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The key difference lies in how insurance companies can optimize operations and IT. This is more than just a strategic production factor.
Philip Franck, Partner
Challenges
Digitalization and new expectations are forcing insurers to consistently focus on the customer
Insurers are struggling with numerous challenges. One key driver is digitalization, which is forcing the development of new products, customer interfaces and processes. The winners will be the companies that rethink and restructure the fastest.
Digitalization and new expectations are forcing insurers to optimize their processes and focus them consistently on the customer. The new customer centricity means that an insurance provider must develop new products and customer interfaces. At the same time, they must drive forward the digitalization of internal processes and increase quality and efficiency.
Established insurers are struggling with the low flexibility of vulnerable and inefficient legacy IT systems. However, only those who are able to react to changes with innovative and differentiating products and services faster than the competition will win the competition for customers at the digital interface.
Only 10% state that they have a flexible IT architecture overall. And only 7% state that they can easily connect external services and cooperation partners.
Insights
Established insurers have to adapt established structures and old IT systems to new requirements. Modern, digital service units are a poor fit for traditional operating models, which are often still characterized by a division-oriented organization. New digital technologies are based on flexibility and modularity and require comprehensive communication and processing channels. IT is now more than just a strategic production factor. IT helps insurers to develop new business models and product offerings. IT is thus becoming a decisive competitive differentiator.
Too many traditional insurers continue to rely on in-house IT. Only a few companies use data center services from third-party providers. Most of them are missing out on the opportunity to save costs and increase IT security. Too many established insurers continue to misjudge the value of the mountains of data they are sitting on. Only a few institutions analyze their own data professionally and enrich it with external sources to create insightful big data series. Insurers need a data science strategy that forms the foundation of the new data-driven work and all further steps.
Solutions & fields of action
Developing future-proof operating models
Based on our many years of experience, we have developed a solution framework that helps us to design a future-proof operating model in collaboration with our clients and to define measures for the transformation.
Guaranteeing operational excellence
We improve digital processes. We combine instruments of traditional process optimization with systematic automation and a greater alignment of processes with a view to customer touchpoints.
Developing IT into a real competitive edge
New business models and offers turn IT into a real competitive edge. They require a new IT strategy, IT architecture and a new IT management. We know the levers for creating faster development cycles for customer-oriented offers, for building flexible and modular IT architectures and making mountains of data available quickly and comprehensively.
Strategically optimizing value-added chains in IT
Insurance companies must evaluate the sourcing potentials of alternative delivery models. This applies to infrastructure operations just as much as to IT applications such as standard software and software as a service (SaaS). To do so, it is necessary to first establish professional service management.
Big Data und eine zukunftsfähige IT-Architektur aufbauen
We help to develop high income potentials by personalizing customer journeys and optimizing processes. This involves selecting big data applications, designing ecosystem concepts in IT, harmonizing and integrating data and developing data science skills.
Data science as a strategic asset
Data science is the systematic application of powerful analytics methods on large volumes of data. Examples include data-supported cross- and up-selling to increase conversion rates in sales, customer churn analyses or optimizing risk models.
Safely following the path into the technological future
Aside from selecting the right applications, migrating from the old world of IT into the new one is the key challenge. We know the diverse requirements from many completed projects and always find the right solutions.
