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How Behavioral Psychology is Fixing Modern Insurance Claims

3 minutes, 56 second read

Human Behavior is inherently hard to predict and mostly irrational. Infact, this irrationality is often overlooked because it offers no meaningful insight or patterns behind our motivations. 

In the early 70’s, Israeli-American economist Daniel Kahneman challenged the assumption that humans behave rationally when making financial choices. His research explored the fundamentals of how people handle risk and display bias in economic decision-making. He would later be awarded the Nobel Prize for his pioneering work which provided the basis for an entirely new field of study called Behavioral Economics

Standard Economics assumes humans behave rationally, whereas Behavioral economics factors in human irrationality in the buying process.

Along with another scientific approach to studying natural human behaviors (Behavioral Science), both these fields became particularly useful to the financial industry early on. By understanding the deep seated motivations behind people’s choices, a specific interaction can be designed to influence an individual’s behavior — also known as behavioral intervention.

By finding meaningful patterns in Big Data, usually performed by a data scientist, businesses are able to leverage analytics and behavioral customer psychology. The outcomes of these insights can help business owners learn about the customer’s true feeling, explore behavioral pricing strategies, design new experiences and retain more loyal buyers. This is why Behavioral Scientists have become highly sought after over the last decade. 

The Rise of the Behavioral Scientist

Take for instance Dan Ariely, who is a Professor of Psychology & Behavioral Economics at Duke University, and also serves as the Chief Behavioral Officer of Lemonade — the World’s biggest Insurtech. Ariely observes that human behavior is ‘predictably irrational’ and constantly exhibits ‘self-defeating’ characteristics. There is a lot of value in studying these behaviors, for many organizations, to encourage positive ones, dissuade dishonesty and improve the underlying relationship.

The ‘dissuading dishonesty’ part is particularly useful for Insurance carriers. For a business that fundamentally deals with both people and risk, Insurance is endlessly plagued by fraud. Insurance fraud losses were estimated around $80B in 2019 alone. On the other hand, legitimate claim instances can at times be overlooked due to the lack of evidence or nuances in the finer policy details. 

To combat fraud during the claims process, Ariely added a simple ‘honesty pledge’ agreement before the beginning of the claims intimation process. A customer signs the digital pledge, and is then asked to record a short video explaining the incident for which they are requesting the claim.

The process seems naive but it’s backed by tons of data and science — a byproduct of decades of research work put into psychology and behavioral economics. 

So, How are claims being driven by data science?
How do insurers capture honesty from their customers?
The answer is priming.

By enforcing an honesty pledge, Lemonade was able to bring down the likelihood of fraudulent claims being intimated for. In other words, they made it harder for customers to lie. The hypothesis that works is: Don’t blame people for mistakes in decision making, it’s on the designers of the system

After the customer got done with their video recording, Lemonade ran 18 anti-fraud algorithms against the claim to check its veracity and a payment was made in a few seconds. 

Behavioral Priming in Insurance

Behavioral work is built on strong academic research that identifies aspects that influence the  buying process. ‘Nudges’ are a perfect example of behavioral priming at work. Nudge theory (a concept within Behavioral Science) identifies positive reinforcement techniques as ways to influence a person’s behavior and ultimately their decision-making.

For example, according to a study published in the Journal of Marketing Research, research subjects who were shown an aged image of their faces allocated twice the amount to their retirement savings when compared to people who were shown images of their current younger selves.

In this case, the ‘nudging’ technique was effective in driving retirement planning behavior among the test group. 


Source: Centre for Financial Inclusion

Behavioral Economics also stipulates that once you start doing something, you are more likely to continue doing so. This is how Netflix uses subtle nudges on their platform, where after each episode a prompt asks if you would like to continue watching the show.

Deriving New Value

Swiss Re’s Behavioural Research Unit outlines five promising areas where behavioral economics can create new value for insurers.

Digital businesses are gradually realizing the limitations of human and machine systems without any real intelligence or computing power behind it. Between human prone errors and the scalability challenges of traditional technologies, a new mechanism is required to learn and adapt better. 

Behavioral Science interventions in insurance can help carriers align their strategies with the true needs of their customers. Using the insights posited from advanced machine learning models, the right behavioral intervention can bring about changes to real-world insurance demand behavior that closely matches the benchmark model.

Also read – how InsurTech beyond 2020 will be different?

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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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