Like many sectors, insurance could really benefit from a deeper understanding of its customers. But other sectors are perhaps not as under threat as insurance, with fintech revolution giving rise to smaller and more agile startups are able to offer a variety of new services to consumers and businesses. These services are not only more interactive and based on the latest technologies, but they are also services that bigger insurance firms cannot easily offer.
This increased competition from newer market entrants is a growing problem for more established insurance providers. But with more data available to insurance firms than ever before, there is an opportunity to understand their customers better and ward off the emerging threat from fintech startups.
Effective use of data in insurance
Insurance is an industry that has always been awash with data, and that is only going to increase in data volume and breadth. This is why so many insurers have invested in Customer Relationship Management (CRM) systems.
The data available on insurance customers is rich in insight, insight that if deployed correctly would allow insurance firms to really understand the needs of those customers and address any issues before they arise. But even when deploying CRM, the industry has traditionally struggled to really monetise this asset, held back by a combination of regulatory concerns, a lack of technological know-how and a reluctance to adopt a business model that truly reflects the value of data.
Now that technology has evolved to help insurers with data analytics, so the value of data has increased exponentially. Some insurers have in fact got to grips with structured data – data that comes in a format and file type that is easily stored, managed and accessed by CRM systems– but the reality now is that the most insightful data available to insurers is now unstructured, such as social posts, emails, web pages and call centre transcripts.
The value of unstructured data
Unstructured data is potentially enormously revealing to insurers, yet most CRM systems are not capable of storing and managing unstructured data. It comes in such a wide variety of formats and even the world’s biggest CRM firm Salesforce has estimated that only 1% of a company’s data is used by its CRM system.
Another issue is that insurers store their customer data in a multitude of different enterprise systems. It is not uncommon for an insurer – whether offering retail, corporate or reinsurance services – to have two different structured databases (one for pricing and one for contracts) in addition to other systems to store customer data.
This means that even finding customer data can be a challenge, before insurers can even think about extracting actionable insight from it. With no 360-degree view of customers and a real inability to search data in a multi-org environment, there is a widespread lack of customer understanding which can have a significant impact on customer churn, as well as lead generation and lead prioritisation.
Deploying AI to mine unstructured data
Any insurer seeking to get maximum value from its data should be developing and shaping their business to put data at the core. This is not a small undertaking, but given the economic potential of data, a step that should be on the agenda for all business leaders within insurance.
A good place to start when addressing the unstructured data that holds so much insight for insurers, is in utilising artificial intelligence (AI). AI uses advanced machine-learning algorithms to create an analytic power far greater than anything used previously, meaning it can extract great insight from data.
A key use of AI is to understand customers much more comprehensively. Not only can AI manage unstructured data but it can also work in a multi-org environment, capturing data stored in different and disparate enterprise systems. This means that customer issues can be identified in advance and makes cross-selling and up-selling an easier task. Service is improved, churn is reduced, and customer retention is increased.
Some insurers have certainly made progress when deploying AI and machine learning to their structured data, and extending that to unstructured data could help established insurers ward off the threat from insurance-based startups, and transform the industry in the process.
About Dorian Selz
Dorian Selz is a serial entrepreneur. Today he is co-founder and CEO of advanced context intelligence and insights solution provider Squirro. Previously, he was co-founder and CEO of local.ch, the leading local search platform in Switzerland. Squirro works with organisations all over the world, using AI and ML to deliver actionable insight and a deep customer understanding.