Introduction 

In our current climate the impact of Artificial Intelligence (AI) on the insurance industry cannot be ignored. There is a constant competition within the insurance sector to be in the forefront of technology and to do things better, more quickly, and efficiently. Customers are also expecting optimal returns for their insurance premiums. AI technology helps insurance companies in achieving this. In an article titled Ignoring AI Is Risky Business for Insurance Chief Executive Officers (CEOs) by Iman Karimi, Charles-Antoine Wallaert, Silvo Palumbo, and Rae Chen dated May 13, 2022 states, AI in the health care market was at $8 billion in 2020 and is expected to reach $194 billion by 2030.” The use of data analytics is a big part of the insurance industry in its ability to inform underwriting decisions, process claims and to also help prevent fraud. AI has made many processes in insurance run more seamlessly and with more efficiency and at a quicker pace. Together with AI comes the concern of the complexity and potential lack of explainability of AI algorithms, the risk of bias and the ethical considerations of AI driven insurance. Insurance companies have the challenge to ensure that whilst they embrace the benefits of AI to the insurance sector to also carefully manage and to have controls in place to ensure that insurance companies continue to maintain a high standard of ethics.  

Benefits of AI 

There are various benefits to both the consumers and insurers with regards to the use of AI in the insurance sector. Insurance companies with the use of big data can better understand and assess risks of their customers and have more personalised offerings that better suit their clients. With the use of telematics in vehicles insurance companies are able to also have a clear indication of the driving behaviour of their clients and be aware of the risk in insuring their clients according to their driving behaviour and be able to improve the pricing of their offerings for their clients to better suit the insurance company. The use of natural language processing, voice recognition and chatbots enhances the customer experience. AI allows for claims to be processed more quickly and efficiently. Underwriting and claims processing is also improved with the use of robotic process automation and optical character recognition. Do you have the right system in place for your business to be able to assess risks pertaining to your customers using the advantage of access to real-time data? 

Challenges with AI 

AI allows for insurance companies to better manage their risk and that could impact the affordability and availability of insurance to segments of their customers. However, the Customer Protection Code ensures that decisions made by insurance companies must be of benefit to their customers. According to KPMG’s article on Insurance and Artificial Intelligence-The benefits and ethical considerations by Jean Rea, dated 10th May 2023, the following was mentioned, “Other challenges relate to the complexity and potential lack of transparency or explainability of AI algorithms, in particular where the use cases could have a material impact on consumer outcomes or insurers themselves. In such cases heightened governance and oversight of algorithms can be helpful to mitigate those challenges.” 

ISB Optimus can assist companies in their AI application choices to ensure that the systems used helps companies to overcome the challenge of maintaining a high standard of ethics whilst taking advantage of AI products suitable to the insurance industries. Whilst many AI development companies ignored the importance of maintaining a high level of ethics in their products there is a company that kept ethics in mind when developing their products. ISB Optimus can help you take advantage of AI whilst protecting the important personal information of your clients. 

Possible Oracle Product: Generative AI empowers your business to automate tasks and unlock productivity while maintaining high data privacy and security. Transform your business with generative AI and unlock a new era of productivity with task automation and end-to-end AI solutions for enterprise customers. 

Oracle has an IFRS (International Financial Reporting Standards) 17 solution that is built on Oracle’s integrated risk and financial architecture. The solution provides out-of-a-box capabilities for data and Contractual Service Margin (CSM) calculations. It also seamlessly integrates with finance and actuarial applications which enables for a single platform for accounting, performance management, risk management and reporting. 

AI and Ethical Considerations 

The South African constitution outlines values and principles that guide the public administration contained in Section 195 of the Constitution, as follows:  

“a) A high standard of professional ethics must be promoted and maintained;  

 b) Efficient, economic, and effective use of resources must be promoted. “

Companies are advised to ensure that AI Policies are in place to protect digital and data security. Veldhuizen of Gillan & Veldhuizen inc. law firm in their News article dated 03/07/2023 advises that to mitigate these risks, “businesses to include specific clauses in their AI policies, such as rules governing data ownership and confidentiality over sensitive information as well as vendor and third-party liability guidelines. The latter should outline responsibilities regarding data protection, security, and compliance with relevant regulations. Veldhuizen also mentions the importance of contracts including clauses that hold vendors accountable in case of data breaches or AI-related incidents.” 

ISB Optimus can introduce you to products where data for inferencing and fine-tuning is never shared with large language model providers and are committed to keeping your customers’ data private. Also, with generative AI prevalent across cloud applications, industry applications, and database portfolio, you can take advantage of the latest innovations within existing business processes.  

Possible solution: Oracle’s Cloud Infrastructure’s (OCI’s) generative AI service will allow customers to have complete control and ownership of their data. In addition, unlike other generative AI offerings, Oracle’s generative AI services will not mix customer data. As a result, a given business’ competitive advantage will always remain its own. Tools for accessing data provenance and lineage will be available as well. 

AI and Bias Risk 

Due to AI being reliant on data to build the parameters to business models, bias can be inherent in AI. Bias can be introduced during various phases of the development of the model. According to KPMG’s article on Insurance and Artificial Intelligence-The benefits and ethical considerations by Jean Rea, dated 10th May 2023, the following was mentioned, “for example the data on which models are built and trained may not be representative of the intended purpose of the model and hence be biased, the variables used in the model or complex combinations of them inherent in the model could be closely linked to discriminating factors (known as proxy bias) and biases of the model developers could get reflected in the model design and build.” 

AI faces some additional challenges in this space due to the complexity and opacity of the algorithms, which can make the results less transparent and explainable and hence making it more difficult to detect potential sources of bias. 

The risk associated with bias will depend on the materiality of the use case and impact it could have on consumer outcomes or the insurer itself. For example, using AI to automate back-office operations is likely to have a lower impact than the use of advanced analytical approaches to set premiums for customers. 

A solution to avoid risk of being bias to clients is for insurance companies to ensure that fairness is monitored, and that data is used for its intended purposes. AI algorithms must be created and implemented in such a way that they are fair to all clients and not propagate bias or discrimination. 

ISB Optimus can help insurance companies ensure that their company policies cater for an unbiased platform and have policies, processes, rules, and regulations that are equal and fair to all clients. 

Possible: Oracle Policy Automation enables organizations in all industries to automate service processes, policies, rules, and regulations to provide superior customer experiences across all channels, through interactive self-service advice, guided agent interviews, and offline surveys and assessments. Oracle Policy Automation includes a management console for tracking, sharing, and deploying policy versions, and for configuring user permissions and connections.

AI Privacy Protection Challenges 

AI technologies did not have privacy as one of their main criteria which has resulted in privacy protection challenges. According to an article by Guy Pearce of ISACA (Information Systems Audit & Control Association) published on the 30th of January 2023, he mentioned the privacy challenges with regards to AI technologies include the following: 

  • Data persistence – data existing longer than the human subjects that created it, driven by low data storage costs. 
  • Data repurposing – data being used beyond their originally imagined purpose. 
  • Data spillovers – data collected on people who are not the target of data collection. 

Data collected by means of AI also raises privacy issues like informed consent freely given, being able to opt out, limiting data collection, describing the nature of AI processing, and even being able to delete data on request.

According to McKinsey’s 2022 Global Survey on AI, only 51% of organisations are working to mitigate AI-related cybersecurity risks. From McKinsey’s survey it is evident that a large percentage of companies need to get onboard with improving their cybersecurity risks. 

Ways to overcome AI Privacy Protection Challenges 

Hafiz Sheikh Adnan Ahmed of ISACA (Information Systems Audit & Control Association) in his article Challenges of AI and Data Privacy – And how to Solve Them, dated 6 October 2021, shares solutions and recommendations in overcoming AI Privacy Protection Challenges. He suggests the following 2 requirements that are especially relevant for organizations using AI: 

  • Privacy by design The data controller should build privacy protection into systems and ensure that data protection is safeguarded in the system’s standard settings. The tenets of privacy by design require that data protection be given due consideration in all stages of system development, in routines and in daily use. Standard settings should be as protective of privacy as possible and data protection features should be embedded at the design stage. 
  • Data Protection Impact Assessment — Anyone processing personal data has a duty to assess the risk involved. If an enterprise believes that a planned process is likely to pose a high risk to natural persons’ rights and freedoms, it has a duty to conduct a Data Protection Impact Assessment (DPIA). Moreover, there is a requirement to assess the impact on personal privacy by systematically and extensively considering all personal details in cases where these data are used in automated decision-making or when special categories of personal data (i.e., sensitive personal data) are used on a large scale. The systematic and large-scale monitoring of public areas also requires documentation showing that a DPIA has been conducted.” 

Experts in the field suggest the following considerations when purchasing and implementing an AI-based system for your business: 

  • Ensure that the desired system you want to purchase and implement satisfies the requirements to maintain privacy of your data and that it protects the rights of your stakeholders, users, and customers. 
  • Ensure that a risk assessment is done before you purchase a system, and you may choose to do a complete Data Protection Impact Assessment (DPIA). 
  • It would also be good to establish industry norms and ethical guidelines with guidance from experts in the field of technology. 
  • It is also important to assess the system you choose to implement on a regular basis to ensure that it is aligned to regulatory compliances. 
Conclusion 

As one embraces AI technology to enhance their business processes, there is a great concern of protecting customer and company data. The securing of your company’s data is a top priority of executives and needs to be managed well.  

Possible product solution: 

ISB Optimus can help you protect your data with their Database Security offering from Oracle. Oracle Database helps reduce the risk of a data breach and simplifies regulatory compliance with security solutions for encryption and key management, granular access controls, flexible data masking, comprehensive activity monitoring, and sophisticated auditing capabilities. 

How can ISB Optimus (Pty) Ltd. help get your Business Aligned with AI technology? 

With ISB Optimus, you gain more than just having an AI system in place —you gain a strategic partner committed to helping your company stay at the forefront of technology and best practices in the industry. Please contact us to resolve your challenges in implementing AI technology as you strive to enhance your business.

Author
Synthie Enoch, Content Administrator

ISB Optimus is a specialised business process management services & professional services firm. This encompasses solutions such as Robotic Process Automation, cloud integration software & iPaaS technology.

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