Globally, insurers are under pressure to find more innovative ways of delivering on customers’ need for more personalised solutions. Low-code and no-code platforms provide insurers with a more flexible and efficient approach to developing data-driven solutions that enable them to create tailored products based on customer data.

Low-code and no-code platforms are powerful tools that simplify and accelerate the application development process. Low-code platforms primarily cater to professional developers and allow them to create applications by visually assembling components with minimal hand-coding.

No-code platforms enable non-technical users to build applications without writing any code at all. These platforms have become increasingly popular due to their ability to shorten development time, reduce costs, and increase agility, thereby freeing up internal specialists to focus on other strategic business functions.

Insurance benefits

In most countries, the insurance landscape is characterised by intense competition, stringent regulatory requirements, and an increasingly demanding customer base. To thrive in this environment, insurers must continuously innovate.

Thanks to low-code and no-code platforms, they have the means to do so far more effectively than before:

• Accelerating time to market: Insurers can quickly develop and deploy new applications, ensuring they can respond to emerging customer needs and market opportunities without delay.
• Enhancing customer experience: By leveraging these platforms, insurers can create personalised, data-driven solutions that cater to the unique preferences and requirements of their customers, leading to increased satisfaction and reduced churn.
• Streamlining regulatory compliance: Low-code/no-code solutions can help insurers automate processes and adhere to regulatory requirements more effectively, reducing the risk of non-compliance and associated penalties.
• Reducing IT costs: By minimising the need for traditional hand-coding and streamlining development processes, low-code and no-code platforms can help insurers reduce their overall IT expenditure.

Business value

From an organisational perspective, the adoption of low-code and no-code solutions can facilitate the development of a more efficient business model. For instance, by giving non-technical employees the means to build and modify applications, the insurer can foster a culture of innovation. Through the democratisation of the application development process, employees can take ownership of finding inventive ways of addressing their role-specific challenges.

The adoption of low-code and no-code platforms is a strategic imperative for insurers regardless of the country in which they are based. By using them to create data-driven solutions and respond faster to customer demands, they gain the agility to respond faster to the rapidly-evolving market demands while delivering more customised solutions.

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.