This is the age of data. This pandemic has forced us to find new ways to get our work done without putting ourselves in danger. Consumer buying behaviours have changed in order to adjust to this new normal in the post-pandemic world.
Before we talk about the changes in the business to navigate in the next two years, we should have a glimpse of the insurance business: What, How, and Why of the insurance business.
As we think of Insurance or Assurance, the first thing that comes to our mind is hedging of the financial risk in the event of the peril and uncertainty over the events faced during the journey of life. It involves two parties:
Insurance is the business of measuring the right estimate of chances of future occurrence of an uncertain event based on experience or research studies. The estimate has to be precise; an overestimate leads to overpricing of the product and no revenues. If the occurrence is underestimated, the insurer will incur losses as premium will not cover the outgo. In both circumstances, enterprises go out of business.
The estimation process requires two skills – one understanding of the event and factors affecting the events and the other skill to estimate. The last two years have changed the perception and likelihood of events affecting human life. Let us examine a couple of scenarios:
Until two years back, it was only a thought. In today’s geopolitical scenario, it appears to be a reality. To assess the damage, people will be re-analysing the data on the losses of World War II, losses, or damages that can be caused by today’s weaponry using various simulation techniques, earth imagery, and firepower strength with sophisticated testing in the laboratory environment. This all reflects rich and strong data analysis to estimate losses that go beyond the conventional framework. Today’s simulation will not only consider the losses to the army. Today’s losses constitute losses to the population at large - not limited to the area where it is fought but spreading to the nearby countries involved or not. Also, due consideration is given to the economic devastation of the world. The devastation will not be caused only during the war. It goes beyond because of the fall out of radiation, chemicals, etc. used during the war. This is all possible with the extensive availability of data, their co-relation studies, and resultant theories for the possible outcome.
The world is experiencing phenomena such as Cyclone Amphan in Orissa and West Bengal, and Nisarga on the western coast of India, which have not been experienced in the last century. To assess the damage and reason of occurring, a lot of data on geography, weather, and other global phenomena will be collected, researched, and analyzed to arrive at the possibility of re-occurrence, development setback at possible re-occurrence and damage estimation.
Some other unforeseen events like COVID-19 widespread, the return of migrant labourers to their home state, how many join back, etc. has jolted India. This will require a lot of data related to population, job opportunities, social security schemes, etc. to be analysed and published to give an insight into Indian society and their preferences in 2021 and onwards.
From the above, we can say that all the peril and risk will be re-evaluated by the Insurance and Reinsurance industry using the widespread data with a new thought and lens by the global multi-functional teams.
Now we can look at how the insured profile is changing and their preference in this technological age. For insurers, the population in the working-age group always attracts as they are the prime prospects for buying insurance products. India’s median age is 29 years, and China’s is 37 years. We can make that statement because someone studying global demographics and analysing data can make that statement. The same interpreted by the business analysts as India offers larger business opportunity as compared to China because India has a larger population in the working-age group and offer the potential to sell. The same is reflected in the population stats, where 15 to 65 share has grown from 63.41% in 2008 to 66.77% in 2018. This is nothing but the outputs of data analysis.
In India, the urban-rural divide was 70/30 in 2008; currently, it is 34/66. If you look at the population growth rates, the urban population is growing, but the birth rate there is lower than the rural population. All factors considered, it is stated that growth in the urban population is because of the migration of the younger generation for better education, employment, and other social facilities.
In the COVID days, there have been some forced or voluntary reverse migration of the population. As a result, this reverse migrated population will change the preferences of products, consumer buying behaviour, and particularly computer literacy in rural areas. This will open up different business opportunities that were not looked up because of technical (IT) infrastructure. TELCO will see some revenues and expand its offering, and the migrated population will likely experience the same customer experience as they did in urban areas.
Before expanding, every business entity will analyse which area has been impacted and to which class of migrants. This will only be possible with a lot of analysis on who has migrated from where to where using the social identifier like Aadhar Cards, MNREGA job cards, banking transactions, etc.
Consider the preferences for completing personal tasks such as purchases. Our parents would most likely go out on weekends or holidays and do the shopping for the home items. It used to be picnic day of the month for the kids. My generation likes to make online transactions, usually after work hours on a laptop or while watching TV. Preferences for these same tasks are changing. Next-generation is averse to using laptops and prefers to work on mobile devices, and completes the task while traveling. Marketing experts will put the numbers into all these behaviours. From where do they get these numbers? While using any electronic media – from DTH to laptop or mobile, we leave digital footprints and indicators of our preferences for specialists to collect, analyse, and devise products offering and messages.
We can conclude with confidence that we are now in the age of data. Whatever we do gets analysed, and we are conditionally trained based on past responses to respond to future situations. When humans are trained and conditioned by data analysis, then businesses will also be driven by data, analysis, and prediction using advanced technologies called Artificial Intelligence.
Artificial Intelligence has many facets under its umbrella - like statistical modeling for behaviour prediction/likes and dislikes, natural language processing to analyse whether someone is happy or not, facial recognition to recognize anomalies, etc.
Insurance business, which is artificial intelligence, will drive nothing but the statistical modeling and probabilities of events - nothing more, nothing less. Whoever invests early will be the winner of the race at the last mile.
Interested in learning how Aureus can help you leverage machine learning and time tested models to boost your risk control, productivity, capital efficiency in insurance operations? Click on the link below to get more information.