their correspondence. Additionally, the system analyzes metadata and signs of possible manipulation. At the same time, absolute impossibility of substitution cannot be guaranteed: the task of anti-fraud is to identify analyzable signs of interference and help the insurer assess the authenticity of materials.
How is geolocation verified? Are GPS coordinates sufficient?
Coordinates alone are not sufficient. The system analyzes metadata and signs of anomalies in geolocation data, including movement patterns along the route. This approach helps identify situations where the declared inspection location may not correspond to the actual circumstances of the shooting.
What happens if the system detects an anomaly?
An anomaly serves as a signal for verification. For example, signs of screen photography may also occur during good-faith recording of odometer readings. Therefore, the decision on further processing must take into account the context, the nature of the signal, and the results of verification by a specialist.
Can the solution be used with an existing calculation system?
VIEWAPP is ready to integrate with various calculation systems provided the necessary technical capabilities exist and integration is agreed with their vendors. If direct connection is not possible, alternative interaction options can be considered, including through the insurer's existing integration bus.
What should be done if the required vehicle make or model is not in the catalog?
This issue must be addressed at the level of the selected calculation system. VIEWAPP can organize integration, but the availability and currency of catalogs are determined by the capabilities of the calculation system and its vendor. Therefore, support for specific makes and models should be verified before launching the relevant scenario.
How accurately does the neural network recognize damage?
Accuracy depends on the type of damage, the quality of photographs, vehicle characteristics, and the accumulated training data. The AI damage recognition model must be improved on real materials until the required accuracy is achieved. To assess readiness for industrial application, measurements on a representative sample and verification of results by specialists are necessary – these are achievable goals within a horizon of six months to a year.
Is it possible to completely eliminate the expert?
Not for all scenarios. At the current stage, the expert remains an important part of the process: they verify recognition results, clarify damage, and adjust repair operations. As data accumulates and quality is confirmed, the share of operations performed automatically can be increased, but the decision on the acceptable level of automation must be based on testing results.
How are low-quality photographs and documents handled?
If the quality of materials does not allow confident interpretation of the image, additional verification is necessary. Depending on the situation, this may be a manual review by an expert or sending for a repeat of that part of the inspection.
Is it necessary to transfer personal data for training the neural network?
For training the damage recognition model, personal data is not a necessary purpose. However, the specific composition of data transmitted and stored, the procedure for its processing, and information security requirements must be determined within the agreed interaction scheme with the insurer.
How long does implementation take?
The timeline depends on the selected scenario, the availability of integration interfaces, information security requirements, and the readiness of the business process. In practice, it is reasonable to start with agreeing on a specific scenario, connecting the necessary systems, and verifying results on a limited volume of materials. After that, a decision on scaling can be made.
How can the economic effect be assessed before full-scale implementation?
To do this, it is necessary to compare the new process with the current one across several metrics: processing time per claim, expert labor costs, the share of repeat verifications, processing cost, and the percentage of operations performed automatically. This approach allows evaluating not an individual technology but the actual result for the insurance company.
Digital claims settlement as a unified process
Effective automation of claims settlement requires coordinated operation of several components. VIEWAPP helps collect and verify inspection materials, link photographs with damage classification, and transmit prepared information to the calculation system. The neural network gradually expands automation capabilities, while the expert controls the quality of results and adjusts the system's decisions.
For the insurer, this is an opportunity to improve the client journey, reduce processing labor intensity, and progressively move toward a higher degree of automation.