2 min read
In the financial services industry, reliance on big data has been increasing at a global level. The usage is not limited to marketing purposes alone but extends to fraud and risk prevention.
Customer demand for personalised products is responsible for this shift. The future of insurance is also being shaped differently due to this. The current lengthy questionnaires won’t be needed at all. Just the data collected will help to accurately predict risk and create policies customised to the person’s needs.
But, a bid to fulfil these demands has paved the way for something less desirable as well i.e. decreased customer privacy.
Where social media comes in the picture
So, how is social media being used to capture big data and to personalise products? Here are three ways:
Personality profiling through social media
In 2016, the insurance company Admiral wanted to use Facebook for determining motor insurance premium rates. By monitoring and analysing the language people use on Facebook, they could gauge their personality and how dangerously people would drive. This would help them set customised premium rates.
The company faced criticism for their experiment and Facebook even announced that the product would be blocked for violating Platform Policy. The backlash made Admiral change tactics and instead of monitoring social media, they introduced a personality quiz.
Planning loans and loan amounts
The use of social media intelligence is typically aimed at people whose financial data hasn’t been available in the past. This means their credit history is low or practically non-existent. Which sectors fall into these categories?
For now - until sufficient data is collected about them - it is the poor and the young.
Apparently, people belonging to these demographics have to reveal more about themselves if they are to be provided with a loan or premium quotation.
Do certain economic and demographic groups need to be subjected to reduced privacy so that social media intelligence can be implemented effectively?
The (unthought of) effects of social media intelligence
The crucial question now arises: how would basing premium and loan rates on social media intelligence prove beneficial in the long run?
If a person knows that their social media posts, engagement, location, etc. are being monitored to determine their financial standing, who is to say that they won’t change those things? Will we able to tell if someone is posting something out of genuine desire or because they have to purchase a car in 6 months?
Honesty and transparency in the social media realm would decrease as customers seek to project a more reliable image. There is no effect on increasing road safety or encouraging responsible driving which is what ultimately leads to reduced motor claims.
Conclusion
All in all, social media intelligence can prove fruitful but it doesn’t come without its cons. The disruption of customer trust is the biggest one. Are insurance companies willing to risk that happening?
Spixii intelligent chatbot can analyse customer behavior throughout the whole insurance journey conversations. It can generate multiple data points that can be interpreted and wrapped into actionable insights. These behavioral insights on how to improve chatbot conversation and the insurance process are derived from anonymized data hence compliant with the privacy rules.
Most crucial of all, insurers can be on the right side of compliance laws like GDPR and IDD (Insurance Distribution Directive) and the right side of their customers’ trust in them.
