Quality, reliable data is at the heart of every good decision and especially important in the insurance sector, says Barley Laing, UK MD at Melissa.
Underwriting, for example, can only be effectively provided when the insurer has access to clean data. Accurate data, culled from multiple sources, enables the underwriter to competently evaluate the risk profile of each applicant or property. If data quality is poor, however, risk assessment suffers, undermining the underwriting process which can lead to fraudulent claims and monetary losses for the insurance company, and put pressure on other service offerings.
Unfortunately, some insurance companies are either unaware or have lost sight of the fact that high-quality data is a key contributor to success.
Accurate customer data is vital for growth
As the current pandemic starts to abate and insurers plan for a post COVID-19 world, decision makers have an exceptional opportunity. By taking a step back and evaluating their existing working practices, they can formulate a plan that will help them not only survive but even thrive in an extremely challenging marketplace.
An excellent starting point is with customer data – one of an insurer’s most valuable assets. If clean, contemporary and verified, this data can help the organisation weather the current economic downturn primarily by helping to prevent customer churn.
Insurers often believe they have done enough in terms of ensuring data quality by collecting verified know your customer (KYC) and anti-money laundering (AML) compliant and clean data at the customer onboarding stage. But that tack is simply not adequate due to the erosion of data quality over time. On average, this degradation occurs at two per cent each month and 25 per cent over the course of a year.
Maintaining clean customer data not only ensures that communications can be efficiently delivered to this audience, but that the data can be effectively analysed for valuable insight to keep existing customers happy, and perhaps, even persuade them to purchase new products and services over the longer term. This is particularly valuable since it costs five times more to acquire a new a customer than to retain an existing one.
Fortunately, data that is simply incorrect, such as a customer name, address, email or telephone number, can be easily fixed. Insurers need to put procedures in place with the right tools to ensure customer data is perfect, which often merely requires simple and cost-effective changes to their data quality routine – in effect going back to basics with the data. These practices should involve cleansing and standardising held customer data to deliver data quality in batch, and as new data is collected in real time, to enable a more seamless customer onboarding experience.
Autocomplete is essential for uniformity
To gather accurate address data in real time, an address autocomplete service works well. This type of tool is crucial since many consumers are completing contact forms on small screens on their mobiles where they are more liable to make mistakes. In fact, approximately 20 per cent of addresses entered online contain errors including spelling mistakes, wrong property numbers, and inaccurate postcodes. This can cause big issues, not only in terms of communication with customers, but it has the potential to make an insurance policy invalid.
An address autocomplete service helps the insurer to deliver a standout customer service by reducing the number of keystrokes required—by up to 70 per cent—when typing an address. This accelerates the checkout process and reduces the probability of not completing the purchase of an insurance policy.
Geocoding takes address data to the next level
Clean address data, or more specifically precise location-based data, is also essential. It enables insurers to evaluate risk and therefore present an accurate insurance premium quote, aiding in driving company performance and profitability. The optimum way to deliver this is to convert a verified postal address into a geocode, which enriches the address by appending rooftop latitude and longitude location coordinates. With geocoding, insurers can obtain precise, plotted coordinates to more accurately evaluate the risk associated with a location — important when insuring a property, for example.
It’s worth bearing in mind that location and address are not necessarily the same thing. Different locations may share an address, such as a plot of land or the street edge of a driveway. A specific geolocation delivers much higher accuracy and reduces the likelihood of losses in the future. A good geocoding tool can also fix spelling errors within addresses.
Geocoding doesn’t just help insurers assess risk, it can aid broader sales and marketing efforts, such as via sales clustering, through the analytics opportunities it provides. With geocoding, it is possible to map the location of customers and find like-minded prospects in specific geographic areas. These individuals can then be targeted based on similar sites where there has been identifiable interest in your insurance offering. Also, in revealing customer clusters, this information can be used facilitate decision making around customer support locations.
Prevent costly duplicate data
Another key part of an insurer’s ‘back to basics’ data quality effort involves the removal of duplicate data. Not only can duplicate data be costly in terms of time and money when communicating with customers, but it can also adversely affect reputation. If a customer receives two mailings in their name, with one spelled incorrectly, it can demonstrate a lack of understanding as to who your customer is and what their needs are. It can also impact on the delivery of a single customer view.
To rectify this, an advanced fuzzy matching tool should be used to deduplicate data. By merging and purging the most difficult records, a single customer view can be deduced from current, albeit fragmented and dispersed, records. This is of utmost importance to those larger organisations that may have accumulated many different databases over time through acquisitions and mergers.
The data quality mindset
Outside the macro economic and social events the world has been facing in recent months, insurers have the ability to control their own destinies when it comes to improving business practices. In order to negotiate these challenging times, it is critical to look at and invest in the fundamental business processes that are vital to commercial success – data quality, data cleansing and data deduplication tools. In effect, organisations must go back to basics with their data practices.
Once customer data is clean, then data-driven solutions, such as geocoding, should be implemented for pinpoint accuracy. Focusing on optimum data quality can give insurers a keen competitive advantage and enable them to emerge from the current crisis with minimal customer churn and considerable growth.