From encouraging customers to spend more by nudging them with just for you recommendations, to analyzing weather patterns to help schedule crop harvesting, data management has impacted all industries.
The insurance sector is no different.
Insurance agencies have been collecting data for as long as they’ve been around in order to assess risk, set policy prices, and answer customer queries. Most times, however, the data is forgotten about after the policy is issued and is consigned to a dusty filing cabinet or ageing database.
But insurance agencies are missing out on a goldmine if they don’t think about data as a strategic asset.
Peter Sondergaard, senior vice president at Gartner, famously said ‘Information is the oil of the 21st century, and analytics is the combustion engine’. Modern data management tools make it easier than ever to collect data from many different places. When combined with powerful analytics, data can fix long-standing problems or exploit new opportunities.
Here are the top 5 benefits of using data for insurance agencies:
1. Improve customer experience
Putting the customer at the center of the business means you can respond to problems quickly, pre-empt others, and ensure all customer-facing staff know about the most recent customer transactions ” positive or negative.
Customer expectations have never been higher and with that comes the demand on agencies to improve every aspect of customer experience. Those who do are rewarded with better customer satisfaction ratings, more referrals, higher revenue per customer, and lower churn.
When trying to tackle a problem as complex as customer experience, you need as much data as you can get to understand each part of the customer journey. What channels are they using for contact or transaction? What information do they need to easily access? What are the pain points that trigger complaints?
For example, an increased number of phone calls asking for help could indicate a customer who’s getting more frustrated and can trigger action from sales or service before the problem becomes a complaint and lost business.
Customers also want a personalized service. With expectations set by other industries such as retail, they expect any interaction with the agency to be placed in the context of previous contact, rather than being treated as if this was their first engagement.
Stored data can be used to pre-populate applications or renewals, and sales and support staff can make short work of answering queries by having all the information they need at their fingertips.
2. Focus on the right customers to maximize revenue growth
Winning new business often gets the headlines inside an insurance agency, but finding additional business from existing customers is quicker, easier, and usually nets a better return for a lower cost.
By combining effective data collection with powerful analytics, it’s possible to calculate Customer Lifetime Value “ the value of the cash flow you expect to generate from a customer over the length of the relationship “ which means you can:
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Identify under-performing accounts
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Prioritize customers for acquisition and retention
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Select priorities for cross or upsell
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Deliver a higher return on sales team efforts
Marketing activities can be improved, too, by calculating metrics such as customer loyalty, conversion rates across different segments, and the most successful lead generation activities.
3. Risk assessment
Data improves risk management by helping to build risk models that provide a better understanding of risk drivers leading to better decision making.
By using historical, continuous, and real-time data, often combined with other internal and external data sources, it’s possible to construct a much more sophisticated picture of risk.
Use data to develop insights into the types of risk for different lines of business, customers, or locations; the risks being written against national averages, and the spread of sum insured exposure. These insights can be used to calculate the risk makeup of the portfolio, compare loss ratios by type, and help evaluate the effectiveness of risk mitigation measures.
A lot of useful data, such as that found in emails, documents, or social media, is unstructured “ it doesn’t neatly fit the data structures used by many computer databases “ but modern tools and analytical techniques can use it as easily as more traditional formats.
4. Fraud prevention
According to the Association of British Insurers, the value of fraud uncovered in the UK is more than £1 billion a year, with an estimated further £2 billion per year going undetected. The cost of crash for cash’ alone exceeds £300 million a year. While in the US, the Coalition Against Insurance Fraud estimates U.S. insurers lose $80 billion annually across all lines of business.
Fraud can be soft, where individuals take advantage of a situation to pay lower premiums or exaggerate claims, or hard, perpetrated by criminal gangs or repeat offending individuals. Either way, the frequency of attacks is increasing.
Outdated technology can’t keep pace with the type and volume of fraud. Training people helps, and they remain an important part of fraud prevention, but effective modern fraud prevention combines the three T’s: team, technology, and tools.
Data management can help an agency’s investigation team detect abnormal behavior, calculate fraud propensity scores in real time as claims are processed, and look for patterns that suggest repeat or hard fraud.
And by matching variables in current claims against those in historic fraudulent claims, red or amber flags, not easily visible to human eye, can be raised for more investigation.
5. Business performance management
Dashboards let managers measure key performance indicators such as performance by product and customer, salesperson profitability, bid-to-sale ratios, operational costs by function, team and location, and most profitable products.
Graphically representing policies by line of business, product, and location can help find gaps in market reach and heat maps can easily display customers who have problems.
Making the move to a data-driven agency
Effective data management isn’t an outcome itself ” improving the top and bottom line is ” but it’s an important enabler for business improvement, and many agencies are investing in the capability.
For example, over half of small- and medium-sized business are considering cloud computing as a way of quickly and cost-effectively giving them a step towards change in managing data.
The two main barriers to effective data management are infrastructure constraints ” not having the right technology ” and data accessibility. Data is siloed, often in different locations and formats, and difficult to find.
Fortunately, modern agency management systems address each of these problems and make it much easier for agencies to take advantage of the many business opportunities offered by effective data use.
