Impact of AI on the Insurance Sector
Artificial intelligence (AI) is rapidly evolving and impacting the insurance sector in a variety of ways. As AI becomes more sophisticated, it can help insurers detect risks and claims fastest and more accurately.
This could lead to cost savings for insurers and increased customer satisfaction and loyalty. For example, AI can be used to improve customer service, automate processes, and create more accurate predictions.
This article looks at ways in which AI is affecting the insurance industry and discusses the potential benefits and challenges of this technology.
Key Benefits of Using AI in Insurance Sector
1) Streamlined Claim Processing
Processing and claims payment is currently a very manual process. By automating these tasks, insurers will be able to reduce costs that can be better used elsewhere in their business model.
A robot could for example reduce the time it takes to number crunch and assess bills of interest at an insurance agency from five seconds or less on average [by reducing human error].
As many different services come together under one roof, they may need improved interaction with each other and AI can be used to increase data entities in order to achieve this more automation of the research process will also reduce errors that have occurred because of human error before.
2) Fluctuating Demand
This will be helped by AI giving a more accurate prediction of customer behavior and the importance that customers place on certain aspects of their life.
For example, if working for an insurer, 70% of insurance holders do not get any health care assistance from their company because they consider it to be unrelated to work-related issues; whereas insurers estimate only 40%. Similarly, people generally exercise control over as many areas of decision-making (such as their job, home, and health) as they can.
Yet people's choices of products within these three areas often fit together like air molecules in a gas-filled balloon, making it difficult for insurers to make accurate predictions about many customers' decisions because that information is all scattered throughout the various touch points across which change occurs.
For example, changes made on one particular app will not always be picked up by another application as quickly or at all, and these results.
In another example, people may prefer a certain exercise plan depending on their height, weight, and whether they have any medical conditions such as diabetes or asthma.
However, with the majority of these things being self-reported many variable factors are hard to account for in most AI systems: it was developed to pick up this 'anomaly' which is why we can expect there will be an increase in companies using artificial intelligence technology.
3) Fraud Detection and Resolution Services
Automating the process of investigation could mean a reduction in costs, as well as speeding up what is usually an intensive investigation which can take months - even years to complete.
Implementing AI into fraud detection services has many benefits because it enables corporations to perform large-scale scanning at very high speeds, unlike the human brain which can only scan documents at low speeds due to its limited capacity such As such AI can scan through a large amount of documents, emails and videos every day comparing them to each other accordingly.
This in turn enables companies to identify fraud where no human would ever be able to collect all the information related to the incident at hand.
In this way, it is likely that those who attempt fraudulent activities will not have any cover for what they have done if algorithms simulate many possible scenarios which could prove their actions illegal - as fraud has been implemented by a number of big corporations in the past.
4) Predictive Analytics/Analysis
Predictively analyzing large amounts of data enables intelligent systems to better predict customer needs accurately, allowing companies to become more profitable as they will be able to market goods and services which customers want - therefore giving its clients a competitive advantage over their rivals in the race for profit.
In this way, it is likely that customers will be much more satisfied with their services if companies are able to predict and provide them with goods they desire - thus making a huge positive impact on their potential in the future.
Additionally, firms can readily use AI systems like machine-learning algorithms (ML) which facilitate the analysis of large quantities of data stored within databases set up by businesses largely through research centers such as those working at MIT Media.
5) Customer service for Insurance
Since AI makes it easier to analyze customer orders and compare them with possible future scenarios they can be programmed into systems that will identify unsatisfied customers that may require additional assistance.
The result of this is a continuous expansion in the interest consumers have for acquiring services more than their competitors, as companies strive to keep up with technological advancements such as robotics and AI.
Although the AI revolution has been predicted to have many positive impacts on society as a whole - because it makes systems more useful and informative, there are concerns over how its implementation may affect individuals who rely on social impact for their daily lives.
6) Improved Loss Estimation
Additionally, adjustments to customer servicing might be examined. For example, in the event of an insurance claim that requires additional research or verification due to a mistake made by the insurer - AI can enable companies to take appropriate measures prior to and after each potential error occurs such as these may have generated expenses.
Although this style of loss estimation is not 100% accurate there are still benefits to utilizing this technology.
For example, a report by the Academy of Finance demonstrated that geographical dispersal and data independency increase similarity in loss estimates which can be achieved through AI software algorithms.
These lead to widespread efficiency which again may encourage further innovation and development within insurance companies." The benefits of using AI or data based automations can be difficult to access because of the complexities involved in implementing its application.
For example, Ingrid Marsdal presents a view on societal progress and how this might involve future insurance customers.
She states "that insurers themselves may consider building into their services additional information through use of artificial intelligence (AI) algorithms that automate complicated calculations as part of a holistic service offering."
These seemingly simple ideas may provide new opportunities for online insurance companies to access a specific audience of consumers who have been set aside from traditional categories.
Trends that will Impact the future of the Insurance industry
The future vision of the Insurance industry will be impacted by AI technologies, especially those at more advanced stages of development such as tri-modal.
These same techniques can provide digital insurance communities with new opportunities to innovate on traditional market segments in order to reduce losses and improve customer experience." Trends that may evolve within the Insurance Industry include:
"Artificial intelligence (AI) automation not only provides advantages for insurers but also costs reductions to their customers which can improve both agent and customer relationship." Trends that are likely to develop within the Insurance Industry include:
"Transparency, efficiency, innovation, and accessibility of data is expected with companies resulting in a more level playing field where insurers will be able to compete on equal footing with other service providers".
Trends that might evolve within the insurance industry include: "Increased data availability may give some insurers the opportunity to further reinforce their competitive advantage".
1) The explosion of data from connected devices
As the number of devices in a consumer's home and workplace continues to surge, technology will soon provide insurers with data to develop more intelligent products. There are over 6 billion devices connected to the Internet, and this number will double by 2025.
As these numbers continue to grow exponentially, insurers can use data from home-based technologies such as sensors—in everything from appliances (e.g., those installed in a refrigerator) that monitor temperature changes on an ongoing basis—to smart meters for energy supply companies, or even electronic medical records kept by hospitals.
In addition to increasing connectivity at home with IoT devices, insurers are also “investing in insights” to improve their products or services. Insurers may participate in initiatives such as the Consumer Data Broker Consortium (CDBC) and Provider Network Architecture (PNA).
The CDB is designed to make available a large data set of information collected on consumers when interacting with the insurance industry. PNA collects financial details from providers that provide a platform for "improving healthcare transparency worldwide."
2) Extended reality
In order to determine whether or not extended reality would affect an insurer's existing processes, The Economist noted: "Firms producing a physical product risk being taken out of business if they fall behind on technology that is no longer feasible or attractive as it ages.
The evolution will also see insurers trying to figure out how best to work with companies providing smartphone applications as a method of price competition."
This approach is logical as well since the industry might find it in its best interest to fully embrace and utilize these app-based technologies. Similar benefits could come from government agencies such as the Department of Health and Human Services (HHS) unless changes are made by legislators.
Data precision
Evolving technologies are proving to make insurance offers more up to date, accurate and straightforward. An example of this advancement is the development of healthy life expectancy.
The past few years have seen considerable struggles in insuring against end-of-life care, giving more elderly Americans financial instability as they age.
Following on these findings, research has now concluded that over a person's lifetime one's actual expected remaining time in good health could be as little as 35 days longer than their projected future predicted mortality risk at 65.
Moreover, life expectancy is determined by the choices of elders themselves. In other words, people are choosing to live longer due to better care available as well as technologies that can provide medical support for a formative period of their lives.
Overview of Artificial Intelligence in the Insurance Sector
The impact on the insurance industry by Artificial Intelligence (AI) technologies starts with consumers' desire to get a lower quote.
The trend is definitely here. AI is also shifting from automating: one of hundreds of businesses that are using it, only a few can boast about its use for their core business such as reinsurance brokers, consultants and rating agencies, etc., rather than customers' primary need for its own use.
Many capabilities that AI brings with it are expected to create better value for customers, which will lead to greater customer loyalty and higher retention rates.
The trend is also rather biased towards the field of business management, not personalization because this technology can help in areas like fraud detection: its capability makes predictions on future incidents by properly classifying an individual's behavior into different risk factors such as age group, etc., thus potentially saving a lot of money, human life and time.
But it is also found that AI could provoke a great risk for customers which would often result in low response rates (especially those who are less educated or who don't speak English well) because of the excessive learning period required by the system to classify different situations so as to make right predictions towards this customer.
In other words, sophistication has its disadvantages otherwise called "perverse effects". While insurers want more personalized service, customers are not satisfied with the level of AI deployment.
The US and the UK have a sparsely populated population of "native" Chinese speakers — estimates vary from 5 million in the United States to 8.5 million (35%) in England, with some analysts going as high as 20–30%.
As non-Chinese businesses expand into China, they generally invest heavily nationwide: Ai Now has invested USD 250+ Million on AI R&D over 10 years in many countries including Japan, Canada USA, UK, China, India and Russia.
Conclusion
In the near future, the impact of artificial intelligence on the insurance sector is likely to be significant. As bots become smarter and able to process data more efficiently, they are likely to play an increasingly important role in the underwriting process.
This could mean a shift away from human agents, and a closer alignment between technology and risk assessment.
In the meanwhile, insurers will still need to consider the ethical implications of such automation, and ensure that their customers are comfortable with its potential impact.
Do you have any thoughts on how AI will impact the insurance sector? Let us know in the comments below!
