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New age technologies such as AI, ML & NLP are poised to reimagine the entire insurance lifecycle from customer acquisition to claims processing. 

The Artificial Intelligence (AI) market was valued at USD 16.06 billion in 2017 and is expected to reach USD 190.61 billion by 2025, at a CAGR of 36.62% during the forecast period. Asia pacific region would exhibit the highest CAGR of 59.8% during 2018-2025. 

KPMG’s Insurance practice estimates that AI will reduce accident frequency by 80% by 2040. This will result in a potentially drastic reduction in loss costs and premiums.

Many insurtech are leveraging AI technologies to slash costs, speed response times and improve customer service. Here are some of the top 10 use case where AI can be leveraged in Insurance

1. Usage Based Insurance / Behavioural Policy Pricing: IoT sensors will provide personalized data to pricing platforms, allowing safer drivers to pay less for auto insurance and people with healthier lifestyles to pay less for health insurance. 
2. Customer Experience: AI will enable a seamless automated buying experience, by leveraging on customers’ geographic and social data for personalized data.
3. Customized Claims Settlement which is faster: Virtual claims adjusters along with Online Interface will make it more efficient to settle and pay claims following an accident. This will also help in simultaneously decreasing the likelihood of fraud.
4. Chatbots/AI assistants: Having Chatbot to respond to customer and also settle claims without human intervention will create an Insurance experience that is fast, simple and delightful.  
5. Re-imaging Claim Processing: Use image recognition software or computer vision to settle auto claims without the need for a visit from an adjudicator. Home sensors, drones and smart devices will often generate a first notice of loss (FNOL) before the customer needs to contact the insurer
6. Better Claim management process: AI can identify patterns in data and help identify fraudulent claims in the process. Using machine learning capabilities business can capture patterns and traits that would be invisible to the human eye
7. Customer Care done right: Use AI Capabilities to improve the process of Customer care during the process of filing a claim with the call center team
8. Customer Segmentation: AI perform customers’ segmentation according to their financial sophistication, age, location, etc.
9. Customer Lifetime Value Prediction: Using AI algorithms to predict the likelihood of the customers’ behaviour and attitude, maintenance of the policies or their surrender.
10. Claim Prediction: Forecasting the upcoming claims helps to charge competitive premiums that are not too high and not too low. It also contributes to the improvement of the pricing models. This helps the insurance company to be one step ahead of its competitors.

McKinsey found that 82% of enterprises adopting machine learning and AI have gained a financial return from their investments. 

At the same time one of the key concern introducing new technologies will be in convincing the public that automation isn’t simply a Trojan horse for denying their claims — a worry that 60% of consumers have expressed about purchasing coverage via chatbot, according to a recent survey by Vertafore.

Red ocean are all the industries in existence today. It’s a known market space, where industry boundaries are defined and companies try to outperform their rivals to grab a greater share of the existing market. Cutthroat competition turns the ocean bloody red. Hence, the term ‘Red’ ocean.

Blue Ocean denote all the industries not in existence today. It’s an unknown market space, unexplored and untainted by competition. Like the actual ‘blue’ ocean, it is vast, deep and powerful –in terms of opportunity and profitable growth.

It’s imperative that all markets will turn to Red ocean at some point. When that happens to survive some of below strategies will help.

1. Be Different: New product features may be enough to differentiate the product, and enter a world free from competition, even within a competitive industry. As far as possible define your differentiation or explore a specific niche within the mature industry
2. Target Demographics: You can also target a different demographic, or capitalize on consumer preferences that aren’t being met by the leading competitors. Focus on the demography what you are comfortable with
3. Price Points: If all your competitors are selling something around the same price, you could easily capitalize on their existing audience by offering the product at a cheaper price.
4. Geographic Location: You could also feasibly find more opportunities in a different geographic area. If there’s a specific business, product, or service that’s popular in one area of the country, you could bring it to a location that’s unfamiliar with it.
5. Peripheral Services: It’s also possible to stand apart from the competition by offering services that aren’t available from mainstream competitors.
6. Increased visibility: Being different immediately helps you stand out. Capitalizing on what makes you different from the major players in a mature industry is a strategy certain to attract attention. This will aide you in your marketing and advertising efforts.
7. Leveraging Untapped Channels: There are invariably marketing and advertising strategies that your main competitors aren’t currently using.
8. Piggy back on existing brand value: As long as you aren’t lying about your competitors, you can mention them directly in your marketing and advertising campaigns, as a way to capitalize on the brand value they’ve already established.
9. Competitor Reduction: If you are following all the above steps, you are already charting a path of your own which instantly reduces the number and ferocity of competitors you’ll face.

As is normally the case, timing is everything. How do you know when is the right time?

1. Conflicting Beliefs: When there is a conflict inside red ocean, That’s an amazing opportunity to enter
2. Too Many Product Options: And when you start to see tons of products competing on ‘better,’ that’s one way to know that the Red Ocean is ripe.
3. Customer Innovation: If customers are starting to innovate on the products in the Red Ocean then its right time
4. Rise of C-level influencers: When you see the rise of C- level influencers. The third tier influencers; that’s a big sign that you’re ready to branch out and take people from the Red Ocean to a new Blue Ocean

Strategy is about making choices, trade-offs; it’s about deliberately choosing to be different. – Michael Porter

Had been to my local milk booth. Lady at the shop had payment stickers for @Paytm & UPI. At the end of my shopping i asked if i could make the payment through @Paytm, she said “NO“, she needs cash.

I asked then why has she put stickers of Paytm & UPI? for which she replied that it was put by her boss and she does not use it. She literally told me “Boss stickers hakthare and nanu stickers thegithini” which basically means “Boss puts the stickers (payment options) & i keep removing all the stickers“.

I asked her for the reason and she had a genuine concern, she said

1. She does not understand it, especially when there is a failed transaction it is difficult to handle
2. Milk van from Dairy does not accept @Paytm and she needs cash to pay him. If she takes only @Paytm, then she will not have any cash to pay.

Thinking about this, it made sense. Digital transactions dont work unless complete chain accepts the same. I started thinking have we gone back to pre-demonetization era? What do you guys think? how do we solve these challenges?

I have been in Project / Program management for close to 11+ years. Over the last few years, there has been Increasing push to move from Waterfall to Agile development. I have seen companies jumping to make this shift without knowing exactly if Agile is the right approach for them. Have come across instances where Agile is Force Fit into the teams whereas Iterative waterfall would have been a better approach. Overall there is a feeling that “Agile” is the Magic Pill for all problems.

With this approach we are running the RISK of not only diluting the meaning of Agile but also implementing something which is not right. Some of the common issues i have seen

• Burnout of the project team while catching up on the lost time without change in Scope
• Having the team Idle waiting for some key Governance decisions to be made
• Un-synchronized backlog between different development team (Data, IT, Training, Deployment..etc)
• No common Definition of Done (DoD) between Company & the Vendor
• Confusion between Incremental Development vs Detailed Documentation
• Adding Unwanted overhead in terms of additional Monitoring & Reporting

What we need to realize is that each of the process has its own Pro’s and Con’s and its important to understand this and choose the one which is right for the job to be done. Ideally this depends a lot on the type of the Project and the Organization setup. When this decision needs to be made, it would be wise to take help of experts who have experience in this area and always ask the question, “Are we making the process Simple or Complex?”.

Overall Agile is broadly assumed to provide Productivity Improvements but Agile at scale for large projects should not be the de facto choice. As per me this decision should not be an organization binding but instead left to each Project team to decide. Though this will be little difficult to track and manage from a reporting perspective but this should be the way to go.