The idea of AI-powered tools and technology transforming practices and revenue models within industries has gathered tremendous weight in the last couple of years. The reason — artificial intelligence has backed the talk with the walk. It is becoming the real deal.
Kind of like those who said the Internet was only a fad back in 1997 and it became one of the key difference makers in human history. Is the Internet still a fad?
From enterprising startups to the technology giants of the world — organizations have invested millions into developing AI-powered tools that help them realize business use cases of tremendous value.
Insurance is an industry that heavily depends on analysis of terabytes of data from several channels — general public health, age-related disease exposure, the correlation between demographics and longevity of human life, financial analysis, creditworthiness of prospects, and many more.
No wonder, the impact of AI-powered tools in this market is already being felt. Here’s your quick intro and run-through how AI-powered tools are transforming the insurance industry.
Driving insurance industry’s supernormal growth
The insurance industry is based on three pillars — reaching out to prospects at the right time (trying not to annoy people month after month with marketing material junk mail, which Geico seems to be an expert at — no means no, you had your shot, we left you for good reason!), delivering them a value-adding and profitable insurance product, and process genuine claims speedily, while rejecting and reporting fraudulent claims.
An insurance firm deploys an army of marketing experts, financial product designers, operations managers, and claim investigators, apart from technology systems to manage the show. Add in the AI boost and insurance firms can expand their capabilities across all these operational aspects. In the next sections, we’ll cover them in detail.
Predictive analytics to identify customers
AI-powered predictive analytics is a massive enabler for insurance companies. Let’s take the example of health insurance. Mostly, the product profitability is closely tied to the probability of the insured individual living a healthy life. Predictive analytics helps here in many ways:
- Building data-based models to categorize customers into different groups according to their expected future course of health (the Infernocons in “Transformers 5” have some serious issues when it comes to their health since they apparently forgot who Optimus Prime is!), hence helping the organization to charge premiums as per the risk profile.
- Analyzing the currently available data assets from the customers and enabling the insurer to proactively communicate to potential outliers, and reduce their chances of degrading health further by sending out partner offers such as free health checkups.
- Claims and insurance usage data may be used to generate individual user level insights related to how the company can pitch better insurance products to specific customer classes.
The applications of predictive analytics algorithms extend beyond this, including all aspects of the insurance business.
Customer experience automation
Artificial intelligence promises significant cost savings for insurance companies by enabling the automation of several customer-facing processes. For instance, instead of deploying teams of support personnel to take up user queries and to pitch products to prospects, insurance companies can deploy AI-powered chatbots.
These bots use natural language processing algorithms and machine learning to manage conversations with end users. Chatbots can customize the communication, messaging, and tone based on the user persona. Also, these bots can judiciously suggest insurance policy products and address user questions about the nuances of these products. This is a massive opportunity for insurance companies to increase market share by offering enhanced customer experiences.
Claim processing efficiency
If you’ve ever had to file a claim with an insurance company, you know that in spite of the service provider’s best intentions, the processing times are inconveniently large. Note that the claims process, for the customer, coincides with a time of personal loss (biological or material — either situation is depressing, though biological is even worse, of course).
Any inconsistencies, delays, and hassles in the claims process severely damage the relationship between the customer and the company.
Market leaders in the insurance vertical — AIG, for instance – are already using AI-powered tools to improve the claims-processing aspect. With AI-powered algorithms to assess, analyze, escalate, contest, and process all kinds of claims, insurance companies can reduce the processing time from around 15 days to 2-3 days. Not a bad deal!
Of course, there have been buzz-making stories such as that of Lemonade, an insurance tech startup based in New York City, which processed a claim within three seconds with the help of an AI-powered claims settlement bot. The bot, in this case, verified details of the claim, and ran the claim through a fraud detection algorithm, and passed instructions to the bank to transfer the claim amount.
A dash of personalization in marketing
Marketing campaigns that strike an emotional chord with consumers deliver stellar ROIs to insurance companies. Personalization is the key here. Traditionally, however, insurance marketing has adopted a mass market approach, primarily because of operational limitations. This is where AI promises to instigate another positive change in the insurance industry.
Let’s take the example of United Services Automobile Association (USAA), an insurance service provider that used Eva, an IBM Watson-based virtual assistance, to personalize its marketing efforts. Eva answers customer queries and then uses the interactions to drive automated and personalized email campaigns for the brand.
A recent survey showcased how customers are also quickly buying into the idea of non-human yet customized insurance advisory service, with 74 percent respondents saying they’d be happy to receive computer-generated insurance advice.
Fraud detection
Did you know — it’s estimated that insurance claims fraud costs the insurance industry $40 billion annually in the United States (and therefore all honest people). Relying entirely on human intelligence and intuition to analyze and verify millions of insurance claims, obviously, hasn’t worked.
AI offers a solution here as well. By analyzing patterns in terabytes of data, analyzing customer history, and continually learning to improve their operations, AI-powered fraud detection algorithms can save millions of dollars every year for insurance companies (and their shareholders).
Image identification and analysis technology, for instance, can assess user-submitted forms and photos and determine unnecessary repairs, hence preventing leakage of claims amounts. Also, AI allows insurers to automatically report and follow up dubious claims, freeing up several labor-hours for a diligent investigation.
AI-powered tools and insurance: An exciting future
Natural language processing, machine learning, chatbots, predictive analysis, marketing personalization — a lot is happening in the insurance industry, and it’s all being driven slowly by advancements in artificial intelligence. With AI-powered tools, the future for the industry is exciting, with the potential for cost savings, product improvement, and customer experience improvement opportunities.
Featured image: Pixabay
