The insurance sector is currently undergoing a profound transformation The emergence of new risks (climate change, Internet risks and pandemics) along with rising interest rates has led to the emergence of a new generation of insurance companies. In a highly competitive context, the risks of client protection and non-compliance are heightened in an environment of full regulatory inflation (Pacte Law/Eckert Law/RGPD/IFRS 17/KYC, LCB-FT: Directive V/SAPIN 2/DDA/CSR…). Here, AI can facilitate regulatory compliance and especially fraud detection. In order to gain a competitive advantage, AI projects can be generalized to pricing, customer experience, and coverage customization. Finally, we must not neglect the potential time savings in claims settlement. For our part, we will focus on the actuary profession 4.0.
Since the Covid pandemic, new risks and digitization have fueled the transformation of the sector and accelerated the transformation of some professions. The health crisis has certainly accelerated the digitization of all sectors of the economy and innovations in the field of artificial intelligence. The insurance sector is no exception. A number of challenges have arisen from this crisis, to which AI provides an appropriate response. In this regard we see for example the development of insurance for use (its acceleration), on demand, behavioral, standard … We also see the development of integration of connected objects to prevent and evaluate claims, improve customer experience, data, automation, dematerialization (simplification, speed, instantaneousness, transparency). Artificial intelligence around cybercrime is also enhanced with well integrated CISO (Manager of Information Systems Security). The insurance company is also becoming more and more of the insurance company that “accompanies” life’s moments, thanks in particular to insurance companies. The ecosystem movement as a whole is gaining momentum. To this should be added the important role of open insurance, with information systems open via APIs (Application Programming Interface) to create open, interoperable platforms and development of partner ecosystems. With RPA technology, There is also acceleration in the automation of high-volume, low-value tasks. In the field of continuous improvement, optimization and digitization of processes and tactical deployment of robotic process automation solutions are essential. We also see the development of the use of voice and applications with extended virtual reality to improve customer experience as well as amplify the development of services with connected objects for the prevention and evaluation of claims, in particular, the massive integration of the blockchain (products and services, fraud, compensation, etc.). All of these aspects have particularly accelerated since 2020. Here we will focus on the profession of actuaries.
In the field of insurance, we will, in particular, decode a profession: actuaries. Thanks to AI, actuaries will have access to better data visualizations, for example using business intelligence tools as well. Business intelligence tools will change and accelerate the way actuaries diagnose and understand results and communicate information to stakeholders.
Graphical data allows them to present the results of complex analyzes to audiences unfamiliar with actuarial techniques. Data visualization also provides the ability to detect trends in an environment where the amount of information increases exponentially. In the field of machine learning (ML)/IA, with data organization and use via R and Python, it is used in pricing and underwriting to perform experience studies, predict policyholder behavior and calculate provisions. When it comes to Low – Code ETL & Low Code Programming, for example Alteryx, Azure Data Factory, these tools will come in handy when traditional ETL tools that require IT support are not sufficient for business needs (for example, it is difficult for users to learn quickly ) or when the IT department is not able to provide the data fast enough. We can also make cloud computing and storage more efficient. For example, Microsoft Azur or Amazone Web Services. Several factors lie at the root of this increased use: the need for flexibility, efficiency gains, and increased computing and storage power. Therefore, cloud technology allows actuaries to access virtual machines in a cost-effective and efficient manner by significantly reducing execution times.
So how will the actuary be enriched by the uses currently under development? As far as unstructured data is concerned, via R and Python as mentioned earlier, the use cases are more focused on R&D, analytics, pricing, underwriting, and product development than the use cases on structured data. Also for ML/IA Documentation Generator As the use of R/Python becomes more prolific among actuaries, the ability to simultaneously generate documentation and reports for applications and processes being developed will gain importance. Finally, when it comes to data management, for example Collibra, companies see this technology as providing significant value to actuaries. The increased use of data, particularly in ML/AI applications, will require companies to be more involved in preventing and managing risks of data misuse and its evolution over time, and this can be achieved through the use of governance tools. Here, APIs, where real-time ML/AI models need to be deployed for downstream applications, are likely to gain importance.
Finally, we must add strong capabilities in two areas:
- Robotic Process Automation (RPA):
Direct use of RPA by actuaries is very limited due to other types of automation already in place or because IT implements RPA without the actuaries actually using it. However, if several different applications are used in a process, RPA can be useful to simplify these applications.
- Data protection management improvement technology:
For example, Privitar – as regulations around data use evolve, these tools could become more useful to actuaries, indirectly, by helping them to use data in a way that is compliant with the regulations. As such, the digital revolution allows for a huge amount of data (big data) that insurance companies must process, store and analyze.
 Robotic process automation