# Blockchain-Driven Generalization of Policy Management for Multiproduct Insurance Companies
## 5 Solution Implementation
### Solution Validation  
It is important to highlight that the solution developed and evaluated in this article is a functional prototype, designed to demonstrate the feasibility and benefits of the proposed architecture in a controlled environment.  
During the validation phase of the implemented prototype, a series of tests were conducted to confirm the inherent benefits of using Blockchain in multipolicy management. These tests demonstrate the unification of processes, allowing internal operations and interactions between external companies to be carried out more smoothly and coherently. Additionally, the elimination of data duplication in relationships between network participants becomes evident, reinforcing the integrity and consistency of the managed information. Thanks to the implemented model, operational efficiency is optimized, and data consistency across the network is ensured, aligning with the standardization and security objectives that are fundamental to the proposed architecture.  
In relation to the standardized policy model, Merkle trees have proven to be an effective tool for managing and expanding the insurance catalog with agility. A practical case was conducted where tests were performed on an initial set of home, auto, and health insurance policies. The inclusion of a new type was proposed: Personal Digital Assets Insurance Policy. The result was a direct integration of the new policy type: it was added as an eligible option in the decentralized user application, and when creating a policy of this new type, a Merkle tree representing the dataset was generated, the hash calculations were performed as previously described, and the data was inserted into the Blockchain network.  
The entire process was completed without modifying pre-existing policies and without any disruptions. This process demonstrated the ease with which the architecture allows new types of insurance to be added, ensuring the system's flexibility and scalability.  
A preliminary analysis of the performance of the proposed prototype has been conducted. The migration of data to the blockchain system is a process that occurs only once, during the initial deployment, and it is estimated that the migration times are negligible in relation to the volume of data and the required infrastructure. Additionally, the operational capacity of the machines used in production environments must be considered.  
Figure 18: DAPP Design.  
Finally, we conducted an empirical analysis of the most frequent operation in this system: data search. From the analysis, we obtained the following results:  
With 500 simulated policies, we have the following results:  
Performing a linear search operation requires an average of 250 operations. This is because, under these conditions, approximately half of the elements are reviewed on average. As the data increases, the search time increases linearly.  
Using a binary search through Merkle trees, we found that the search takes log2 (number of policies), which, applied to the case study of 500 records, results in an average of 9 operations per search. It is important to note that the search time will increase much more slowly as the number of records grows.  
Although the times with the two systems are not significant for the development of operations in the company, on average the use of Merkel trees improves the search by about 50%, having considered the search in all possible positions of the chain.  
Although these operations were tested solely using the prototype developed for the proof of concept, we can conclude that this improvement is key to optimizing the system's efficiency, especially as the volume of managed policies increases so in number as in types of policies. For a comprehensive study, including real metrics, it is necessary to consider real-world conditions such as software, hardware, operational time windows, workload, etc.