Financial and insurance industries across EMEA are known for their organically grown legacy IT infrastructures.
By Patrick Maphopha, technology evangelist and chief technology officer at NetApp Africa
Although South Africa has seen the rise of challenger banks such as Bank Zero and Thymebank that are born in the cloud, most long-standing financial institutions are still trying to manage their data within legacy systems. Their intricate architecture with numerous branch offices and the sheer volume of highly sensitive customer data make fundamental modernisation considerably more difficult. After all, no branch office must be left behind.
At the same time, the volume of online business and the number of enquiries in both sectors is growing exponentially – whether it is online trading, claims or service enquiries. Smartphones and digitalisation are making banks and insurance companies increasingly accessible to customers, even outside business hours.
However, many of these requests are repetitive and require no or little individual response. They are therefore predestined for automated processing: robot-controlled process automation (RPA) is the key phrase here. And according to the NetApp survey, decision-makers in both industries see this as the ideal starting point for integrating AI solutions in their companies.
RPA goes mainstream
The analyst firm Gartner currently value global spending on RPA software at 680 million dollars. By 2022 it could be 2.4 billion. For investments of this magnitude, calling it a mainstream presence seems appropriate. And, according to Gartner, banks and insurance companies are among the leading users of RPA. Above all, the automatisms help reduce the error rate of repetitive tasks, for example in accounting or processing (46,7% of the respondents to the NetApp survey from the financial industry already use AI here).
At the same time, the survey for the financial and insurance industries shows that increasingly intelligent solutions are also gaining traction in more complex areas such as portfolio management (26,7%), customer service (46,7%), and fraud prevention (40%). In the future, AI will also be able to reduce the workload of service and support teams in individual customer care, although it is currently only used in isolated cases. Even in predictive analysis, AI still has considerable potential beyond its current applications.
The cloud as a catalyst
When it comes to infrastructure, the financial sector is particularly cloud-oriented: 86.7% of respondents rely on AI services that draw their computing power from the cloud.
These solutions offer financial institutions the necessary flexibility – reminder: branch offices – and at the same time the necessary performance to process the high data quality and quantity at the required speed. They enable the IT security departments of banks to quickly detect and flag fraudulent transactions. Or support chatbots can recognise the language of the request automatically, thanks to Natural Language Processing and can reply to the customer in their native language.
Cloud architectures such as NetApp Cloud Volume Services pursue a developer-centric approach that is designed to make it as easy as possible to build your own infrastructure through simple connectivity and extensive customising possibilities.
Plan well, implement quickly
Despite the numerous fields of application, the financial sector is one of the pioneers when it comes to the implementation and practical use of AI solutions. At the time of the survey, over 56%of the participants had been pursuing their own strategy for several years and had integrated one or more solutions into their day-to-day operations. The responsibility for the use of AI usually lies with the management, in rare cases with the IT department. 30% of companies even planned the introduction of a dedicated AI department in their company.
In co-operation with external consultants, these departments could then clear up the last remaining reservations about AI. The survey showed respondents were particularly concerned about privacy – understandable given the highly sensitive and personal records their industry works with. Working together with experts can create the necessary know-how for secure data handling and guarantee that only sufficiently secure and certified solutions are used.
The demonstrated will to invest in AI and the high implementation rate of the AI projects show that IT decision makers in finance and insurance recognise the importance of this technology. If they maintain this attitude and remain open to the possibilities of artificial intelligence, they are well-prepared for the future.