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6 AI Applications that are transforming Insurance Now

With an insurance boom in the Asia-Pacific (APAC) region, Insurers are competing for developing superior technological capabilities in order to meet their customers’ demands better. Therefore, to stand out from the competition, companies are regularly adapting new tactics to ace the game, and AI is one of them.

According to a study, more than 80 per cent of insurance CEOs mentioned that AI was already a part of their business model or would be within the next three years.

AI has honed the way increasing data, computing capabilities, and evolving consumer expectations are handled and executed by making processes more automated and efficient. The role of AI has evolved over time to fulfil complex business requirements. In this blog, we will cover six significant areas in which AI is transforming insurance companies, but before proceeding, let’s take a look at how AI trends within Insurance.

Trends of AI in Insurance (50-100 Words)

Google Trends, reveals a constant uptick in AI-powered insurance applications acquired by the insurers between 2015-2020.

Google Trends, reveals a constant uptick in AI-powered insurance applications acquired by the insurers between 2015-2020. 

However, the impact of COVID-19 in 2020 has slowed this pace down a little. This is because insurer spending on AI systems had taken a back seat to mitigate other more pressing challenges that required allocation of budgets to those priorities. But in the Post- COVID world, it is expected that AI and insurance have a long way to go together.

How AI is Transforming the Insurance Industry 

Artificial Intelligence has driven positive impacts on many different business models, and insurance is no exception. Also, it works much better with AI because insurers have a treasure-trove of data, which is the primary fuel to drive successful results with AI.

Among all changes AI brought, the six major ones are mentioned below:

  1. Claims acceleration

AI is applied to automate or accelerate the process of claim. Claims processing includes a lot of tasks like reviewing, investigating, making adjustments and remittance or denying. If solely done by humans, the following issues might occur:

  • Inconsistent processing and more probability of errors
  • Varying data formats and time-taking management 
  • Staff training and process updating sessions

These processes can be accelerated with new Artificial Intelligence capabilities, leading to claims being paid in hours or days rather than weeks. However, likely, this kind of automation for claims acceleration will only work in low impact claims. For complicated requests, AI, along with human interaction, will be able to achieve the goal.

  1. Price sophistication using GLM

Insurers widely use AI techniques like GLMs (Generalised Linear Models) for price optimisation in tar and life assurance fields. Pricing optimisation allows companies to understand their customers better and enable them to balance capacity with demand and drive better conversion rates. 

Moreover, adding non-traditional data like unstructured data and written reports can also augment price optimisation and make better decisions.

  1. Using IoT 

IoT (Internet of Things) is one of the most significant AI opportunities within the insurance industry. These devices are getting a lot of traction from the users and are beneficial for insurance companies to assess customer risk profiles. Several IoT smart home devices are being used to alert customers when there are issues within their home or commercial property, for example, leak/moisture sensors. Using them, along with AI, helps insurance companies to offer better services.

For example, predictive analytics models could be built using the datasets of customers using leak detection sensors to predict which customers might be vulnerable to a leak. This prediction will help companies to send out repairers to replace faulty pipes before they burst to lead to claims.

  1. Personalised Services and Recommendations

Personalised services help customers to match their needs and lifestyle. Artificial Intelligence creates personalised services using customers’ product ratings, demographic data, preferences, interaction, behaviour, attitude, lifestyle details, interests, and hobbies. This helps companies in selling the right product to customers and target the correct audience. An Accenture study suggests that 80% of insurance customers are looking for more personalised experiences, and AI helps companies do so. 

Moreover, with the recommendations based on the customer’s behaviour or past purchases, AI shapes the way things are recommended to the customers. For example, a customer looking for health insurance would be displayed with offers on health insurance. Also, this helps in sending meaningful marketing messages.

  1. Eliminating underwriting risks

Humans solely did the process of underwriting. Therefore, the probability of getting errors was quite more and also it was a time-consuming process. But AI technologies have worked their way into this area of insurance and made the process quick and efficient without manual efforts.

  1. Affective computing (Emotional AI)

Also known as emotion AI, Affective computing is used to understand customers better and make decisions according to their mental/emotional states. It identifies, processes, and simulates human feelings and emotions and behaves and replies based on the same. This technology is shaping the Insurance industry in the following ways:

  • Fraud detection: Voice analytics is used to understand if a customer is lying while submitting a claim. AI makes this analysis based on various previous data sets and customer behaviours.
  • Intelligent call management: Customers running short on time or are angry are directed to more experienced call agents to ensure their satisfaction. 

New Adaptations

This ever-changing digital era is continuously adopting new technology. Therefore, another critical element to understanding the industry transformation is comparatively learning about the existing techniques and the new ones. 

The chart mentioned below contains some generic high-level use cases that many Insurance organisations are adopting. The abbreviations used are:

  • ML: Machine Learning
  • NLP: Natural Language Processing
  • SVM: Support Vector Machines
The chart contains some generic high-level use cases that many Insurance organisations are adopting.

Conclusion

So far, the blog must have helped you know how AI is transforming the Insurance industry in various ways. You can adapt to these modifications in your business model to stay ahead in the competition. However, it is worth mentioning that AI to an Insurance company could be beyond standard use cases and be viewed as a way to augment the role of data assets. There’s a lot to gain from the AI-first world for insurers, and also a lot to lose if AI is not embraced and well understood.

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Enhancing digital patient experience with healthcare chatbots

5 minutes read

Chatbots are fast emerging at the forefront of user engagement across industries. In 2021, healthcare is undoubtedly being touted as one of the most important industries due to the noticeable surge in demand amid the pandemic and its subsequent waves. The Global Healthcare Chatbots Market is expected to exceed over US$ 314.63 Million by 2024 at a CAGR of 20.58%.

Chatbots are being seen as those with high potential to revolutionize healthcare. They act as the perfect support system to agents on the floor by providing the first-step resolution to the customer, in terms of understanding intent and need, boost efficiency, and also improve the accuracy of symptom detection and ailment identification, preventive care, feedback procedures, claim filing and processing and more.

At the outset of the COVID-19 pandemic, digital tools in healthcare, most commonly chatbots, rose to the forefront of healthcare solutions. Providence St. Joseph Health, Mass General Brigham, Care Health Insurance (formerly Religare), and several other notable names built and rolled out artificial intelligence-based chatbots to help with diagnostics at the first stage before a human-human virtual contact, especially while differentiating between possible COVID-19 cases and other ailments. The CDC also hosts an AI-driven chatbot on its website to help screen for coronavirus infections. Similarly, the World Health Organization (WHO) partnered with a messaging app named Ratuken Viber, to develop an interactive chatbot for accurate information about COVID-19 in multiple languages. This allowed WHO to reach up to 1 billion people located anywhere in the world, at any time of the day, in their respective native languages.

For Care Health Insurance, Mantra Labs deployed their Conversational AI Chatbot with AR-based virtual support, called Hitee, trained to converse in multiple languages. This led to 10X interactions over the previous basic chatbot; 5X more conversions through Vanilla Web Experience; Drop-in Customer Queries over Voice Support by 20% among other benefits.

Artificial Intelligence’s role in the healthcare industry has been growing strength by strength over the years. According to the global tech market advisory firm ABI Research, AI spending in the healthcare and pharmaceutical industries is expected to increase from $463 million in 2019 to more than $2 billion over the next 5 years, healthtechmagazine.net has reported. 

Speaking of key features available on a healthcare chatbot, Anonymity; Monitoring; Personalization; collecting Physical vitals (including oxygenation, heart rhythm, body temperature) via mobile sensors; monitoring patient behavior via facial recognition; Real-time interaction; and Scalability, feature top of the list. 

However, while covering the wide gamut of a healthcare bot’s capabilities, it is trained on the following factors to come in handy on a business or human-need basis. Read on: 

Remote, Virtual Consults 

Chatbots were seen surging exponentially in the year 2016, however, the year 2020 and onwards brought back the possibility of adding on to healthcare bot capabilities as people continued to stay home amid the COVID-19 pandemic and subsequent lockdowns. Chatbots work as the frontline customer support for Quick Symptom Assessment where the intent is understood and a patient’s queries are answered, including connection with an agent for follow-up service, Booking an Appointment with doctors, and more. 

Mental Health Therapy

Even though anxiety, depression, and other mental health-related disorders and their subsequent awareness have been the talk around the world, even before the pandemic hit, the pandemic year, once again could be attributed to increased use of bots to seek support or a conversation to work through their anxiety and more amid trying times. The popular apps, Woebot and Wysa, both gained popularity and recognition during the previous months as a go-to Wellness Advisor. 

An AI Wellness Advisor can also take the form of a chatbot that sends regular reminders on meal and water consumption timings, nutrition charts including requisite consultation with nutritionists, lifestyle advice, and more. 

Patient Health Monitoring via wearables 

Wearable technologies like wearable heart monitors, Bluetooth-enabled scales, glucose monitors, skin patches, shoes, belts, or maternity care trackers promise to redefine assessment of health behaviors in a non-invasive manner and helps acquire, transmit, process, and store patient data, thereby making it a breeze for clinicians to retrieve it as and when they need it.

Remote patient monitoring devices also enable patients to share updates on their vitals and their environment from the convenience and comfort of home, a feature that’s gained higher popularity amid the pandemic.

A healthcare chatbot for healthcare has the capability to check existing insurance coverage, help file claims and track the status of claims. 

What’s in store for the future of chatbots in Healthcare? 

The three main areas where healthcare chatbots can be particularly useful include timely health diagnostics, patient engagement outside medical facilities, and mental health care. 

According to Gartner, conversational AI will supersede cloud and mobile as the most important imperative for the next ten years. 

“For AI to succeed in healthcare over the long-term, consumer comfort and confidence should be front and center. Leveraging AI behind the scenes or in supporting roles could collectively ease us into understanding its value without risking alienation,” reads a May 2021 Forbes article titled, The Doctor Is In: Three Predictions For The Future Of AI In Healthcare. 

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