Amigo MGA Best Practices

Digital consumerism is a trend that has been growing in recent years. With the advancements in AI and machine learning, companies in every industry can now get a more detailed picture of their customers. In retail, this means a 360° profile documenting more than just a purchase history. The one area that has trailed behind is the world of auto insurance, dragged down for decades by stagnant national brands and legacy product lines. That is all changing with the advancement of technology. Customers are demanding a personalized experience, and the auto industry is prepared to deliver.

Many things go through a person’s mind when they are in a vehicle accident. The guidebooks say to go through a checklist that includes checking yourself for injuries, checking passengers, getting everyone to a safe place, calling for help, waiting until help arrives, exchanging information with other parties, and documenting the incident. Most people, however, are not in the right frame of mind to rationally step through this list without getting emotional, which is to be expected. The concept of a clear-headed machine being able to handle all the details seems too good to be true, yet technology is at that point already.

Customers’ most significant complaint with their auto insurance providers is that claims are not processed quickly or correctly. The rates are then increased, either due to an incident or on the whole. Insurance providers have long sought ways of saving money so the savings can be passed down to customers. The issue arises when a claim comes in. Providers don’t usually hear anything until the claim. By then, claim costs have gotten out of control because expenses have already been paid. Customers could assist the providers by embracing sensor technology but choose to avoid it due to privacy concerns regarding private data and driver behavior. 

Accident Detection and Response (ADR) is the latest piece of technology that will not only save costs but will also save lives. Insurance providers can be involved in real-time at the moment of an accident through virtual sensors. Crash data is instantly read, and first-responders are contacted, if necessary. Without sharing personal data, ADR can share granular, real-time bodily injury reports with EMTs in order to get the required life-saving care. All crash data is instantly uploaded to the cloud and analyzed, generating damage and injury reports without false positives or false negatives. 

New car technologies have features in common with other IoT devices of today. The more automated the vehicle, the more reliant the system is on algorithms and AI. When shopping for auto insurance, there are questions that people of today need to be prepared to ask. The more knowledge you have, the better because the old method of the rate calculation for insurance no longer applies to these new variables. 

When shopping for a new car, it’s essential to weigh the latest model’s pros and cons against how much your insurance will increase. This could be something as small as a newer design of bumper or a back-up camera. Examine the levels of insurance being offered, including the premium vs. basic levels. For some people, it’s a waste of money to purchase the higher-end policies. For others, the extra cost is worth it if repairs or maintenance are needed. Opt-in discounts are also carefully worded and must be read carefully, such as with advanced anti-theft services only being considered when merged with a comprehensive premium coverage plan. 

The Repair Cycle 

It is a cyclical process. Over the past several years, car insurance rates have increased as a result of the latest technology. In the past, you could bring a car to an auto body shop or car dealer for a simple issue, such as a cracked bumper. Nowadays, there are built-in sensors and very complex electronic components. A car with a built-in navigation center or a backup camera will require more skilled labor than the past’s standard car repair. Not only will specialized parts need to be ordered, but the labor will also increase as jobs will take longer to complete. The mechanics themselves will be trained and more technical, which will also raise their hourly rates. 

Safety Features

Despite all the exciting new safety features being touted in today’s autonomous cars, there is still much testing left to be done. In addition, humans still have the ability to override a driving system, giving them just as much control as a regular driver. Insurance companies must consider the driver as well as the vehicle, no matter how complex. The learning curve might also hinder, as humans adjust to new distractions of lights and buttons that they are not familiar with. This could slow a person’s reaction time in a crisis. 

 The Driver

Regardless of the technology you have in your car, insurance rates will also depend on you, the driver. Moving violations and accidents on your driving record will increase your rate regardless of the type of car you drive. Demographics also play into how much insurance you will pay. Rural communities have fewer vehicles on the road, which lessens the probability of accidents occurring. This substantially lowers insurance rates.

It would be an understatement to say that machine learning and artificial intelligence have made some type of impact on nearly every sector and industry around the globe. In addition to the energy, healthcare, real estate, and consumer goods and services markets, the influx of emerging technologies is disrupting the financial and insurance worlds as well. 

It is crucial for industries to embrace the future of a reduced human workforce and to learn how to work in collaboration with machines, not against them. The advent of machine learning and its ability to process big data will give partnered insurance companies an enormous boost over the competition that refuses to do so. The main advantage comes from a machine’s ability to read and identify massive quantities of data that a human would never be able to. In addition, the device can see patterns in the data, sort it, and predict behaviors. This means making a fair estimate of an incident’s causes, leading to a timely and unbiased assessment of damages, resulting in speedy and accurate claims processing. From a customer service perspective, this is a dream come true. 

Another way that an insurance company would benefit from emerging technology is by having a chat-bot on their website. This is a feature that is becoming increasingly more popular because of its ability to respond 24/7 to the majority of general questions for customers. In addition to making customers happy, the call centers’ employees will also be relieved of stress due to fewer anxious phone calls and an overall decrease in caller volume.

Many industries are also embracing the concept of digital portals. These are web-based platforms that combine data from multiple sources into one easily manageable location. Unlike websites designed to maximize traffic, web portals are meant to filter out the majority of visitors and only share relevant data to those with login credentials. Customers and employees can access the interface and use it to review customer data, a claim’s history, and status updates.

In general, the future of machine learning and automation will benefit the world of insurance in many ways, either by saving time, money, or aggravation. Underwriting will be handled faster and more efficiently. Claims will be filed based on a vast array of knowledge sorted by a clients’ history and predictive analysis. 

Big data is named that for a very good reason. It refers to quantities of information that are so large or complex that it’s impossible to process using traditional methods. We as a species have collected more data within the past two years than mankind has in its entire history, yet we are unable to process it sufficiently. The variety of industries that are offering up data are constantly growing, including electrical engineering, telecommunications, vehicular technology, social media, voice analytics, connected sensors and wearable devices.

One of the great things about machine learning is its ability to handle big data like this. Machine learning takes a large amount of information and detects meaningful patterns. From there, it can make predictions at a rate of speed and accuracy that far surpasses humans. Machine learning and its ability to adapt is being used in almost every industry nowadays and the world of insurance is no exception.

Auto insurance is all about data when it comes to claims and premiums. When a driver seeks to purchase auto insurance, there are a number of factors that are considered, and the higher a person’s risk factor, the more it translates into real-world decisions like the costs of premiums.

Most insurance companies are only able to process 10 to 15 percent of the data they receive. This data is stagnant and stored in databases. This structured data is not used to its full potential, and it doesn’t display any predictive modeling behavior. Machine learning provides the boost they need to face their competition and enhance customer satisfaction. AI is also being explored in other departments as well, such as underwriting, fraud detection, and loss prevention.

Ultimately, direct machine-to-human interaction will begin from the moment the first interaction occurs between the customer and the insurance company. On the front-end, 24/7 chatbots have made it easier for potential customers to have answers at the ready, as well as existing customers filing claims. All while freeing up in-house employees to focus on other tasks. On the back-end, clients receive personalised products that are created by machine learning algorithms that have tailor-made packages based on users’ profiles.

The ultimate goal is to combine the Internet of Things (IoT) to share omnipresent data in an open source platform. This would apply to everything from smart homes to smart cars to the healthcare industry. 20 percent of companies have departments solely dedicated to guide and monitor the progress of machine learning.  

Perhaps one of the biggest concerns about the migration over to self-driving cars is the safety factor. Many questions are being raised about the issue of ethics. While a computer can make lightning-fast decisions based on data and logic, the recurring fear is that, as a machine, it cannot possibly make the same type of life-affecting moral decision that a human can. For this reason, many studies are being done to determine whether it really is safer to have an AI system behind the wheel.

Research published by the National Highway Traffic Safety Administration division of the U.S. Department of Transportation (USDOT NHTSA) found that the majority of all car crashes between 2005 and 2007 were the result of driver error, as opposed to a malfunction. Driver distraction and/or impairment caused 94% of the crashes. In order to be deemed safe, therefore, an automated system would just have to have better numbers than humans.

Testing has been a bit of a contentious issue since real-world scenarios are hard to employ without putting people in danger. There are test runs being done by companies such as Google, who are showing huge strides with their focus being on driver assistance, rather than car manufacturing. What began as a self-driving car project, their offshoot company, Waymo, has partnered with several major car developers to enhance their own cars for automation. 

If data analysts focus on the issue of driver error due to impairment and/or distraction, there will undoubtedly be fewer instances of alcohol- or drug-impaired driving when the human is removed from the equation. Within the next few years, safety testing will advance to real-world situations in order to help with the machine learning process. Tesla’s latest model has received high marks for safety tests. In order to earn its five-start rating, the Model 3 not only had to show good overall performance in crash protection but also display superior and robust crash avoidance technology.

That being said, all computing systems are vulnerable to hacks, and cyber protection will have to be at unprecedented levels in order to prevent malicious external cyberattacks from occurring. 

There are several trends that are making a huge impact on the auto insurance industry. Some of these include maximizing efficiency, attracting fresh talent to the industry, and making people’s data more secure. 

AI

Artificial Intelligence has the ability to completely transform the insurance industry in areas from productivity and customer service, to security. New functions that focus on fraud protection help not only the insurance providers but also the customers who follow the rules. Robo-advisors are on the horizon which will save both clients and underwriters unnecessary wait times. The development of 24/7 chatbots has already been well-received for common user questions.  While humans are still working in tandem with machines, it is no secret that companies need to embrace this technology in order to survive in their industry. One example of AI already at work is CARPE DATA, which gathers real-time data and uses it for predictive scoring for every stage of an insurance lifecycle, including claims. Shift Technology is a company that focuses on fraud detection specifically for the insurance industry. 

Blockchain

Blockchain maintains the same advantage as the World Wide Web, in that there is no main point of control. Blockchain technology acts like a virtual ledger that records all transactions in a secure, unchangeable way. It takes the place of having a third verification party for each transaction, thereby saving the insurance company money which in turn, gets passed down to customers. Using this technology, insurers can quickly verify credentials, historical data, and contracts. It is also nearly impossible to duplicate, because of it’s multi-level verification transparency. It is a perfect fit for apps like Teambrella, who apply the democratic notion of insurance and filing claims. They support the concept of teamwork being part of every decision. Users cover each other and vote on payouts and premiums, as opposed to being presented with a limited number of options to choose from. Blockchain technology is used to securely handle all payments put all minds at ease. Lemonade makes full use of AI and blockchain technology to call themselves the home, rental, and pet health insurance provider for the 21st Century. The philanthropic arm of the firm also donates a portion of profits to various causes.

The insurance industry is by far heavily dependent upon statistics and analytics. It thrives on data. By examining a variety of data and looking for patterns, they are able to predict probabilities. This helps insurance providers create personalized risk profiles, which are used to drive an individual’s premiums and payout amounts, among many other factors. Machine learning has taken away some of the tedium involved in data gathering and investigating insurance fraud, in addition to helping the insured get the help they need. 

Common sense dictates that the best protection against danger is prevention. Vision Zero is the goal of a worldwide zero-tolerance policy for traffic deaths and injuries. Many companies are on the path towards accomplishing it thru AI. Zendrive is a mobile app that monitors customers’ driving behavior. Through the use of sensors, it can help detect potential collisions, track phone use while driving and help the driver avoid drifting, among other features. It can also use this data to reward good drivers with auto insurance discounts. 

Despite all precautions, sometimes accidents do happen. When a claim is filed, it typically passes through checkpoints as it moves through the processing system. When it’s all human-controlled it can be a lengthy process. The advent of machine learning has automated the process for many standard claims, which frees up the system to concentrate on the ones that need more time for investigation.

Healthcare underwriting is another area that has benefitted greatly by a data-driven approach because of the cost of diseases, accidents, disabilities, and death. Daisy Intelligence uses artificial intelligence to suggest prices based on individual risk profiles.

One roadblock in any human-to-computer interaction is the difficulty in parsing human handwriting into usable data. Captricity uses an algorithm called READ that is able to read and extract data from both handwritten or typed forms with 99.9% accuracy. Lemonade is a carrier that uses AI to process all of their claims quickly and efficiently, providing customers with faster payouts. 

In addition to saving money for both the clients and the insurance carriers, AI-propelled chatbots can provide 24/7 customer care service to the majority of questions people need to be answered in a hurry. When it comes time to choose an insurance plan, customers can use AI resources to narrow down their choices to match the best plan for themselves and their families.  Not only does this free up phone lines during business hours, but it also goes a long way towards relieving people’s anxiety about claims, billing, and payouts. 

When people discuss the best practices of a business, they are usually describing the policies, ideas, and ethics that represent the most sensible course of action in any given business situation. The best practices of a company are usually decided upon by a company’s management team and they are created to fix problems in the most prudent way possible. In addition, best practices are in place to encourage positive employee morale and to help people succeed.

Deciding on which best practices you intend to follow as a business should be something you as a management team agree upon during the earliest stages of company creation. It is tied in very closely with a company’s culture and how freely the employees feel they can come to their leaders with issues or for guidance. Employee engagement is one of the most important practices, as it makes them feel like they are a part of the company. Holding all-hands meetings to announce when changes occur and then giving employees the opportunity to ask any follow-up questions is a great motivator. Highlighting good performance by giving shout outs and honoring employees of the month are other ways of recognizing the efforts of your team members.

 In addition to hosting meetings, a good rule of thumb is to get employee feedback every few months on how they feel best practices are being used. As a leader, it is your job to be open to critique and suggestions without taking any of it personally, so ask the right questions that will really encourage people to give constructive answers. Most importantly, let them see that you take suggestions seriously by incorporating effective changes in the workplace and showing consistent enforcement.

If a major update is going to take place, it’s important to make sure that everyone is involved when it is announced. The last thing you want is for some people to not be alerted to an announcement and find it out through other channels. All people should be notified at the same time. Introduce change slowly and with plenty of time for training. All change will come with a learning curve.