Artificial intelligence by default has become a part of our lives. It is possible to see artificial intelligence applications in almost every app that we are frequently using every day. For example, Spotify offers a weekly playlist to suit our music taste; Tesla cars drive without a driver, and Siri answers the questions we ask. This list can be improved considerably. It is unknown whether artificial intelligence will take over the world, but for now, it is obvious that it is a part of our lives and that we are rapidly adapting to it. With the rapid development of artificial intelligence, many sectors are being affected by this trend. We see artificial intelligence in almost every sector. One of the sectors where artificial intelligence has been on the rise recently is the insurance sector.If you're following the Hackquarters blog, you've seen our article on InsurTech a couple of weeks ago. In general, we talked about InsurTech, the sector, and trends. This week's article goes in-depth on the relationship between artificial intelligence and the insurance industry. Before examining the relationship between artificial intelligence and the insurance sector, let's focus on artificial intelligence in general.
Artificial intelligence is the general terminology of the technology of developing machines that can exhibit behaviors and movements such as human beings created entirely by artificial means without taking advantage of any living organism. When approached as an idealist, artificial intelligence products that are completely human capable of feeling, predicting behaviors and making decisions, are generally called robots.
When we enter into artificial intelligence, machine learning, and deep learning come on stage. So, what is machine learning and deep learning?
Machine Learning is a method paradigm that makes inferences from existing data using mathematical and statistical methods and makes predictions about the unknown. Some examples from our current lives in machine learning: face recognition, document classification, spam detection.
Deep Learning is a machine learning method. It allows us to train artificial intelligence to predict outputs with a given dataset. Both supervised and unsupervised learning can be used to train artificial intelligence. The more data, the better artificial intelligence features will be revealed. Things will become more complex, and as they become complex, shifts from artificial intelligence to machine learning will occur. As it becomes more complex, the transition from machine learning to deep learning will begin. The more data you have, the better your system will work. While machine learning operates in a single layer, deep learning processes several layers simultaneously.When we consider all this, we can think of artificial intelligence as an umbrella that takes machine learning and deep learning. In fact, all these practices are methods developed to facilitate human life and to provide solutions to our daily life problems.
Thanks to technologies such as Robotic Process Automation, you will be able to get your relatively demanding jobs, such as data entry, from outside service providers. Artificial intelligence is adding a new dimension to productivity, insight, and probability, especially for deepening customer engagement and relationships and encouraging growth. Today, insurance agents are already using artificial intelligence in customer service, answering simple questions with chatbots and redirecting requests. In the future, employers can even offer additional benefits with specialized chat robots that provide personal advice in the fields of health or medical counseling.
Artificial intelligence, combined with other technologies, such as devices compatible with the Internet of Things and machine learning, can also help insurance agents better understand the behavior of their customers and indirectly risk. For example, some car insurers offer customers discounts on drivers with safe habits by placing sensors in their vehicles to track their driving.In the field of collateral, health and life insurance agencies use wearable products that follow the daily habits of the members. In light of this information, artificial intelligence can take these initiatives one step further by increasing participation or personalizing services. For example, data can help a client benefit from health and nutrition coaching.
One of the most promising ways to use artificial intelligence is in the prevention of fraudulent demands vertical. With artificial intelligence and machine learning, computers can detect fraud and get better at it. For example, Shift Technology, a new French-based company, helped an agency association in Europe analyze 13 million demands. With this technology, 3,000 new cases were identified, including a large organized crime mechanism that affected almost the entire union.Here are some InsurTech companies that reshape the Insurance industry.
It stands out with Chatbot technology, one of the most popular and widespread areas of artificial intelligence. Built on the artificial neural network algorithm, the chatbot provides 24/7 policy generation and damage approval within 90 seconds. In addition, they hybridize an algorithm called Benford's Law with a Neural Network algorithm through artificial intelligence with fraud detection and analyze potential misconduct.
Zendrive is an insurtech in the field of pay as you that the insurance industry has heard a lot about and is still under interest. What distinguishes it from others is that it shares the data it collects with the drive as actionable data, using the machine learning technology it uses. Zendrive's artificial intelligence, who learns that traffic accidents on a particular street are increasing, can tell you when you approach that street, “You better not go into this street ”. Moreover, thanks to the big data, the initiative shares very effective messages.
Using an algorithm similar to the deep learning algorithm that Google uses to show you similar pictures when you upload an image, Tractable offers an artificial intelligence that predicts how much damage you will take when you crash your vehicle.