Articles - Personalisation – A new era in the digital age


Over recent years, customer experience expectations have been transformed. Digital disrupters such as Amazon, Netflix, Uber and Google have set a new standard with which all companies must now compete. Customers no longer just want a good level of customer service; they expect companies to predict what they would like to do next, pre-empting their next move and personalising their service offering accordingly.

 By Udi Ziv, CEO at Earnix 
 Like many other industries, insurers need to keep pace, not only to keep up with changing client demands but also to fend off competition from new insurtech disrupters who are redefining the status quo with their agile operational models. But how can insurers offer a more personalised service?
  
 The customer-centric revolution
 Over the last few years, digital transformation in the insurance industry has focused heavily on operational efficiency. Whilst this is set to continue, the next horizon is likely to center on customer-centric digital transformation.
  
 Customer-centric digital transformation will take personalisation to an entirely new level, not only in terms of customer engagement, but also for its ability to personalise product offerings based on an individual’s particular risk factors.
  
 Unlike many others, financial products often have a cost and profitability associated with an individual’s risk. Customer-centric digital transformation will see advanced analytics being used to address this issue by personalising the relationship between insurers and customers. Not only will this help drive customer engagement, but it will also increase profitability for insurers.
  
 Traditionally, in order to define price, insurers would focus on the similarities between customers. Now, in our data driven, consumer-centric age, insurers need to focus on what is unique about each customer. To do this, insurers need to delve deeper into their data and use more than just basic information like name, address, type of account, and how long a customer has been with a company to build a fuller, more accurate picture of the consumer.
  
 For example, to be more customer-centric, insurers need to consider every past interaction a customer has had with their firm, track the previous products they have bought, infer their preferences, and begin to use new forms of unstructured data such as IoT data to ensure they really understand each individual.
  
 By taking this approach, insurers will be able to understand their customers far better, which will make it much easier to predict what they want. This will enable firms to provide better solutions for customers, which will in turn drive consumer engagement. We only have to look at the success of customer-centric heavyweights like Amazon and Netflix to know that this model works.
  
 Putting it into practice
 At the core of customer-centricity is technology. To gain valuable insight from the deluge of data that is now available, insurers need to enlist the help of technology that can process this information and select the most valuable customer insights.
  
 However, as with many financial institutions, the digital transformation of insurance companies has not always been straightforward, as the business of writing and pricing risk is not easy to simplify. As a result, even though a lot of change has happened at the front end, the same old disparate legacy systems can be found chugging away behind the scenes, leaving valuable data siloed and inaccessible.
  
 To take a more customer-centric approach, insurers need to turn this model on its head by integrating the powers of AI and machine learning into existing systems. This way, their data will be able to deliver high-value, transformative activities such as real-time pricing changes for aggregators.
  
 By integrating AI and machine learning with their core systems, insurers will be able to apply the analytics required to deliver highly personalised product and pricing suggestions at hyper-speeds. AI and machine learning both have the ability to price risk on a one-to-one basis with surprising accuracy. As a result, these technologies have the potential to change the product and distribution processes offered by insurers significantly, giving those early adopters an edge over their counter-parts.
  
 Where to begin
 Over the last decade, many insurers have taken steps to overhaul their infrastructure and processes as part of their digital transformation strategies. However, this new era of artificial intelligence and machine learning is likely to mark a new revolution, driving new levels of responsiveness and customer engagement.
  
 Machine learning is expected to play an increasing part of our lives over the next decade, but today it is still focused on the areas where it can drive real business value. By initially applying it to pricing analytics, insurers will be able to see real business benefits very quickly. Pricing has a tremendous impact on sales and margins, both of which affect competitiveness. By beginning with price, insurers will therefore be able to provide customers with the benefits they want to see first.
  
 To stay ahead of changing customer expectations, insurance firms need to look at their current business models, assessing where they can offer customers a better, more personalised service. By implementing new technologies like AI and machine learning, insurers can leverage the expanse of data that they have at their fingertips to provide personalised pricing and product recommendations to customers, generating greater revenue and meeting their customers’ needs in the process.
  
  
  
 
  

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