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InsurTech: 5 benefits of technologies in Insurance Sector

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InsurTech is a buzzword nowadays where a variety of technologies are set to transform the traditional insurance industry. In the last two years, insurers have already transformed themselves digitally to offer convenience, security, choice, and a seamless experience to their customers.

Accenture estimates that insurance companies can increase their annual profitability by 20% with the right investment in the technology.

Internet of Things (IoT), telematics, drones, the blockchain, smart contracts, and artificial intelligence (AI) are providing new ways to measure, control, engage customers, reduce cost, improve efficiency and increase customer experience.

Here are five ways Insurers can stay ahead in the market and successfully fulfill high customer expectations. 

1. Lower Insurance rates:

 – Fitness apps or wearable devices:

Staying fit has many perks. Some of the fitness apps like Wysa and wearable devices help maintain weight, and food habits and boost energy and mood. And most importantly they can help save a huge amount of expenses related to health insurance costs. Numerous insurance providers have tapped into wearable devices to keep motivating their customers to stay fit and healthy and offer them discounts and benefits based on fitness levels.

– Self Driving car:

Self Driving cars can help in reducing the chances of accidents and lower life insurance rates. Since road deaths are a significant percentage of deaths in the entire world, any slight downward change will ultimately lead to lower deaths and hence life insurance claims.

2. Fraud Prevention:

Insurance fraud costs companies billions of dollars per year across the globe. Insurance companies should establish a technology framework, tap into advanced automation and analytics, and take steps to prevent it.

– Digital Signature:

Digital signature technology is without a doubt lowering fake insurance account activation and hence a fraud. For example, a digital signature can prevent fraud- insurance purchased after the accident can be brought down with digital signatures verifying the actual date.

– Data analytics:

The technology involves data mining tools and quantitive analysis. Data analytics can be applied to detect fraud. Predictive analytics is useful to improve the fraud detection process, helping prevent claims payouts. Analytics on claims and fraud transactions helps enhance risk management.

3. Lower underwriting cost:

–IoT

According to IoT Analytics, the global number of connected IoT devices is likely to grow at 9%, with 12.3 billion active endpoints. By 2025, there will likely be more than 27 billion IoT connections, which will have a significant impact on the availability of real-time information that insurers can use for better pricing/underwriting. Drones are satellites on steroids at least as far as underwriting is concerned. Satellites have dramatically changed how home insurance policies are written due to fire. Everything can be captured via drone footage even the houses that get covered behind the trees. Captured data can be used for underwriting purposes.

4. Billing efficiency:

Billing systems are not only integrated but now can accept varied forms of payments allowing ultimate flexibility to the customer and thereby making the billing systems efficient. The automated systems inform and remind customers of approaching due dates for premiums thereby lowering unintentional defaults.

Digital wallet has become one of the most widely used platforms for payment systems. Insurance companies are leveraging payment gateways like Google Play to sell insurance to users. Last year, SBI General Health Insurance launched Arogya Sanjeevani on Google Pay Spot to offer standard coverage at affordable premiums and improve the penetration of health insurance in the country.

5. Specialized insurance:

Each type of insurance is different from the other and the factors that are suited to one are not suited to the other. This requires the insurance agents to have specialized knowledge and the internet helps. however, Machine learning is vitally important here. It has the capability to learn and analyze billions of patterns and identify suitable underwriting clauses as well as identify specific customized plans for the customers based on the data provided. This can change the customer perception of the insurance company and provide an engaged customer who is likely to stay longer. 

Dinghy, is a pay-by-the-second insurance provider that customizes coverage for freelancers and businesses where customers may switch their policies on and off as needed without any upfront premiums, interest, credit checks, or fees. 

6.  Smart and Faster Claim Processing and Settlement: 

–AI-Powered Chatbots:

Claim settlement has been one of the pressing issues in insurance. With intense competition looming in the market, delay in the claim settlement gives a bad experience to the customer who prefers to switch to another brand. Insurance providers worldwide have been investing in AI-powered insurance chatbots to enhance customer experience. Metromile can validate 70% to 80% of claims instantly using AVA, an app based-claims assistant.

7. Data-driven pricing

–Telematics:

Innovation has become one of the top priorities for insurers today due to rapid change in customer demand. The usage-based insurance market is projected to hit over $190 billion by 2026, telematics is allowing carriers to capture user data and create personalized usage-based insurance products. 

For example, auto insurance was based on a pay-as-you-drive model where customers use to pay a premium based on the distance covered. But with technological innovation, insurers are working on a pay-how-you-drive model where customers can get discounts based on their driving skills. 

Rise in demand for innovative solutions, intelligent experiences, and speedier processes has led to technological disruption in the insurance industry. According to  IDC, IT spending in the insurance industry will increase globally at a CAGR of 6.0% by 2024, touching $135 billion. With continuous investment in technology, insurers are working on improving customer experience and operational efficiency to maximize profitability in the long run.

Thanks you Scott W Johnson, owner at WholeVsTermLifeInsurance.com for providing your valuable information on how technologies are helping Insurance industry.

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10 Analytics Tools to Guide Data-Driven Design

Analytics are essential for informing website redesigns since they offer insightful data on user behavior, website performance, and areas that may be improved. Here is a list of frequently used analytics tools to guide data-driven design that can be applied at different stages of the website redesign process. 

Analytics Tools to Guide Data-Driven Design

1. Google Analytics:

Use case scenario: Website Audit, Research, Analysis, and Technical Assessment
Usage: Find popular sites, entry/exit points, and metrics related to user engagement by analyzing traffic sources, user demographics, and behavior flow. Recognize regions of friction or pain points by understanding user journeys. Evaluate the performance of your website, taking note of conversion rates, bounce rates, and page load times.

2. Hotjar:

Use case scenario: Research, Analysis, Heat Maps, User Experience Evaluation
Usage: Use session recordings, user surveys, and heatmaps to learn more about how people interact with the website. Determine the high and low engagement regions and any usability problems, including unclear navigation or form abandonment. Utilizing behavior analysis and feedback, ascertain the intentions and preferences of users.

3. Crazy Egg:
Use case scenario: Website Audit, Research, Analysis
Usage: Like Hotjar, with Crazy Egg, you can create heatmaps, scrollmaps, and clickmaps to show how users interact with the various website elements. Determine trends, patterns, and areas of interest in user behaviour. To evaluate various design aspects and gauge their effect on user engagement and conversions, utilize A/B testing functionalities.

4. SEMrush:

Use case scenario: Research, Analysis, SEO Optimization
Usage: Conduct keyword research to identify relevant search terms and phrases related to the website’s content and industry. Analyze competitor websites to understand their SEO strategies and identify opportunities for improvement. Monitor website rankings, backlinks, and organic traffic to track the effectiveness of SEO efforts.

5. Similarweb:
Use case
scenario: Research, Website Traffic, and Demography, Competitor Analysis
Usage: By offering insights into the traffic sources, audience demographics, and engagement metrics of competitors, Similarweb facilitates website redesigns. It influences marketing tactics, SEO optimization, content development, and decision-making processes by pointing out areas for growth and providing guidance. During the research and analysis stage, use Similarweb data to benchmark against competitors and guide design decisions.

6. Moz:
Use case scenario: Research, Analysis, SEO Optimization
Usage: Conduct website audits in order to find technical SEO problems like missing meta tags, duplicate content, and broken links. Keep an eye on a website’s indexability and crawlability to make sure search engines can access and comprehend its material. To find and reject backlinks that are spammy or of poor quality, use link analysis tools.

7. Ahrefs:
Use case scenario:
Research, Analysis, SEO Optimization

Usage: Examine the backlink profiles of your rivals to find any gaps in your own backlink portfolio and possible prospects for link-building. Examine the performance of your content to find the most popular pages and subjects that appeal to your target market. Track social media activity and brand mentions to gain insight into your online reputation and presence.

8. Google Search Console:

Use case scenario: Technical Assessment, SEO Optimization
Usage: Monitor website indexing status, crawl errors, and security issues reported by Google. Submit XML sitemaps and individual URLs for indexing. Identify and fix mobile usability issues, structured data errors, and manual actions that may affect search engine visibility.

9. Adobe Analytics:
Use case scenario:
Website Audit, Research, Analysis,
Usage: Track user interactions across multiple channels and touchpoints, including websites, mobile apps, and offline interactions. Segment users based on demographics, behavior, and lifecycle stage to personalize marketing efforts and improve user experience. Utilize advanced analytics features such as path analysis, cohort analysis, and predictive analytics to uncover actionable insights.

10. Google Trends:

Use case scenario: Content Strategy, Keyword Research, User Intent Analysis
Usage: For competitor analysis, user intent analysis, and keyword research, Google Trends is used in website redesigns. It helps in content strategy, seasonal planning, SEO optimization, and strategic decision-making. It directs the production of user-centric content, increasing traffic and engagement, by spotting trends and insights.

About the Author:

Vijendra is currently working as a Sr. UX Designer at Mantra Labs. He is passionate about UXR and Product Design.

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