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Der entscheidende Unterschied liegt darin, wie Versicherungen den Betrieb und IT optimieren können. Dies ist mehr als nur ein strategischer Produktionsfaktor.
Philip Franck, Partner
Challenges
Digitalization and new expectations force insurance companies to systematically focus on customers
Insurance companies are faced with various challenges. Digitalization is a major driver as it forces the development of new products, customer interfaces and processes. The winners will be those that rethink and redesign fastest.
Digitalization and new expectations force insurance companies to optimize their processes and to systematically consider them from the customer’s point of view. Customer centricity now means that insurance providers need to develop new products and customer interfaces. At the same time, they need to push the digitalization of their internal processes and boost quality and efficiency.
Established insurance companies struggle with the inflexibility of inefficient and error-prone legacy IT systems. After all, only the companies that can respond to changes with innovative and distinct products and services faster than their competitors will win the battle for customers at the digital interface.
Nur 10 % geben an, insgesamt über eine flexible IT-Architektur zu verfügen. Und sogar nur 7 % geben an, externe Services und Kooperationspartner insgesamt leicht anbinden zu können.
Insights
Established insurance companies must adapt historically grown structures and IT systems to the new requirements. Modern, digital service units do not go very well with traditional operating models that are often strictly organized into divisions. New digital technologies rely on flexibility and modularity and demand wide-ranging communication and processing channels. IT is already more than just a strategic production factor. IT helps insurance companies to develop new business models and product offers. This makes it the critical difference among competitors.
Too many traditional insurance companies still rely on their own in-house IT department. Only few companies use the data center services of third-party providers. Most miss out on the chance to save costs and increase IT security. Too many established insurance companies do not recognize the value of the mountains of data that they possess. Only some institutions professionally analyze their own data and enrich it with data from external sources, thereby creating valuable big data pools. Insurance companies need a data science strategy as the foundation of new data-driven ways of working and all follow-on 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.
