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InsurTalks Podcast with KV Dipu: Protecting the Demand-side in the New Normal

7 minutes, 26 seconds read

The outbreak of Covid-19 pandemic has deeply impacted the global economy. Industries such as healthcare, travel and hospitality among others are still reeling from the immediate fallout of the crisis. The Pandemic has exposed the cracks in the Indian healthcare system, and the exposure of India’s masses to a multitude of personal risks who are largely uninsured to stave off financial ruin. At the same time, Insurance has had to adapt their processes to the fast changing climate. Core insurance functions like claims processing and customer support operations have had to accelerate transition to the cloud in order to ensure operational continuity during the crisis and adapt to the new normal. 

In this special podcast, we talk to Mr. KV Dipu about how Insurance is coping with this crisis. Before joining Insurance, he worked at GE Capital for 19 years, where he has built a career in retail finance operations. He is a certified Lean Six Sigma Black Belt and a member of the Harvard Business Review Advisory Council. Today he drives digital transformation as the President of Operations, Communities, and Customer Experience at Bajaj Allianz.

During our conversation Mr. Dipu shared valuable insights on the state of insurance, how insurers need to gear up for the challenges in the New Normal and the initiatives undertaken by Bajaj Allianz to meet their customer’s expectations.

You can watch the full podcast here: 

Interview Excerpts from Insurance in the New Normal

Potential Insurance Frauds amidst COVID-19

Insurance, at least in India, is not strange to the experience of dealing with outbreaks even though at a smaller scale – with virus outbreaks like Ebola & Zika in the past. However there aren’t too many reliable historical models to learn from and you’ve stated in the past that fraud triggers can only work if there are strong flags sitting on top of really good data. In the absence of really good data and unreliable historical models, how does this affect dealing with fraud?

KV Dipu: That’s a good question and I think this is exactly what a lot of players today across industries are grappling with because no PCP or model ever envisaged this. And if you do not have passed precedents then you have to learn as you go. So I think that is clearly what we have seen. In terms of COVID-19, you can see a series of potential fraud possibilities. 

I’m using the word ‘potential fraud possibilities’ because we have to see how they play themselves out. One is you could find a lot of people who possibly could get into scams, that they can maybe influence the entire ecosystem, especially in terms of helping customers who are seeking benefits from the insurance company or various entities. And whenever there are losses you typically will find that there are people out there who are going to try to to make a fast buck. So I think that’s one area we need to watch out for. 

The other is you will actually find that as business models emerge there are some people who’ll be quick to jump into the game. For example, today everybody feels that health insurance is one thing we should focus on and that’s typically when you could have both type A and type B errors. You have middlemen who basically promise health insurance saying ‘I can get you this.. I can have my way through various insurance companies’. You may have people trying to forge various checkups through the entire process. 

So these are some areas which we are very off, right, and the good thing is even if a model from the past is not going to help us with the specific input I think our own experience of various scenarios will come into play.I think as long as we are smart on that front it will help us. Now this is where it’s a classic combination of technology and expertise technology can enable the process but you need years of experience to figure out the fraudulent ones from the good ones. Which is where I think established companies like ours which are technically and technologically savvy, as well as years of deep expertise will be really able to figure out who the fraudsters are.

Change in the Nature of Risks & Its Impact on Underwriting

From an underwriting perspective it’s usually said that poor underwriting leads to poor financial performance, so the ‘not knowing what to expect’ will definitely have an impact on underwriting losses. Going forward, how does this change the nature of risk from perhaps the actuaries point of view? 

KV Dipu: If you look at actuarial science, what they do with every event is they learn, right. The learning adds to their kitty, so to speak. So, today you have various players globally trying to figure out what the models are, what are the potential scenarios and we can also learn from the experiences of different countries. You see while it’s still a global pandemic, the scenarios across various countries are different. Some countries for example have had a very sharp recovery, where they’ve shown a v-shaped recovery. Now there are some countries which are in a u-shape recovery pattern, and  there are some where there is a recovery-outbreak-and then a recovery which would be a W pattern. 

So I think as we see the scenarios play themselves out in various countries, we draw learnings very quickly and then basically recalibrate our models accordingly, that’s point number one. Point number two – I think once the lockdown is lifted and then when you start to see people back on the roads, when you start to see cars back on the roads, and when you start to see hospitals functioning again – that is when I think the rubber will start hitting the road and that is when our extreme vigilance will help. I think as long as we’re prepared with data it will really help us get through this.

[Related: New Product Development in Insurance: The Actuary]

Product Innovations in the New Normal

Today a lot of companies are ‘investing in digital’. They’re making sure they have digital assets, capabilities and tools not just for employees internally in the business but for outward facing agents as well. And that has been  the trend even before the Pandemic had broken out. Most sales teams and channel partners are equipped digitally with mobile apps to generate quotes, issues policies even remotely. 

Given that the physical act of selling itself has been severely affected due to lockdown restrictions and social distancing norms, How can insurance build and protect the demand side?

KV Dipu: Okay, so there is one famous whatsapp forward doing the rounds nowadays. it basically says “Guess who’s responsible for digital transformation in a company? Answer number one: CEO. Answer number two: the relevant CXO. Answer number three: COVID-19.” No prizes for guessing, right? Now what COVID-19 has done is to the point that you made everybody believe that in a push product like insurance in-person meetings, relationship building  is all important and rightly so. And that is the reason this business is intermediated and it’s been that way for a while now. New normal is where people will have to learn how to do contactless selling. That is where COVID-19 helps because if let’s say COVID-19 had been restricted to let’s say one particular city or one particular sector you would not have had a change in universal behavior. 

But the fact of the matter right now is globally right I think there are more people under lockdown than at any previous point of time in history. We have so many people on lockdown and everybody realizes the need for social distancing and the need to go digital. That is when people are also more amenable to being sold to digitally. Which is why now the smarter companies who figure out that in the new normal we have to build relationships while being physically away, and manage to sell from remote or contactless sales as i call it – are the ones who will be able to make a difference going forward. 

The good thing is from a process perspective we have enabled them like you rightly said they have the tools to generate quotes, they have the tools to issue policies, they have the tools to even raise claims. It’s about willingness and that willingness has been accelerated and fast tracked by COVID-19. So what could have potentially taken a long time has now been fast-tracked now in the last 60 days – which is why once the lockdown is lifted and we go back into the world you’ll realize that some parts of this contactless selling or even large parts of it are here to stay.

Click on the below link to watch the full episode of InsurTalks with KV Dipu –

Mantra Labs is an InsurTech100 firm building products and solutions for fast evolving enterprises. To connect with us for interviews, drop us a line 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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