Potentially, artificial intelligence (AI) can reshape the insurance industry. From claims processing and improved application management to delivering on-demand solutions and providing enhanced advisory services, its impact can be far-reaching. But within the opportunities, potential challenges around risk and compliance must be kept in mind.
Most of these challenges centre on how the insurer manages the data at its disposal – specifically what systems are accessing the data, to what end, and which users can leverage those insights for claims and underwriting procedures.
Legal matters
According to Webber Wentzel, AI systems must account for the requirements of the Protection of Personal Information Act (POPIA). Of specific importance is section 71(1) of POPIA, which governs automated decision-making.
‘This section protects data subjects from being subjected to a decision which is based solely on automated decision-making, which results in legal consequences for the data subject and the data subject being profiled. For instance, an AI system would have the ability to profile customers seeking a bank loan, and determine their creditworthiness based on previous loan repayments, income, indebtedness etc.’
The law firm states that the section prohibits a financial services provider to approve or reject an application solely based on the profile created by the AI system. Insurers therefore cannot leave the decisioning process entirely up to technology to manage, regardless of how the algorithms are designed.
Initial stages
Of course, all this might seem challenging to manage. But it is within difficulties such as these where the greatest opportunities can be unlocked. In many countries where General Data Protection Regulation (GDPR) is adopted, there is a constant evolution of the regulation on AI usage across several sectors, financial services being just one. This is vital to introduce accountability into the process and prevent the potential for abuse and misuse.
In doing so, consumer confidence in the usage of AI in insurance will increase. Insurers will also better manage the complexities of the regulatory environment as they know exactly what is required from an implementation perspective. Even though AI can be considered to be in the preliminary stages when it comes to insurance, this also provides significant impetus to scrutinise the technology and understand the business use cases for incorporating it into existing systems.
For instance, claims management, a labour-intensive process, can become more efficient and effective in terms of decisioning by incorporating elements of automation into the value chain. Leveraging intelligent process automation, neuro-linguistic programming capabilities, and the like, insurers can dramatically streamline something that used to take a significant length of time to complete.
Furthermore, automation and AI can cut down on fraud. Algorithms can be put in place to identify fraudulent claims. This not only saves the insurer money, but also creates a smoother underwriting experience for customers as well.
For our part, SilverBridge has been focused on building intelligent solutions such as Smart Claims and Smart Underwriting to provide a critical balance between machine-driven automation and human knowledge.
No ignoring the potential
When the regulatory environment and its requirements are considered and adopted, an insurer who uses AI to collect, analyse, and embed data-driven insights into its core processes can unlock significant value. Just consider the potential of optimising sales, distribution, pricing, underwriting, and claims management.
Local financial services providers are embracing data-driven solutions to increase engagement with customers while meeting regulatory compliance requirements. An example of using technological innovation and data analysis to provide customers with uniquely tailored products and services to increase engagement are companies that use rewards programmes.
The opportunity is that the more clients engage with technology; the more data is generated to be used in AI processes that help in the generation of analytics that lead to the creation of compelling value propositions for both the insured and insurer. Now is the time for insurers to embrace AI while remaining cognisant of the regulatory environment.
