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Model selection with cross-validation: A quest for an elite model

3 minutes, 13 seconds read

What do you call a prediction model that performs tremendously well on the same data it was trained on? Technically, a tosh! It will perform feebly on unseen data, thus leading to a state called overfitting

To combat such a scenario, the dataset is split into train set and test set. The model is then trained on the train set and is kept deprived of the test set. This test set is utilized to estimate the efficacy of the model. To decide on the best train-test split, two competing cornerstones need to be focused on. Firstly, less training data will give rise to greater variance in the parameter estimates, and secondly, less testing data will lead to greater variance in the performance statistic. Conventionally, an 80/20 split is considered to be a suitable starting point such that neither variance is too high. 

Yet another problem arises when we try to fine-tune the hyperparameters. There is a possibility for the model to still overfit on the testing data due to data leakage. To prevent this, a dataset should typically be divided into train, validation, and test sets. The validation set acts as an intermediary between the training part and the final evaluation part. However, this indeed reduces the training examples, thus making it less likely for the model to generalize, and the performance rather depends merely on a random split. 

Here’s where cross-validation comes to our rescue!

Cross-validation (CV) eliminates the explicit requirement of a validation set. It facilitates the model selection and aids in gauging the generalizing capability of a model. The rudimentary modus operandi is the k-fold CV, where the dataset is split into k groups/folds and k-1 folds are used to train the model, while the held out kth fold is used to validate the model. Henceforth, each fold gets an opportunity to be used as a test set. This way, in each fold, the evaluation score is retained and the model is then discarded. The model’s skill is summarised by the mean of the evaluation scores. The variance of the evaluated scores is often expressed in terms of standard deviation.

5-fold cross validation

But is it feasible when the dataset is imbalanced? 

Probably not! In case of imbalanced data an extension to k-fold CV, called Stratified k-fold CV proves to be the magic bullet. It maintains the class proportion in all the folds as it was in the original dataset, thus making it available for the model to train on both, the minority as well as majority classes. 

stratified 5-fold cross validation

Determining the value of k

This is a baffling concern though!  Taking into account the bias-variance trade-off, the value of k should be decided carefully. Consequently, the k value should be chosen such that each fold can act as a representative of the dataset. Jumping on the bandwagon, it is preferred to set the k value as 5 or 10 since experimental success is observed with these values. 

There are some other variations of cross-validation viz.,

  1. Leave One Out CV (LOOCV): Only one sample is held out for the validation part
  2. Leave P Out CV (LPOCV): Similar to LOOCV, P samples are held out for the validation part
  3. Nested CV: Each fold involves cross-validation, making it a double cross-validation. It is generally used when tuning hyperparameters

Finally yet importantly, some tidbits that shouldn’t be ignored:

  • It is important to shuffle the data before moving ahead with cross-validation
  • To avoid data leakage, any data preparation step should be carried out on the training data within the cross-validation loop
  • It is preferable to repeat the cross-validation procedure by using repeated k-fold or repeated stratified k-fold CV for more reliable results especially, the variance in the performance metrics. 

Voila! We finally made it! If the model evaluation scores are acceptably high and have low variance, it’s time to party hard! Our mojo has worked! 

Further Readings:

  1.  5 Proven Strategies to Break Through the Data Silos
  2. Speech is the next UX
  3. The Next Big Thing for Big Tech: AI as a Service
  4. Insurtechs are Thriving with Machine Learning. Here’s how.

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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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