Technology has meant that new sources of data have become available to the insurance industry in volumes that have not been seen before. But the challenge will be to utilise this data to drive intelligent business decisions that can reduce risk, increase efficiency, provide consumers with competitive policies, and increase profitability.

Big Data in insurance

The insurance industry has always used data and analytics to target and segment customers. However, the digitisation of society has opened up vast new sources of data that can be used to understand consumer behaviour in a deeper and more granular way. Being able to analyse the data available to them in more complex ways will be key to insurers continued competitiveness.

Machine learning in insurance

This new commercial focus for data analysis is where machine learning and artificial intelligence come in. These new sources of data are often unstructured and unstable and the biggest challenge facing insurers is how to make sense of the information and use it to develop useful insights. Machine learning offers many avenues to explore and leverage Big Data successfully.

6 ways machine learning and Big Data will impact the future of insurance

Both machine learning and Big Data promise to change the insurance landscape and have an impact on aspects of the insurance industry as diverse as marketing, risk assessment, fraud detection and day-to-day industry processes. Some of the biggest ways they are currently impacting the insurance industry include:

  1. Making it easier to appeal to new customers
    By analysing data related to customers online behaviour, insurance companies can create marketing campaigns that will better appeal to new customers. Big Data can also be used to help insurance companies process the feedback received from customers across multiple platforms and to gather insights from that feedback.
  2. Personalising products and pricing
    A deeper understanding of consumer needs provided by Big Data allows companies to offer personalised products to their customers based on their specific needs. By understanding customer behaviour and anticipating problems, insurers can also take advantage of opportunities for upselling.
  3. Supporting increased customer retention
    Using machine learning algorithms, insurers can predict problems and spot the signs of customer dissatisfaction earlier, allowing them to improve their services, solve issues and ultimately retain a customer’s business. For example, a data-led pricing strategy that can respond to customer expectations can increase retention rates by 15-20%.
  4. Improving risk assessment
    Insurers have always used customers’ data to assess risk. However, the use of Big Data, machine learning and analytics means insurers can make better, more confident decisions surrounding risk, increasingly important in a highly regulated market. Managing risk in this way increases efficiency and ultimately profitability.
  5. Better fraud detection
    An estimated £3.3million of fraudulent insurance transactions are detected every day in the UK insurance industry. Big Data can help insurers detect and prevent fraud using predictive modelling to compare profiles to known cases of fraud. Machine learning can also eliminate the possibility of human error in fraud prevention.
  6. Making internal processes more efficient
    Automation and the use of data algorithms can make insurance processes quicker and more efficient. Processes such as checking a customer’s claims history, assigning them to a risk class, processing claims and offering tailored pricing can all be automated. A study by McKinsey and Company estimated that around 43% of the time an insurance employee spends on repetitive tasks could be saved by automation.

Automation, machine learning and Big Data have the potential to save insurers time and money across several functions which will allow them to reduce customer premiums and stand out in a crowded market.

Davies Resourcing can help you leverage your technology

Getting the most from your data through machine learning will require specialist teams that are highly skilled in technology and data analytics and talent that may not have been traditionally drawn to the insurance sector.

Davies Resourcing can help you create a bespoke recruitment strategy that can source the specialist skills you need to drive your business forward. Specialist in the insurance sector we can accelerate your search and ensure the best possible fit for your business.

Please, get in touch to find out more about how we can help your business.

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Mandy Dhillon

HR Director

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