Insurance & Asset Management

Sustainability presents a major challenge for insurance companies: They need new data and data processes to manage their investments and insurance products as well as for sustainability reporting (EU taxonomy, SFDR, CSRD, etc.). We created the target operating model for the IT and data architecture and coordinated it with the stakeholders at group level. This also included the topics of data processes and governance. We created a design for the introduction of the data mesh organizational principle for sustainability data. The project to implement the new sustainability architecture and the selection and introduction of a central sustainability system is underway. With the new architecture, all sustainability management processes will be managed consistently within the company.

The customer's data architecture in finance was characterized by regional legacy systems and was highly fragmented. We have designed and successfully implemented a global standardized data architecture for the client in the Azure Cloud based on data lake and lake house concepts. In addition to the development of an efficient data architecture for Azure including governance, our tasks comprised the implementation of modern digital financial reporting, the development of automated processes and specialized web applications as well as the migration of data from previous legacy systems to the new architecture and infrastructure. The newly invented data landscape for finance leads to globally consistent and high-performance data processes.

The reserving of a reinsurer using traditional methods reaches its limits when there are irregularities in the history or contracts involving clean-cuts. We have designed and implemented a prototype that uses AI to determine the reserve at contract level. An artificial neural network determines the reserve at contract level over a period of 20 years. Aggregation is used to compare the results at LoB level with a determination according to the chain ladder. The neural network is consistently at least as good or even better as traditional approaches. The results are reported in a dashboard with drill-down options by LoB, contract type or region. This provides the customer with a fully automated and intelligent solution for calculating reserves.

To process private health insurance invoices, many insurance companies still rely on manual steps. We have fully automated the process and successfully proved the result with data taken from practice. The invoices are captured by a document AI. The data record is checked for technical and professional errors in a decision engine. Based on this, the reimbursement amount is determined. In the background is a data architecture that efficiently contains all the necessary information. The claim is checked for plausibility before reimbursement is initiated. An AI-based check detects attempts at fraud. The software and document AI used are selected in such a way that they can be adapted to the individual needs of the insurer. As a result, the customer benefits from high-performance invoice processing at lower costs.

In times of digitalization and AI, investors expect efficient, timely and flexible reporting from their asset manager. Despite of this, many companies provide their clients with a selection of static PDF reports only. Additional information required by the client often entails complex and long-term ad-hoc processes. We were commissioned by a large asset manager to design and implement an analytical reporting solution that provides the investor with state-of-the-art business intelligence methods. The technology was based on the SAP BW4/HANA and SAP Analytics Cloud, which enables real-time access to data. The functional responsibility within the company was identified for each field used in reporting. With the new reporting, questions can be clarified quickly already on the user side, which provably reduced the workload in the reporting team and increases customer satisfaction.

The communication process with customers included several manual steps and media gaps. We supported the introduction of the Appian automation platform and the automation of processes and were also responsible for the operation of Appian. As a result, the quality and performance of customer communication has increased significantly, while costs have been provably reduced.

Requirements on asset managers in terms of data and processes are constantly increasing. In addition to the accounting view of the assets under management (Accounting Book of Records, ABOR), a market-oriented investment view of the investments (Investment Book of Records, IBOR) is required for optimal portfolio management. To meet these complementary requirements, Bloomberg AIM was selected as the dedicated front-office system to complement the existing back-office system. We supported two German asset managers in the introduction of Bloomberg AIM/PORT in two independent, multi-year projects and, together with the specialist and IT departments, designed and tested the interfaces and data architecture and developed the business processes. We were also involved in project management and the implementation of investment limits in the system. The standardized interfaces and workflows of the new Bloomberg platform increased the efficiency and scalability of the front office workflows while reducing operational risk. In total, more than EUR 100 billion in assets are managed via the new systems.