Astronaut loading animation Circular loading bar

Try : Insurtech, Application Development

AgriTech(1)

Augmented Reality(20)

Clean Tech(5)

Customer Journey(12)

Design(36)

Solar Industry(6)

User Experience(56)

Edtech(10)

Events(34)

HR Tech(2)

Interviews(10)

Life@mantra(11)

Logistics(5)

Strategy(17)

Testing(9)

Android(47)

Backend(30)

Dev Ops(7)

Enterprise Solution(27)

Technology Modernization(2)

Frontend(28)

iOS(43)

Javascript(15)

AI in Insurance(35)

Insurtech(63)

Product Innovation(49)

Solutions(19)

E-health(10)

HealthTech(22)

mHealth(5)

Telehealth Care(4)

Telemedicine(5)

Artificial Intelligence(132)

Bitcoin(8)

Blockchain(19)

Cognitive Computing(7)

Computer Vision(8)

Data Science(17)

FinTech(50)

Banking(7)

Intelligent Automation(26)

Machine Learning(47)

Natural Language Processing(14)

expand Menu Filters

Intelligent Claims Automation Is Reshaping Malaysia’s Insurance Sector

Malaysia, drawn by its strong economic growth, expanding middle-class income and rising insurance penetration levels, is witnessing a new era of innovation – with AI leading the charge in bringing new and intelligent technologies to the mass-market.

According to Bank Negara, the country’s regulator of banks and insurers, life insurance penetration rate stood at 56% in 2018. Foreign insurers have been highly keen in this market despite lingering regulatory uncertainty over the sector’s foreign ownership rules, currently set at a 70% cap.

While ‘motor’ remains the largest class of insurance with a market share of 45.6%, followed by fire at 19.2% and marine, aviation and transit (MAT) at 8.2%; Takaful has been outpacing conventional insurance in the Islamic peninsula.

(Takaful refers to Islamic insurance products.)
Islamic insurance penetration rate in the country will likely touch 16% in 2019. In financial dealings, ‘takaful’ firms follow religious guidelines including bans on interest and monetary speculation and a prohibition on investing in industries such as alcohol and gambling.

Growth in the takaful business in Malaysia, the world’s second largest Islamic insurance market after Saudi Arabia, is backed by government efforts to reach out to the general consumer with affordable insurance coverage and the potential use of better technology as a disruptor.

AI is already poised to play a crucial role in Malaysia’s next big step. By 2021, Artificial Intelligence will allow the rate of innovation to almost double (1.8x) and increase employee productivity improvements by 60% in Malaysia, according to an AI study put forth by Microsoft & IDC-ASEAN Research Group.

While seven in 10 business leaders polled agreed that AI was instrumental for their organisation’s competitiveness, only 26% have embarked on their AI journeys. Those that have adopted AI expect it to increase their competitiveness by 2.2 times in 2021. Though, everyone agrees – every single interaction from here on is going to be digital.

Mckinsey Claims Automation Benefits

Malaysia is also moving towards a cashless society with infrastructure being put into place to facilitate e-payments which have more than doubled per capita from 2011 to 2019. For this, banking solutions in the region have ramped up digital investments so customers can take advantage of convenient and secure banking.

Intelligent Claims Automation

For insurers, claims settlement represents a large customer service touch point. However, taking a customer seamlessly through the claims resolution process is not always going to be simple.

Being an AI-driven insurtech enterprise means being able to fully utilize data and optimize business processes with powerful algorithms, creating the space for data-driven decision making. With AI, the claims process can be augmented using chatbots to convey support and status of a claim, and Machine Learning (ML) that can study large-volume patterns to reveal insights and detect fraud. Claims automation can be achieved at part or whole of the settlement process.

Claims Management Process

The Malaysian Insurance market is already witnessed to big insurers rolling out innovative products for customers, such as “Ask Sara” – AIA’s AI-powered enquiry channel that provides instant, real-time answers to agents anytime via Facebook Messenger. Integrating sensors into the value chain has also provided greater rewards with predictive modelling and data analytics, like Katsana – a telematics company that is enabling insurers to provide usage-based insurance based on driver’s performance data. These measures allow for safer, accurate and more affordable risk-based pricing for consumers.

The attitudes of the insurers and younger generations are shifting alongside their Asian peers, to a seemingly more AI-involved future. While the general insurance trade has witnessed nearly stagnant growth over the past several years, AI can help lower overheads and variable costs that will enable insurers to roll out affordable coverage, including to the under-served segment.


Enterprises benefit from our AI-first thinking.
We build AI roadmaps from scratch, guiding you all the way through your next transformational journey.

To learn how, drop us a line here: hello@mantralabsglobal.com


International Insurance Landscape

Cancel

Knowledge thats worth delivered in your inbox

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.

Cancel

Knowledge thats worth delivered in your inbox

Loading More Posts ...
Go Top
ml floating chatbot