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5 Deep Learning Use Cases for the Insurance Industry

4 minutes, 9 seconds read

In 2010, with the launch of the Image Net Competition, a vast dataset of about 14 million labeled images was made open-source to inspire the development of cutting-edge image classifiers. This was when Deep Learning technology got its a real breakthrough and since then there’s been no looking back for advancements in this field.

Different industries are actively using Deep Learning for object detection, features tagging, image analysis, sentiment analysis, and processing data at extremely high speeds. The bigger benefit that differentiates Deep Learning from other AI and ML technologies is the ability to train vast amounts of unstructured data in near real-time. Organizations with a strong focus on data are already about 1.5 times more likely to invest in Deep Learning for actionable insights — Forrester Predicts.

What makes Deep Learning Technology so sought after?

Let’s take a look at 5 Deep Learning use cases from an insurance perspective.

5 Noteworthy Deep Learning Use Cases in Insurance

Deep Learning (DL) is a branch of Machine Learning, which is based on artificial neural networks. DL techniques are specifically useful for determining patterns in large unstructured data. It is highly beneficial for assessing damages during an accident, identifying anomalies in billing, etc. that can eventually help in fraud detection and better customer experiences.

The insurance industry can leverage Deep Learning technology to improve service, automation, and scale of operations. 

1. Property analysis

Typically, insurers analyze a property only once before quoting an insurance premium. However, a customer may remodel the property, for instance, install a swimming pool. 

Under such instances, Insurers can proactively modify the insurance coverage with the help of deep learning technology. In fact, with DL technology, Insurers can help their customers with predictive maintenance, fault analysis, and real-time support. 

For example, Enodo provides underwriting for multifamily properties. It allows users to analyze historical rent, concession data, and market values. Such data-driven tools are also a great aid for insurers.

2. Personalized offers

Insurers are seeking different ways to enhance the customer experience. Deep Learning can vividly improve interaction experiences at different customer touch-points. Take for instance — marketing outreach. Through personalized recommendations and dynamic remarketing strategies, insurers can achieve better conversions. McKinsey states that personalization can reduce customer acquisition costs by up to 50%

At the core of these strategies lies Deep Learning technology. DL technology can make logical classifications of unstructured data through unsupervised learning. We’ve already seen product recommendations based on our own preferences, browsing/search patterns, and peers’ interests. The same applies to the insurance industry, especially when insurers endeavor profits through bite-size and on-demand insurance products.  

3. Pricing/Actuarial analysis

Actuarial analysis and evaluation are both time-consuming and error-prone processes. Insurers can considerably improve policy pricing through automated reasoning. Deep Learning techniques combine statistics, finance, business, and case-based reasoning and can assist actuaries in better risk assessments. Accenture reports — Insurers are leveraging machine learning for underwriting in P&C (56%) and life (39%) insurance sectors

  1. Explainable AI (XAI) is capable of adopting and implementing AI across all capacities of the actuarial profession. 
  2. Pattern recognition from historical data can help assess the risk and understand the market better.
  3. Deep Learning can help in pragmatic actuarial solutions to make effective decisions on large actuarial data sets.

4. Deep Learning Use Cases in Fraud Detection

In Norway alone in 2019, there were 827 proven fraud cases, which could have caused a loss of over €11 million to insurers.

Insurance fraud usually occurs in the form of claims. A claimant can fake the identity, duplicate claims, overstate repair costs, and submit false medical receipts and bills. Mostly because of disconnected information sources, Insurers fall victim to fraudulent activities from customers. Now, here’s the challenge. How to unify different data sources, which, to date, even include offline receipts and manually scanned documents. 

Deep Learning can help in fraud detection by-

  • Finding hidden/implicit correlations in data.
  • Facial recognition, sentiment analysis on submitted claims application.
  • Supervised learning to train the fraud detection models using labeled historical data.
  • Eliminating the time lag in the verification of documents, which raises the potential for data breaching.

5. Claims

Deep Learning incorporates two-fold benefits to insurers in terms of claims. One — with a connected information ecosystem, it helps insurers with faster claims settlement (thus, customer experience as well). Two, deep learning predictive models can equip insurers with a better understanding of claims cost. 

For example, Tokio Marine — the largest P&C insurance group in Japan uses a cloud-based document processing system to process handwritten claims from the time of the first intimation. Many insurers are looking forward to end-to-end claims processing systems with deep learning and other AI capabilities. 

The Crux

Today, Deep Learning technology is able to mimic an infant’s brain. The research is on for developing new neural network architectures (e.g. Siamese Network, OpenAI’s GPT-2 Model, etc.) that will be capable of performing complex functionalities of a mature human brain. Deep Learning technology, in the near future, will be leading the development of cognition-based insurance systems.

Also read — The Cognitive Cloud Insurer is Next!

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How Smarter Sales Apps Are Reinventing the Frontlines of Insurance Distribution

The insurance industry thrives on relationships—but it can only scale through efficiency, precision, and timely distribution. While much of the digital transformation buzz has focused on customer-facing portals, the real transformation is happening in the field, where modern sales apps are quietly driving a smarter, faster, and more empowered agent network.

Let’s explore how mobile-first sales enablement platforms are reshaping insurance sales across prospecting, onboarding, servicing, renewals, and growth.

The Insurance Agent Needs More Than a CRM

Today’s insurance agent is not just a policy seller—they’re also a financial advisor, data gatherer, service representative, and the face of the brand. Yet many still rely on paper forms, disconnected tools, and manual processes.

That’s where intelligent sales apps come in—not just to digitize, but to optimize, personalize, and future-proof the entire agent journey.

Real-World Use Cases: What Smart Sales Apps Are Solving

Across the insurance value chain, sales agent apps have evolved into full-service platforms—streamlining operations, boosting conversions, and empowering agents in the field. These tools aren’t optional anymore, they’re critical to how modern insurers perform. Here’s how leading insurers are empowering their agents through technology:

1. Intelligent Prospecting & Lead Management

Sales apps now empower agents to:

  • Prioritize leads using filters like policy type, value, or geography
  • Schedule follow-ups with integrated agent calendars
  • Utilize locators to look for nearby branch offices or partner physicians
  • Register and service new leads directly from mobile devices

Agents spend significantly less time navigating through disjointed systems or chasing down information. With quick access to prioritized leads, appointment scheduling, and location tools—all in one app—they can focus more on meaningful customer interactions and closing sales, rather than administrative overhead.

2. Seamless Policy Servicing, Renewals & Claims 

Sales apps centralize post-sale activities such as:

  • Tracking policy status, premium due date, and claims progress
  • Sending renewal reminders, greetings, and policy alerts in real-time
  • Accessing digital sales journeys and pre-filled forms.
  • Policy comparison, calculating premiums, and submitting documents digitally
  • Registering and monitoring customer complaints through the app itself

Customers receive a consistent and seamless experience across touchpoints—whether online, in-person, or via mobile. With digital forms, real-time policy updates, and instant access to servicing tools, agents can handle post-sale tasks like renewals and claims faster, without paperwork delays—leading to improved satisfaction and higher retention.

3. Remote Sales using Assisted Tools

Using smart tools, agents can:

  • Securely co-browse documents with customers through proposals
  • Share product visualizations in real time
  • Complete eKYC and onboarding remotely.

Agents can conduct secure, interactive consultations from anywhere—sharing proposals, visual aids, and completing eKYC remotely. This not only expands their reach to customers in digital-first or geographically dispersed markets, but also builds greater trust through real-time engagement, clear communication, and a personalized advisory experience—all without needing a physical presence.

4. Real-Time Training, Performance & Compliance Monitoring

Modern insurance apps provide:

  • On-demand access to training material
  • Commission dashboards and incentive monitoring
  • Performance reporting with actionable insights

Field agents gain access to real-time performance insights, training modules, and incentive tracking—directly within the app. This empowers them to upskill on the go, stay motivated through transparent goal-setting, and make informed decisions that align with overall business KPIs. The result is a more agile, knowledgeable, and performance-driven sales force.

5. End-to-End Sales Execution—Even Offline

Advanced insurance apps support:

  • Full application submission, from prospect to payment
  • Offline functionality in low-connectivity zones
  • Real-time needs analysis, quote generation, and e-signatures
  • Multi-login access with secure OTP-based authentication

Even in low-connectivity or remote Tier 2 and 3 markets, agents can operate at full capacity—thanks to offline capabilities, secure authentication, and end-to-end sales execution tools. This ensures uninterrupted productivity, faster policy issuance, and adherence to compliance standards, regardless of location or network availability.

6. AI-Powered Personalization for Health-Linked Products

Some forward-thinking insurers are combining AI with health platforms to:

  • Import real-time health data from fitness trackers or health apps 
  • Offer hyper-personalized insurance suggestions based on lifestyle
  • Enable field agents to tailor recommendations with more context

By integrating real-time health data from fitness trackers and wellness apps, insurers can offer hyper-personalized, preventive insurance products tailored to individual lifestyles. This empowers agents to move beyond transactional selling—becoming trusted advisors who recommend coverage based on customers’ health habits, life stages, and future needs, ultimately deepening engagement and improving long-term retention.

The Mantra Labs Advantage: Turning Strategy into Scalable Execution

We help insurers go beyond surface-level digitization to build intelligent, mobile-first ecosystems that optimize agent efficiency and customer engagement—backed by real-world impact.

Seamless Sales Enablement for Travel Insurance

We partnered with a leading travel insurance provider to develop a high-performance agent workflow platform featuring:

  • Secure Logins: Instant credential-based access without sign-up friction
  • Real-Time Performance Dashboards: At-a-glance insights into daily/monthly targets, policy issuance, and collections
  • Frictionless Policy Issuance: Complete issuance post-payment and document verification
  • OCR Integration: Auto-filled customer details directly from passport scans, minimizing errors and speeding up onboarding

This mobile-first solution empowered agents to close policies faster with significantly reduced paperwork and data entry time—improving agent productivity by 2x and enabling sales at scale.

Engagement + Analytics Transformation for Health Insurance

For one of India’s leading health insurers, we helped implement a full-funnel engagement and analytics stack:

  • User Journey Intelligence: Replaced legacy systems to track granular app behavior—policy purchases, renewals, claims, discounts, and drop-offs. Enabled real-time behavioral segmentation and personalized push/email notifications.
  • Gamified Wellness with Fitness Tracking: Added gamified fitness engagement, with rewards based on step counts and interactive nutrition quizzes—driving repeat app visits and user loyalty.
  • Attribution Tracking: Trace the exact source of traffic—whether it’s a paid campaign, referral program, or organic source—adding a layer of precision to marketing ROI.
  • Analytics: Integrated analytics to identify user interest segments. This allowed for hyper-targeted email and in-app notifications that aligned perfectly with user intent, driving both relevance and response rates.

Whether you’re digitizing field sales, gamifying customer wellness, or fine-tuning your marketing engine, Mantra Labs brings the technology depth, insurance expertise, and user-first design to turn strategy into scalable execution.

If you’re ready to modernize your agent network – Get in touch with us to explore how we can build intelligent, mobile-first tools tailored to your distribution strategy. Just remember, the best sales apps aren’t just tools, they’re growth engines; and field sales success isn’t about more apps. It’s about the right workflows, in the right hands, at the right time.

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