Advanced Analytics for the global Investment Management at Munich Re
Creating a real impact with the right tools and processes.
WAY OF WORKING of working
Our proven Implementation approach
Step 1
Understand your business
Collect, understand and connect business requirements of different units. Identify the source systems which hold the relevant information.
Step 2
Integrate the technology
We Setup the technologies in your organization to increase efficiency and reduce non value adding activities to a maximum.
Step 3
Empower your experts
Integrate the system into your processes of value creation and let the central business warehouse drive your decision making and performance management.
Step 4
Make it a system
Improve efficiency and productivity through automated analytics & planning using our smart & centralized decision system.
ABOUT
About mylantech
The world is already complex enough, your digital tools don't have to be, too. Our mission is to decomplexify the world of business with easy to use, human centric solutions. We are convinced that only humans, using with the latest technologies, can create sustainable and optimal profitable value for your business.
The Conclusion
Reduce the complexity!
Complexity reduction is the focus. Clear structures in processes, technologies, and responsibilities enable experts to generate optimal business value. The right tools at the right time and in the right place foster
innovation, comprehensibility, and traceability.
The right tools
Leveraging the right tool and their specific core functionalities, the project is not just able to move and react faster, but also drive innovation with much less friction on all corners.
The right people
It's all about the mindset. Remove dogmas, accept that the world is dynamic and only real business value drives all stakeholders towards a common goal.
The most value
Find a business case with real impact on the organizational success, and people will pout all their energy into this goal. The best projects solve real problems and help experts in their daily job.
Executive Summary
“With mylantech's solution, we have more time for our core task: capital market analyses. We were able to seamlessly transition from 'Excel on the network drive' to the Automated Advanced Analytics world in a very short time. Without sacrificing flexibility or autonomy. On the contrary, the implemented data landscape promotes innovative use cases in the business area.“
Florian Burger & Dr. Martin Blankenburger, Senior Investment Manager Munich Re
Scenario
Munich Re's Tactical Asset Allocation Team aims to analyze heterogeneous data uniformly within the global IT governance framework. (Data sources: Bloomberg, Haver, Ned Davis, and Oxford Economics)
Challenge
The data and analyses must be reliably automated to be available to the right individuals at the right time in the right format, all within the licensing and governance guidelines.
Solution
A modern lakehouse storage serving as a data foundation with overarching processes and clear responsibilities promotes flexibility within business units and establishes an innovative structure that complies with corporate guidelines.
Business Value
Risk mitigation and efficiency improvement through clear processes, technical separation of responsibilities, and qualification of experts to optimally implement use cases with the right tools. Synergies between heterogeneously composed teams and departments are fostered. A Security & Compliance Governance set by the global corporate IT establishes clear guidelines and guardrails for the business unit.
The customer: Munich Re
Munich Re is a globally leading provider of reinsurance, primary insurance, and insurance-related risk solutions. The group comprises the business segments of reinsurance, ERGO (primary insurance), and the asset manager MEAG. Munich Re operates worldwide and is active in all insurance sectors. Since its founding in 1880, Munich Re has been distinguished by unique risk expertise and exceptional financial solidity. Munich Re possesses outstanding innovation capabilities and is able to underwrite extraordinary risks such as rocket launches, renewable energy, or cyber risks.
The challenge
The Tactical Asset Allocation department of Munich RE utilizes a variety of data from providers such as Bloomberg, Haver, Ned Davis, and Oxford Economics for market analyses. This data is supplied in various formats, including databases, CSVs, text files, or through APIs, and are harmonized and transformed using technical tools such as Python, R, Excel, and PowerBI. Centralized and uniformly structured, they serve as the foundation for subsequent analyses and for optimizing the investment process and portfolio for the teams.
For this, the department requires a Data & Intelligence platform that provides the following.
Reliable Data Delivery
Unified, reliable, and risk-free delivery of all data for various use cases; both exploratory and standardized.
Empower the Experts
Comprehensive empowerment of all team members, regardless of their technical background knowledge. Opportunities for experts to further process results with their preferred tools (including the use of Excel) to enable ad hoc analyses.
Compliance & Governance
Adherence to and consideration of all compliance, IT, and IT-security requirements in a highly regulated business sector.
Success Factor 1
The Team
T-shaped teams" are crucial for successful projects as they provide a combination of broad knowledge and deep expertise in a specific field. This multidisciplinary approach promotes effective
communication and enables the efficient implementation of complex projects. Together with the IT units and departments of the corporation, mylantech has implemented a Lakehouse based on Databricks and Azure as the central data platform for the TAA business segment. All data is loaded from source systems, standardized, transformed, and made available to experts for analysis. Governance, centrally managed by the global IT department, monitors compliance with guidelines, while users
access data individually using Excel, Python, R, or Power BI within clearly defined boundaries, allowing for flexible analysis. Our solution allows seamless integration of various data sources,
individual transformations, and effortless sharing of visualizations.
Success Factor 2
The Technology
Custom Python scripts efficiently load data into the corporate Lakehouse in a timely and reliable manner. This data is stored
as .parquet files based on the so-called Medallion Architecture.
On-premises hosted data is loaded via Azure Data Factory using the internal Integration Runtime and is also stored as .parquet in the Data Lake. From there, the data is centrally processed and transformed (including Data Quality Monitoring) using Databricks and made available to use cases as Databricks Delta tables. An established SharePoint connection allows business units to centrally configure pipelines based on Excel. For data visualization, the business units have access to Excel, Databricks Dashboards, Power BI, and R.
Databricks
Provides a unified analytics platform that allows for the processing of massive datasets, facilitating collaboration between data scientists and engineers which is essential for complex data projects.
Azure Data Factory
Enables automated data integration at scale, important for constructing reliable data pipelines that can feed analytical models and reporting systems.
Python, SQL & R
Versatile programming languages known for its ease of use and powerful libraries in data analysis, crucial for building flexible and effective data-driven solutions.
Azure Datalake
Offers scalable data storage that supports big data analytics, important for organizations looking to manage vast amounts of data efficiently while enabling advanced analytics.
Sharepoint
Facilitates collaboration and information sharing across an organization, crucial for maintaining data integrity and promoting a culture of data-driven decision making.
Power BI & Excel
Provides robust data visualization and business intelligence capabilities, essential for transforming data into actionable insights and enhancing decision-making processes.