InsurTech

Change is the only constant of life which means that insurance also has to develop. In recent years the scale of possible risks, business dynamics, and preferences of customers have drastically changed which has been caused also by macroeconomics trends. The covid-19 pandemic has shifted the focus to technological, system, and product gaps of insurance and InsurTech companies.

They are forced to digitalize to improve their operational effectiveness. The unpredictability of further development is pushing them towards restructuralization of their processes and products


FinTech Roadmap

For every area of FinTech, we create a strategic table in which we identify incoming trends, key factors, challenges, and comparison of the state in the Czech Republic to other countries to provide companies an overview on how to implement the newest technologies.

 

Incoming trends Key factors Challenges Comparison to other countries
The BigTech and non-traditional players are entering the insurance market Higher customer experience, competitive area Traditional companies will have to reach the same level of customer experience as BigTechs, possible regulations of BigTech It’s gradually beginning to appear also in CR
Digitalization of services Customers demand around the clock availability of services via many communication channels Taking advantage of the opportunity and investing in insurance comparison websites, providing quality information on their websites It’s in an active process in CR. An example is the Mutumutu platform
The emergence of AI  in insurance Business models innovation, risk modeling, better customer service, many other use cases Companies should have a precise strategy on how to implement AI It’s gradually beginning to appear also in CR
Insurance companies are starting to use real-time data Data are becoming a more and more important commodity, availability of new data streams, process automatization, better predictive analysis BigTech have adopted AI more widely It’s gradually beginning to appear also in CR
Image recognition Higher effectivity, many use cases such as verifying the identity, interactive marketing, insurance claims estimations The technology may not be precise enough for some use cases, there may be not enough training data for some models It’s gradually beginning to appear also in CR