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Home»Opinion»Using Social Media Data In Life Insurance
Opinion

Using Social Media Data In Life Insurance

Nelson CamaraBy Nelson Camara2023-01-23No Comments5 Mins Read
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With more than 30 million South Africans active on social media, insurers have a wealth of unstructured data to tap into. Insurers can effectively ‘listen in’ to their customers, apply predictive modelling, and use the insights to gain a better understand of customer behaviour. In turn, this can result in improved customer engagement and experiences, and the development of more customised solutions that open new growth opportunities for the insurer.

In fact, enhancing the customer experience through an awareness of their preferences and sentiment at any given point in time can add immeasurable value to the insurer. An example of this is if a policyholder posts major life events that can range from getting married, starting a family, moving jobs, or even getting retrenched. The insurer can use this data to identify potential upsell and cross sell opportunities. In the case of a policyholder being retrenched, there might even be an option to provide them with payment breaks on their premium if they qualify.

Clearly, social media and its role in the insurance industry is evolving beyond marketing strategies and personalised ads. It now extends to encompass more advanced risk assessment and improving fraud detection capabilities, all while enabling new customer experiences.

Behavioural analysis

Social media can also be used to monitor customer behaviour.

As far back as 2019, people were cautioned about what they post on social platforms as this could have implications on their insurance policies especially when it comes to underwriting and pricing in the case of life insurance.

This is where technologies like artificial intelligence (AI) can play a significant role. For example, insurers can partner with third-party data vendors that use AI to scrape data from users’ profiles and build predictive models faster than human agents. These models enable underwriters to gain a more detailed assessment of an insured’s level of risk. It is here where sentiment analysis can be used to assess a client’s behaviour and flag any potential risks that require further investigation. Insurers can also use machine vision that uses software algorithms to assess images based on existing data sets already evaluated by humans. For instance, discovering more about a client’s lifestyle, including eating, exercise, and smoking habits.

It will soon become commonplace for local insurers to automate the mining of social media data for more efficient underwriting and claims processing. This must happen within the regulatory framework especially pertaining to the requirements of the Protection of Personal Information Act (POPIA).

Fraud detection

There are more nefarious cases where technology can be used to investigate fraud based on the content that is available on social media. A Morgan Stanley report cited a tool used by insurers to investigate claims throughout the assessment process that examines the social relationships between parties involved – and monitors their activity on the day of the loss to look for red flags.

Moreover, the report also highlights the need for insurers to rethink their customer engagement model. Thanks to the normalisation of connected devices, the opportunity to collect new data sets and assess risk in more innovative ways can transform insurance. When it comes to life insurance, actuarial risk assessments leveraging statistical techniques to structural risk modelling based on real-time observations can be crucial to more accurately underwrite and price policies.

As the Morgan Stanley report writes: ‘Similar changes are likely to be seen over time in health insurance and life protection. Insurers that seize these opportunities are likely to become the industry’s leaders, while those that do not could find themselves disadvantaged as the industry evolves.’

Change for growth

This is perhaps one of the most crucial points – adapt or risk being left behind. By focusing on how social media data analysis can enhance customer engagement, the insurer can develop a journey that results in greater loyalty, trust, and even advocacy where customers promote their positive experiences on their own social pages.

Insurers who therefore create a more personal experience for customers based on the data they share as well as the data that can be analysed from social posts, are the ones that create differentiation. Additionally, they give the customer a sense of comfort in that the insurer sees them as individuals as opposed to just a number in a database.

When it comes to using social media data, insurers need to ensure compliance from a regulatory perspective. While the likes of the Protection of Personal Information Act (POPIA) in South Africa does provide an element of protection, consumers still place a fair degree of trust in insurers when it comes to divulging their information and what that data is used for. Analysing social media data that is readily available online to raise (or lower) premiums must be done responsibly if the insurer is to maintain a positive relationship with the client.

Yes, social media data analysis will serve to inform the insurer about the major life events of its customers to identify opportunities to cross or upsell products and services in more organic ways. Insurers must be willing to embrace this social media data analysis and then act on it. But the business opportunities this can unlock make it something to incorporate throughout the insurance value chain when managed properly and not seen to be breaking people’s trust in the company.

  • Nelson Camara, Go-To-Market Executive at SilverBridge

Behavioural analysis fraud detection insurance insurer Life Insurance social emdia data
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Nelson Camara

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