Data Science

How Artificial Intelligence Will Impact The Insurance Industry

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If you’re like most people, calling an insurance company isn’t among your favorite activities. That’s because the insurance industry is one of the least innovative areas for customer experience, meaning that customers typically come away from their interactions disappointed and dissatisfied. However, things are definitely changing, and artificial intelligence is playing a large role. The fast-growing technology has the potential to disrupt the entire industry and greatly improve the insurance customer experience.

Artificial Intelligence In The Claims Process

The insurance agency is notorious for its outdated processes. Filing a claim often looks the same today as it did decades ago because the industry isn’t consistently leveraging new technologies that are available to them. If an employee is busy or on vacation, a claims request could sit still until the right person is back. The outdated processes make it harder for agents by increasing the workload and forcing them to work with antiquated systems and frustrated customers.

However, AI can be applied to improve the claims process. Claims currently are touched by multiple employees. However, a new process of “touchless” claims doesn’t require any human intervention. This process uses artificial intelligence and other technology to report the claim, capture damage, audit the system, and communicate with the customer. The potential here is huge, as the process could allow clients the chance to file claims without having to wade through red tape.

Companies that have already automated some aspects of their claims process have seen a significant reduction in processing times and quality. AI-powered claims could also fight against one of the most costly elements of the insurance industry: fraudulent claims, which cost the industry more than $40 billion a year. Instead of relying on humans to manually comb through reports to catch inaccurate claims, AI algorithms can identify patterns in the data and recognize when something is fraudulent.

Future Of AI And Insurance

The industry is definitely ripe for AI disruption. Customers expect to be able to interact with companies through modern technology; a recent survey found that 74% of consumers say they would be happy to get computer-generated insurance advice.

Many insurance companies are already using artificial intelligence to some degree, and the number of companies following in their footsteps is sure to increase dramatically over the coming years. Artificial Intelligence has never been less expensive or more accessible, which means most companies don’t have a reason not to adopt it in at least some form.

Chatbots

Chatbots work through messaging apps many customers already have on their phones, which makes them a natural next step in customer interaction. In order to truly be effective, chatbots must have natural language processing and sentiment analysis so they can understand what customers are really asking. Effective chatbots can process concerns that are either typed or spoken from customers and provide personalized service. In the insurance space, chatbots can be used to answer basic questions and resolve claims, as well as sell products, address leads, or make sure customers are properly covered by their insurance. (Read More...)

Getting personal: how AI-driven personalised marketing is the future of brand communications

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Moreover, this phrase even encapsulates what personalised marketing is all about. Simply put, it is the art of creating and delivering communication tailored according to each individual consumer’s preferences. Fundamentally, personalised marketing is the process of communicating the different value of the same product or service to various consumer segments, be it students, working professionals, millennials, middle-aged consumers, digital or offline consumers, etc. Hence, as the communication channels for each of these segments varies greatly, marketers must also craft their messages for consumers in such a way that it is connected to everyone. This simply means only pitching the content, products, and services that appeal to them.

Why personalise?

Consumers today want to spend as little time as possible on choosing from the seemingly endless number of offerings in the market. Moreover, they are often looking to avoid the overload of messages from multiple brands across various channels. Hence, the success of personalised marketing hinges on short and precise messages that convey value and elicit a positive response from the consumer. Personalised marketing also delivers better measurable responses and can be leveraged considerably to not only acquire new customers, but also retain them in the long term.

Where does Artificial Intelligence (AI) fit into personalised marketing?

Today, Artificial Intelligence is that secret ingredient that’s enabling brands to win customers through hyper-personalisation of their products and services. AI has transformed the customer experience into something which, until a few years ago, was simply inconceivable, and several companies are already applying the technology for various digital marketing activities. For instance, AI is being deployed by businesses to create websites, social media posts, run email marketing campaigns, optimise content for different consumer segments, etc. Thus, it is helping brands become more agile in their communications, as well as more responsive to consumer demands, as and when they change.

Traditionally, marketing campaigns are designed around a single message or product. While the message may be a predefined one based on the customer lifecycle, these campaigns are usually targeted to a broad consumer segment. With AI, however, marketing campaigns can be made much more streamlined and targeted. The combination of AI, Machine Learning, and data analytics can enable marketers to do impressive things. For instance, insights from a customer’s behavioural traits, gathered through predictive analytics, can be an indicator of not only when they are likely to purchase a product, but can also help marketers create tailor-made messages based on specific data from the past. Customer profiles, purchase patterns and histories, brand interactions, and social data all create a detailed map of each customer’s mindset and preferences. (Read More...)

Big Companies Are Embracing Analytics, But Most Still Don’t Have a Data-Driven Culture

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For six consecutive years NewVantage Partners has conducted an annual survey on how executives in large corporations view data. Each year the response rate increases, and the reported urgency of making effective use of data increases as well. This year the results are both more encouraging and more worrisome than in the past.

Six years ago, the primary focus of questions and answers in the survey was big data, which was relatively new on the business scene. In the 2018 survey, the primary attention has moved to artificial intelligence. AI is now a well-established focus at these large, sophisticated firms. There is both a stronger feeling that big data and AI projects deliver value and a greater concern that established firms will be disrupted by startups.

The survey includes senior executives from 57 large corporations. The industry group with the most firms represented in the survey is one of the most data-intensive: financial services. Companies from the life sciences, manufacturing, telecom, and online industries also participated. The actual respondents are changing somewhat from the first surveys: It has always involved a high proportion of C-level executives responsible for data, but this year chief data officers are 56% of the respondents, up from 32% last year. Only 12% of firms in the 2012 survey had even appointed a chief data officer.

While AI gets the headlines here and elsewhere in the world, the survey addresses both big data and AI. Terminology comes and goes, but the constant is a data explosion and the need to make sense of it. Big data and AI projects have become virtually indistinguishable, particularly given that machine learning is one of the most popular techniques for dealing with large volumes of fast-moving data. It’s also the case that statistical approaches to AI — deep learning, for example — are increasingly popular. Therefore, we view traditional data analytics, big data, and AI as being on a continuum. Virtually all of the respondents (97%) say they are investing in these types of projects.

Perhaps the best news in this survey is that companies continue to believe they are getting value from their big data and AI projects. 73% of respondents said they have already received measurable value from these initiatives. That number is half again higher than in the 2017 survey, which suggests that more value is being achieved as companies grow familiar with the technologies. (Read More...)

Machine Learning Is Revolutionizing Marketing

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Measuring marketing’s many contributions to revenue growth is becoming more accurate and real-time thanks to analytics and machine learning. Knowing what’s driving more Marketing Qualified Leads (MQLs), Sales Qualified Leads (SQL), how best to optimize marketing campaigns, and improving the precision and profitability of pricing are just a few of the many areas machine learning is revolutionizing marketing.

The best marketers are using machine learning to understand, anticipate and act on the problems their sales prospects are trying to solve faster and with more clarity than any competitor. Having the insight to tailor content while qualifying leads for sales to close quickly is being fueled by machine learning-based apps capable of learning what’s most effective for each prospect and customer. Machine learning is taking contextual content,  marketing automation including cross-channel marketing campaigns and lead scoring, personalization, and sales forecasting to a new level of accuracy and speed.

The strongest marketing departments rely on a robust set of analytics and Key Performance Indicators (KPIs) to measure their progress towards revenue and customer growth goals. With machine learning, marketing departments will be able to deliver even more significant contributions to revenue growth, strengthening customer relationships in the process.

The following are 10 ways machine learning is revolutionizing marketing today and in the future:

  1. 57% of enterprise executives believe the most significant growth benefit of AI and machine learning will be improving customer experiences and support. 44% believe that AI and machine learning will provide the ability to improve on existing products and services. Marketing departments and the Chief Marketing Officers (CMOs) running them are the leaders devising and launching new strategies to deliver excellent customer experiences and are one of the earliest adopters of machine learning. Orchestrating every aspect of attracting, selling and serving customers is being improved by marketers using machine learning apps to more accurately predict outcomes. Source: Artificial Intelligence: What’s Possible for Enterprises In 2017 (PDF, 16 pp., no opt-in), Forrester, by Mike Gualtieri, November 1, 2016. Courtesy of The Stack.
  2. 58% of enterprises are tackling the most challenging marketing problems with AI and machine learning first, prioritizing personalized customer care, new product development. These “need to do” marketing areas have the highest complexity and highest benefit. Marketers haven’t been putting as much emphasis on the “must do” areas of high benefit and low complexity according to Capgemini’s analysis. These application areas include Chatbots and virtual assistants, reducing revenue churn, facial recognition and product and services recommendations. Source:  Turning AI into concrete value: the successful implementers’ toolkit, Capgemini Consulting. 2017. (PDF, 28 pp., no opt-in).  (Read More...)