In this piece, JOSEPH INOKOTONG identifies some of the strategies the insurance industry should focus on to balance the innovative potential of Artificial Intelligence (AI) with responsible management, ensuring its benefits are realised without compromising trust or fairness.
The insurance industry is almost on the verge of a seismic, tech-driven shift, with vital input from Artificial Intelligence (AI) which requires astute management to stay on course and avoid negative disruption.
The disruptive roles of AI in the insurance industry can be managed by adopting a strategic and ethical approach like developing clear regulations and policies. This calls for regulatory frameworks, establishing robust AI-specific regulations to ensure transparency, fairness, and accountability in AI-driven processes like underwriting, claims management and fraud detection. There is the need to create ethical guidelines to address bias, data privacy and decision-making autonomy.
Investment in human-AI collaboration is needed to upskill the workforce by training employees to work alongside AI tools, enhancing their ability to interpret and apply AI insights effectively. Human oversight: Ensure human involvement in critical decision-making processes to maintain a balance between automation and human judgment.
Data security and privacy must be prioritized through robust cybersecurity measures by implementing strong cybersecurity protocols to protect sensitive customer data.
Compliance with privacy laws is important by adherence to data protection regulations such as GDPR, HIPAA, or regional equivalents.
Transparency should be ensured. Explainable AI: The usage of AI systems that provide clear, understandable explanations for decisions, especially for customers affected by these decisions, cannot be overstressed. Audit Trails: Maintain detailed logs of AI-driven processes for accountability and auditing purposes. Mitigate bias in AI algorithms. Diverse data sets: Use diverse and representative data to train AI models to minimize inherent biases. Regular Audits: Conduct regular algorithm audits to identify and address biases or errors.
Customer-centric approach should be adopted via enhanced communication. It is imperative to educate customers on how AI is used in policies, claims, and risk assessments. Accessible support: Provide options for human customer support to address AI-related concerns.
Innovation should be fostered with caution. Control experimentation by testing AI solutions in controlled environments before full-scale implementation. Collaborative ecosystems: Partner with technology firms, regulators, and other insurers to share best practices and insights.
Proactive risk management – Scenario planning entails simulating AI-related risks and preparing mitigation strategies. Insurance for AI risks means that policies should be developed to cover liabilities arising from AI failures or misuse.
Ethical leadership should be emphasized by establishing Board-Level AI committees to focus on overseeing AI strategies and ethical concerns. Stakeholder engagement: Involve stakeholders, including customers and employees, in discussions about AI integration and its implications.
By focusing on these strategies, the insurance industry can balance the innovative potential of AI with responsible management, ensuring its benefits are realized without compromising trust or fairness.
Today, the term AI describes a wide range of technologies that power many of the services and goods used every day – from apps that recommend TV shows to chatbots that provide customer support in real time.
Although the term is commonly used to describe a range of different technologies in use today, many disagree on whether these constitute artificial intelligence. Instead, some argue that much of the technology used in the real world today constitutes highly advanced machine learning that is simply a first step towards true artificial intelligence, or “general artificial intelligence” (GAI).
Yet, despite the many philosophical disagreements over whether “true” intelligent machines exist, when most people use the term AI today, they are referring to a suite of machine learning-powered technologies, such as Chat GPT or computer vision, that enable machines to perform tasks that previously only humans can do like generating written content, steering a car, or analysing data.
In many ways, Artificial intelligence (AI) can help the insurance industry grow.
This can be achieved by automating insurance underwriting and claims processing, making the process faster, more accurate, and less labour-intensive. By providing personalised insurance products and services, and using data analytics to understand customer needs and preferences, AI can enhance the growth of the industry.
Other ways AI can be of assistance to the insurance industry include preventing fraud by analysing customer data to identify suspicious activity, enhancing customer service through chatbots and other AI-based customer service tools, and developing new insurance products, such as usage-based insurance that charges premiums based on actual driving patterns. Another way that AI can help the insurance industry is through predictive analytics where it can be used to analyse vast amounts of data to predict future trends, allowing insurance companies to make more informed decisions about pricing, underwriting, and risk management.
In risk assessment, AI can be used to evaluate risks more accurately, helping insurance companies to better price policies and reduce losses. While in loss prevention, AI can be used to detect potential risks and recommend loss prevention measures, such as alerts for potential weather damage.
The notion that the deployment of AI in the insurance industry would displace human workers is an important concern. AI does have the potential to automate some tasks that humans currently perform in the insurance industry, which could lead to job displacement. However, it is important to remember that AI is not a replacement for human workers, but rather a tool that can be used to enhance their capabilities.
Some insurance industry roles that may be affected by AI include claims adjusters and underwriters risk analysts. However, AI is unlikely to completely replace human workers in these roles as human judgment, empathy, and problem-solving skills will still be needed to handle complex or unusual situations.
A lot can be done to remedy this situation. There are a few strategies that can be implemented to help remedy potential job displacement due to the deployment of AI in the insurance industry. Retraining and upskilling should be seriously considered. Insurance companies can invest in retraining and upskilling programmes for their employees, helping them to develop new skills and adapt to changes in the industry. New job creation would be obvious as AI will create new job opportunities in areas such as data science, AI engineering, and customer service. Insurance companies can help to ensure that their employees are prepared for these new roles.
Experts have highlighted a few more points to consider such as diversity. They submit that AI systems can be trained on biased data, leading to biased decisions. Also, insurance companies should ensure that their AI systems are diverse and inclusive.
Transparency: Insurance companies should be transparent about how their AI systems are being used and the data being collected to ensure that customers and employees understand the implications of AI in the industry. Collaboration: Insurance companies should collaborate with industry groups, academic institutions and policymakers to address the potential challenges of AI deployment and ensure that it is used responsibly.
All the technologies required already exist and many are available to consumers. With the new wave of deep learning techniques, such as convolutional neural networks, artificial intelligence (AI) has the potential to live up to its promise of mimicking the perception, reasoning, learning and problem-solving of the human mind (exhibit 1).
Experts say in this evolution, insurance will shift from its current state of “detect and repair” to “predict and prevent,” transforming every aspect of the industry in the process. The pace of change will also accelerate as brokers, consumers, financial intermediaries, insurers and suppliers become more adept at using advanced technologies to enhance decision-making and productivity, lower costs and optimise the customer experience.
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