The insurance industry is driving digitization forward. There are four important reasons for increasing the use of this technology.
Unlike other industries, the insurance industry has been hesitant to use the cloud in the past. Cloud software was used for areas such as CRM (Customer Relationship Management), accounting, or financial accounting, but not for the core processes of an insurance company. Cloud solutions were only used sporadically for life, pension, health, and property insurance. But here, too, a reversal of the trend can be seen. In the USA, for example, the majority of all new insurance solutions are already operated in the cloud. European insurers will also increasingly have to go this route—four key factors driving cloud adoption in the insurance industry.
Intense competitive pressures force insurers to develop and deliver new products and services rapidly. The ideal basis for this is cloud platforms and technologies that enable high business agility and flexibility. Insurers also benefit from the scalability of the cloud since their business often develops dynamically – combined with a change in the load profiles after the initial dimensioning. In addition, IT is not necessarily one of the core competencies of insurers. Their relocation to the cloud gives them the freedom to concentrate on their actual business areas.
Insurance Industry: Optimal Use Of Data
A fundamental problem for most insurance companies is that, according to Fadata’s experience, around 80 percent of all data lies unused on servers. Comprehensive data exploitation would also enable insurers to develop and offer new products and services. The prerequisite for this is big data analytics applications. Due to the complexity and volume of data, there is practically no way around using cloud resources when it comes to big data – concerning storage, databases, or analysis functions.
In addition, big data analytics supports the intelligent use of in-house insurance data and analysis and their linking and refinement with general information on demographics or external trends. On this basis, an insurer can carry out descriptive, predictive, and also prescriptive analyzes that can be used for individual customer contact.
Use Of Machine Learning
ML (Machine Learning) will play an increasingly important role in the insurance industry. With the help of ML, offers can be optimized for customers, cases of fraud can be detected, claims accuracy can be improved, and ultimately employee productivity can be increased. In addition, ML contributes to increased customer satisfaction through faster processing of applications and damage reports. ML technologies will thus be increasingly integrated into core insurance systems, as they enable better decisions in complex, time-sensitive environments and support critical insurance business processes securely and with a high degree of automation.
One challenge is that ML models require ongoing maintenance once they go live. For a company, this means a considerable effort. The MLOps approach, which includes ML, software development, and operations, ensures the productive use of ML models. An insurer can also use an on-premise solution for MLOps, but operating an ML framework in the cloud is a good idea due to the complexity.
Insurance Industry: Use Of Digital Ecosystems
Cloud platforms offer companies in the insurance industry the opportunity to use digital ecosystems. This allows them to link their insurance offers with the services and benefits of other service providers – including insurtechs, for example. Such ecosystems make it easier and quicker to address new customer segments. Without the cloud, insurers can integrate innovative technologies via open interfaces and flexibly access data together with partners, and such service extensions are difficult to implement. Additionally, ecosystem usage can be essential for insurance companies to modernize business and drive legacy transformation.