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FlowMagic — The Visual AI Platform for Insurer Workflows

For any operational effort across large organizations, a significant amount of time and resources are spent manually inputting data into downstream systems. These processes more specifically affect insurance practices that are deeply reliant on back-office processes. The bulk of the insurance workforce is condensed into operations and support functions (e.g. policy issuance and servicing). Here, data is typically unstructured and locked away in heaps of paper-based documents, emails, scanned images, excel worksheets, pdf, and word reports.

Typically in insurance, at least 90% of unstructured documents are manually processed, while an ‘Insurance Policy Administration System’ is on average between 15–20 years old — forcing them at times to lag behind their financial services peers. 

To make the most out of the massive quanta of inbound data stored in siloed systems, firms have recently begun to take a serious look at streamlining data migration using AI-based tools. The burgeoning reality is that a tremendous amount of man-hours are wasted in repetitive tasks leading to increased processing times and slower through rates for insurance.

Proportion of Unstructured Data in P&C Insurance (%)

portion of Unstructured Data in P&C Insurance (%)


Source: SPS Data

AI Gets Holed Up In Silos
According to a recent IDG study titled the ‘Future of Work’, less than 50% of global enterprises have deployed intelligent automation technologies (such as AI, Cognitive Automation or RPA), while over two-thirds find greater difficulty in integrating these people, process and AI. Over fifty percent of enterprises identify siloed deployments and overwhelmed internal application development teams as long-term issues. This can create friction between teams operating in silos and those trying to derive insights from unstructured docs. Nearly a third of enterprises identified getting AI into production and live services as the single biggest challenge to overcome.

According to a McKinsey paper, intelligent process automation is at the core of next-generation operational business models.

The Need For Intelligent Document Processing

The Need For Intelligent Document Processing


Source: Imaginea

A New Platform

MantraLabs has launched a unique solution to address the insurer’s pain-point through an intelligent platform built especially for silos, The solution addresses several dependency issues and is built to scale, making it a vendor-neutral platform that doesn’t require deep coding skills. The christened solution is FlowMagic — a simple and easy to use visual AI platform for insurer workflows.

FlowMagic applies proprietary AI techniques, Machine Learning and NLP, to extract any target data from unstructured documents. At the recently convened 4th Annual Insurance India Summit and Awards 2019 held in Mumbai, Mantra Labs presented a live demonstration of FlowMagic’s unique capabilities. Mantra Labs CEO Parag Sharma took the opportunity while speaking in front of industry leaders and attendees, to showcase our true AI-first approach to solving insurance challenges. FlowMagic truly embodies the spirit of that approach in tackling the problems plaguing traditional insurers — such as reducing document delivery times to the back-office by 80%.

FLOWMAGIC DASHBOARD

Customizable Workflows
The platform is equipped with plug and play capability. Using quick drag and drop, one can create custom workflows to address the most pressing operational functions, such as insurance agent onboarding or verifying medical invoices. Mantra Labs has pre-built over 50 AI-powered apps for its users to take advantage of. The open platform also allows insurers to create their own apps that can be seamlessly integrated.

FLOW MAGIC’s IN-BUILT APPS

By leveraging machine learning, insurers can use FlowMagic to shift intensive operational functions into auto-pilot. The AI tool can automate the ‘classify, extract, and validate’ cycle for insurers and direct decision-ready insights straight to decision-makers.

Although declining, the Insurance field is still paper-intensive. Insurers are shifting towards AI-powered engines to replace unnecessary manned effort behind redundant operational tasks. These systems can bring about at least a 70% reduction in manual processing and 30% improvement in cost-efficiencies throughout the value chain. 

To know more about how FlowMagic is helping insurance leaders cognitively automate complex processes, reach out to us at hello@mantralabsglobal.com 

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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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