The Impact of Big Data on South African Insurance
Big Data: noun Extremely large data sets that may be analysed computationally to reveal patterns, trends, and associations, especially relating to human behaviour and interactions.
Although Big Data has been making the rounds since the early 1990’s, it isn’t until recently that we’ve come to fully understand its benefits in identifying consumer needs within the insurance industry. However, Big Data is more than just a large volume of data used to analyse certain consumer characteristics in the hopes of making better, more informed decisions. For insurers, Big Data has the potential of completely transforming the way we ‘do’ insurance in South Africa. Big Data has the potential to add real value to clients by analysing exactly what they need, when they need it, how they need it, and for how long they need it, instead of making an estimated decision based on normal protocol. Knowing full well that trust goes a long way in any industry, especially in the insurance sector, it only makes sense to incorporate Big Data into operational processes in order to become a trusted partner with new and existing clients.
Here are four specific areas within the insurance model where Big Data can transform the way we ‘do’ insurance in South Africa:
- Micro-and on-demand- insurance:
Many South Africans don’t have the need for a long-term, comprehensive insurance policy, but rather something quick, simple and instant. Seeing as there is no such insurance service currently in South Africa, Big Data can find insights into this particular market in order to better serve consumers in the future.Similar to what British start-up Cuvva did in 2016 when they launched an innovative app-based insurance policy – enabling consumers to borrow friends’ vehicles allowing them to purchase a once-off insurance policy; whether for a day, a week, or even a simple once-off trip. Not only does this make sense for consumers who prefer instant service (as many do), but it’s also a great way to target a large demographic otherwise not reached. Big Data can deliver the stats needed in order to make an informed decision on whether or not this insurance model is viable to a specific insurer.
- Acquisition and onboarding
When it comes to hooking potential clients, one of the most difficult steps in creating a successful ‘sale’ is having the consumer release important, personal information needed to generate a reliable quote; unless they come to you. However, since 5% of insurance opportunities originate from digital channels (which may not seem like a large percentage until you start calculating the exact numbers) this leaves us with having to find a way to interest potential clients in such a way that allows us to know who exactly to target in order to avoid a waste of time and resources.Big data can match client profiles on social media and digital marketing channels by pairing up with 3rd party data sources; such as the Deeds office, credit bureaus, vehicle registration offices etc. This leads to potential clients not having to reveal much information in order to receive a reliable insurance quote; avoiding the step where you may lose a ‘sale’ due to scaring the client away.
- Claims management
The whole point behind consumers investing capital into an insurance policy is to receive assistance once something goes horribly wrong. Unfortunately, this is the part where the insurer struggles most keeping up with the demands of processing a claim within a reasonable timeframe. By employing ‘connected sensors’ into vehicles, homes, medical wearables etc. data is sent directly from the policyholder straight to the insurer alerting the insurance company of an accident. By then automatically relaying the message to emergency personnel, time wastage is eliminated and client service rises tremendously; not to mention the possibility of saving more lives. All of this may seem futuristic, but with Big Data, it’s possible.
- Health and vehicle insurance
Closely working together with claims management, Big Data has the potential to change the way consumers choose to live life. By collecting more accurate data in large amounts, insurers can offer advice on how to live healthier lifestyles; creating inter-personal relationships and improving client service without the need to ask a series of relevant questions.
Why is Big Data important?
The key to making anything work is to actually execute it. Big data is merely the collection of large volumes of information. What you do with that type of information is what’s going to make the difference. Big Data can answer questions relating to cost reductions, new product development, time reductions, and smart decision making. Combined with analytics, you can achieve the following:
- Recalculate risk portfolios in a fraction of the time.
- Evaluate the reasons behind failures or defects in near-real time.
- Determine specific consumer needs based on their buying habits.
- Most importantly, detect and stop potential fraudulent behaviour before any damage is done to an
One of the most important advantages of incorporating Big Data into the insurance industry is the ability to reduce and prevent insurance fraud; saving insurers millions in legal and investigative costs. Unfortunately, insurance fraud not only affects the insurer, but also causes suffering to the policyholder due to identity theft, hijacked policies, and an increase in premiums in order to compensate for cost incurred by the insurance fraud in the first place.
Here’s how Big data can reduce and prevent insurance fraud:
- Predictive analysis
Being able to predict which individuals are at a higher risk of committing fraud, insurers can prevent the need to do damage control. The ability to layer data modelling onto various platforms; including social media, client data, financial trends, and geospatial data, insurers are able to pinpoint individuals who may commit insurance fraud during the claims process.
- Image and voice recognition
Advances in such technologies now make it possible for insurance companies and call centres to implement advanced verification processes in order to determine the legitimacy of the client through voice biometric systems and photo evidence. Without Big Data, this may not be possible otherwise.
- Validate information earlier
Soft fraud, offering misguided information during the initial phases of onboarding a client, occurs on a regular basis due to potential clients seeking better rates or agents wanting to meet their targets. By integrating Big Data, insurers can cross-reference data from 3rd parties to validate the information given by the agents or potential client. This can prevent further problems down the line by accurately calculating risks from day one.
Big Data will not only transform the way we ‘do’ insurance in South Africa by using the principles of gamification, it also benefits consumers in the sense that they get what they need instead of what they pay for. It’s important for insurers to use Big Data within the insurance model by encouraging consumers to make healthier, more informed decisions through guidance, instead of making it seem as if their every move is being watched.
Apart from having to keep a close eye on the consumers’ ever-changing needs, insurers also need to find the correct technology in order to navigate their way around consumer protection laws, data privacy, and ever-evolving cyber security concerns. There’s a very fine line between making consumers feel taken care of and ‘stalked’, which is why it’ll be interesting to see which insurers are able to find the correct level of client care without scaring consumers away.
Although Big Data in the above-mentioned sense may seem somewhat futuristic and unattainable, it’s not only necessary to implement into future insurance models, it’s the way forward in order to do what insurance companies do best: provide reliable, comprehensive, and convenient insurance policies to suit the consumer’s needs.