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Rapid business insights with cloud-based data warehouse modernization solutions


BCI Seguros


Financial services


Santiago, Chile

Use Case

Data Analytics


BCI Seguros is the leading general insurance company in Chile and the second-largest in non-pension life insurance. The Spanish group Mutua has recently acquired a majority stake, and in addition to BCI Seguros, the brand includes ZenitSeguros and Auxilia. The company has over 1,000 employees and branches throughout Chile.

Business Challenges

BCI Seguros faced common challenges of modern organizations, including difficulties in synchronizing multiple data sources, unmet critical needs in information analysis, and barriers to on-premises data warehousing infrastructure. Due to limitations in computing power, limited storage, and data processing capacity, business analysis was heavily restricted in generating insights, making decisions, and therefore gaining competitive advantages in the market.

Additionally, the generation of business insights needed to be a fast, agile, and flexible process with support for normal information modifications and response times aligned with the dynamics of the insurance industry. Business information from different sources with large data volumes needed to be analyzed within a limited timeframe. Scalability and availability were critical to enable expert information analysis and adjust product offerings according to relevant market variables.

The following business challenges summarize the previous state:

  • Slow business analytics: Data extraction and processing from transactional databases were manual and slow, limited by the use of local resources and high investment in labor hours.

  • Difficulties in data storage and processing at scale: Reports and analysis relied on OLTP databases, resulting in increased business risks and user limitations. The implementation of an analytical data storage model (OLAP) allowed computing capabilities and users to access data online from different perspectives.

  • Low operational efficiency: The need to reduce operating expenses and IT support costs, which were performed through manual administrative processes such as database backups, copies, restoration, storage management, etc., resulted in high costs for the company.

  • Data strategy misalignment with business needs: The outdated data architecture needed to support the business requirements and facilitate disruption in the industry.


Through the collaboration between BCI Seguros and Arkhotech as strategic partners in achieving business objectives, a cross-functional team was formed to drive business disruption through data.

Arkho employed a cloud-based data ingestion, processing, and consumption strategy with multiple workstreams that will enable the generation of critical business insights in the coming years:

  • Data synchronization from the business to the cloud, with a low impact on productive processes and low response latency.

  • Creation of enterprise data lake structures to accommodate future analytical needs by reusing the same information.

  • Distributed processing for optimal information modeling and data enrichment.

  • Data consumption in existing BI tools already used by the business.


As a result of the project, the business was able to capture business insights needs more efficiently by utilizing large volumes of information and automatically enriching data through transformations. Response times for business queries were optimized by 95% compared to previous times required. Additionally, the created analytics structure enables the business to continue innovating in predictive use cases and driving further disruption in the market.

Moreover, the solution generated various optimizations in data processing:

  1. Online data replication in AWS S3, allowing the creation of a data lake for the company. The use of the Parquet format improves efficiency by 60% and reduces storage space requirements.

  2. The online data replication in AWS S3 enables data reuse for creating temporary test databases, data backups, and running more complex queries for business information. This structure allows for maximum reuse and more complex analytics use cases in the future.

  3. Near-real-time synchronization of the local Oracle database with Redshift, enabling users to perform online queries.

  4. Having a subset of raw data in Redshift has allowed users to decouple from OLTP data sources and eliminate competition for resources in transactional databases, delivering results in less time even with aggregated information.

  5. Data replication metrics serve as a common language for business and IT operations teams.

  6. The creation of alarms and online monitoring has empowered users to shift from reactive to proactive operational models.

  7. Athena allows for fast querying and searching of results with minimal infrastructure requirements.

Overall, these benefits have significantly improved the agility, efficiency, and scalability of data analytics for BCI Seguros, enabling faster and more informed decision-making.

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