In an industry race to become more customer-focused and to harness advanced analytics, health and life insurance have tended to lag behind the general insurance sector.
The nature of health insurance requires providers to navigate through a deeper stream of personal data, more fragmented systems as well as regulatory challenges to access the required data. However that is changing and with recent advances in wearable devices and health apps, the future is looking bright for creating a more data-driven culture in this sector.
The primary challenge for health insurers in India lies in infrastructure. The integration of platforms to capture more data requires better connectivity of healthcare systems, but this is improving. A lack of infrastructure to capture data is the biggest challenge for most insurers. In an industry that has been largely dominated by paper-based transactions, electronic documents are still evolving.
There are some examples from around the world that show the future. There will be a lot happening in the next three or four years, not just the next ten years, with over 250,000 health-related smartphone apps out there globally, which are backed to varying degrees by clinically-validated data for health decisions.
With the deployment of personal devices for fitness and health there are big questions, such as how to do we integrate the data? As an industry we are building on reactive risk modelling towards predicting customer behaviour, but how do we collaborate between the technical experts, the data modellers, and the leaders who are shaping the insurance business? How do we deploy?
Steps to becoming a data-driven organization
Without question, this is a journey of data collaboration and there are no quick wins. You cannot expect to move quickly from being a low adopter to an organization with a sophisticated digital DNA. The first steps involve the basics such as gathering business intelligence capability, running reports and then aligning the reports with the business need. The next steps then involve integrating more of the external data sources with the internal sources and then driving this across the whole organization.
In the final stage, the most sophisticated insurers become truly customer-focused where business changes are constantly updated for advances in consumer behaviour. Propensity-to-buy models are already being used to understand customers’ needs for health and life products based on age, gender and other factors like credit card behaviour and optimistic/pessimistic social media posts.
Research from one global insurer in the Asia Pacific region for example has shown a 70% increase in call centre campaign performance for health products, using such a personalised, targeted approach, compared to a control (random) group of customers.
Lifestages and personalization
It is important to take a 360-degree view of the customer and their lifestages. This should extend to including things like their channel preferences, quality requirement and mood (sentiment) defined as social media sentiment. Understanding the customer’s needs is the first step towards helping them, rather than just selling to them. Data and analytics is the vital tool to achieving that.
In the US, at LexisNexis® our Lead Optimizer has been shown to optimize marketing leads and prospects, cutting unproductive leads by more than 30%.
Life events to a large extent drive decision behaviour in life and health insurance, as our research shows.
But customers – and especially the older generation – might be concerned that we are moving towards a Big Brother society, where insurers know everything about them and their family, their age and preferences. So the key to communicating is to be aware of the customer’s needs but not to be too personal.
As an insurer, if we know a customer recently got married or had children, there is no need to expressly communicate that. There is still a lot of room for personalization.
New businesses are being built around the interpretation of health and life-stage data. But when it comes to things like disease risk assessment and risk rating, the outcomes are only as good as the data that has been collected, tested, trusted and validated. For us at LexisNexis, the goal is very much about answering the ‘so what?’ question and gaining applicable insights from all the vast new sources of data that are being generated.
As in the rest of the world, the new health insurance regulations for 2016 place more responsibility on India’s insurers to advise the customer and feedback information to them on healthy living. The new regulations incentivise buying a plan early, staying with it, and maintaining good health. The incentives will be disclosed upfront in the policy literature.
How we leverage health data and analytics
As an industry leader in a number of areas relevant to fraud prevention including identity management, data linking, predictive analytics, full spectrum SIU investigative tools, public data and social networking analytics, LexisNexis brings data driven solutions to various healthcare workflows.
Our data and analytics can be applied to wellness and disease management outreach to improve contact ratios and ensure healthcare organizations have the most current contact information on its population. The benefits include reduced costs associated with return mail and failed member outreach. Our solutions leverage vast amounts of public data and identity analytics to target receptive individuals and help organizations increase contact and conversion ratios.
LexisNexis assists in updating contact information for members in target populations using our batch data cleansing capabilities; improves outreach success by enriching data with additional contact information, including mobile phone numbers and email addresses; automates time-consuming and labour-intensive administrative processes, such as handling returned mail; and uses demographic and behavioural information to focus disease management outreach on members who are likely to respond positively to outreach efforts.
Conducting a real-time search of billions of public records straight from your desktop before a claim is even processed can increase auto-adjudication ratios and greatly reduce the amount of money paid for fraudulent claims.
Access to this same extensive database can also dramatically reduce the amount of time required to investigate suspicious claims after they’ve been paid as well as administrative costs associated with manual claim reviews and reprocessing of denied claims. Benefits include reduction of claim denials due to inaccurate information, fraud detection and improved debt recovery.
Follow the link to the LexisNexis Risk Solutions India website to find out more about how we support insurers.