The insurance industry, according to experts, is on the verge of a seismic, tech-driven shift. A focus on pertinent areas can position stakeholders to embrace this change. JOSEPH INOKOTONG reports.
Artificial Intelligence (AI) refers to computer systems capable of performing complex tasks that historically only a human could do, such as reasoning, making decisions, solving problems, recognising speech, making decisions and identifying patterns.
AI is an umbrella term that encompasses a wide variety of technologies, including machine learning, deep learning and natural language processing.
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.
The insurance industry, according to experts, is on the verge of a seismic, tech-driven shift, and a focus on pertinent areas can position stakeholders to embrace this change. In the future of insurance, as seen through the eyes of Uche, a customer in the hypothetical year 2030, his digital personal assistant orders him a vehicle with self-driving capabilities for a meeting across town. Upon hopping into the arriving car, Uche decides he wants to drive and moves the car into “active” mode. Uche’s assistant maps out a potential route and shares it with his mobility insurer, which immediately responds with an alternate route that has a much lower likelihood of accidents and auto damage as well as the calculated adjustment to his monthly premium.
Uche’s assistant notifies him that his mobility insurance premium will increase by four to eight percent based on the route he selects and the volume and distribution of other cars on the road. It also alerts him that his life insurance policy, which is now priced on a “pay-as-you-live” basis, will increase by two percent for this quarter. The additional amounts are automatically debited from his bank account.
When Uche pulls into his destination’s parking lot, his car bumps into one of several parking signs. As soon as the car stops moving, its internal diagnostics determine the extent of the damage. His assistant instructs him to take three pictures of the front right bumper area and two of the surroundings. By the time Uche gets back to the driver’s seat, the screen on the dash informs him of the damage, confirms the claim has been approved and reports that a mobile response drone has been dispatched to the lot for inspection. If the vehicle is drivable, it may be directed to the nearest in-network garage for repair after a replacement vehicle arrives.
While this scenario may seem beyond the horizon, such integrated user stories will emerge across all lines of insurance with increasing frequency over the next decade. All the technologies required above 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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