Australia’s adoption of life insurance is at a decade low, with approximately one in five Australians failing to renew life insurance. Combined with eroding margins due to an increase in claims, and associated costs in areas such as salary continuance, this is creating tough competition between insurers who are now placing an increased focus on the cost of investing in people, processes and technology to support the business.
Gartner believes the changing business landscape is the reason why business leaders have to adopt more prescriptive analytics to make business decisions smarter. Analytics has the scope to transform an insurer’s ability to make fast, accurate decisions and to spin on a dime in an ever-changing marketplace. It can provide accurate and useful information to help determine the right policies and packages to stay ahead of the competition.
Fundamentally, using analytics makes a positive impact on the profitability of your business through informed decision-making. By combining analytics with specialisation in personal injury and return to work claims, it is possible to reverse the trend of smaller profit margins. However, more broadly, insurers that are able to spot emerging trends in a timely way will be able to refine their risk models and underwriting practices. This speeds up payments for legitimate insurance claims and boosts customer satisfaction.
Having said so, it's important to note that any analysis is only as accurate and as good as the reliability of its source of information. Inaccuracies in data occur for a number of reasons, especially if the data is manually recorded. Data collection methods must also be thought through carefully to ensure a complete set of data is obtained and then sorted into the right formats. Here, companies need to be prepared to invest time and energy into making data as accurate as possible, taking a more holistic end-to-end approach to data capture.
You can’t prevent what you can’t predict
Analytics gives insurers the ability to intelligently plot and identify trends and then to make reliable predictions about the future. It enables business leaders to assess whether trends are universal or if they are isolated to regions, even cities.
Gartner also reports that the use of predictive modelling solutions will enable insurers to more accurately predict customer behaviour or trends, manage risks, improve fraud detection, reduce claims leakage, improve underwriting profitability and assist with product pricing. For instance, projecting what might happen in the future can help insurers take steps to modify policy wording or determine any loopholes that are prone to exploitation.
Another use for predictive analytics is to enable organisations to trial tactical adjustments to policies and to forecast the impact on losses. This becomes especially important in health insurance, who continue to face intense competition amongst providers. With analytics, different strata of the organisation can have access to relevant insights to make timely decisions.
Further improving the speed of decision-making, today’s analytics software eliminates the need for extensive manual analysis by highly skilled analysts. This enables the delivery of analytics exactly to the point of contact where and when decisions and actions need to be made, whether it’s a C-level executive or a team leader in underwriting.
Five tips to getting it right
There is no need to reinvent the wheel when it comes to implementing business analytics. It often works better to leverage out-of-the-box capabilities and then work with a specialist to fine-tune the tool to match your unique needs such as geographical spread and customer types. However, some other points of consideration include:
1. To get the most out of any investment in analytics, always keep your business objectives in mind -- process, people and technology -- and align analytical tools to meet these objectives.
2. Remember that analytics is an iterative process; use its power to self-examine how analytics is improving your internal decision making to make it even better.
3. Just like trying to take a Ferrari off-road, analytics is only going to give you the best performance when it is run on optimum terrain. Think hard about the quality of data you are asking your analytics tools to work with, and don’t dismiss the fact that analytics can help you identify areas of data weakness.
4. Build a culture of analytics and develop it throughout the business. Trust your people with business insight and empower them with the insight to make improved decision-making. Prioritise which business units are going to benefit from analytics, and concentrate on its effective use.
5. Analytics is not an island. Approach it holistically, take a deep look into the bowels of your organisation and define how and where data is stored, considering its format and accessibility.
Overall, a pragmatic approach to analytics offers a clear opportunity for differentiation and advantage when executed with forethought and planning. As we move to integrate big data into our strategies, now is the time to get the basics of analytics right.
Diego Ascani is general manager, Australia at Xchanging.