Businesses and consumers alike typically consider insurance to be a grudge purchase – something they need to have, but which does not add value, says Ian Logan, senior director: Insurance and Partners at TransUnion.
Although it is essential in protecting them from a wide range of unforeseen events, the worth of the monthly or annual premium paid as well as any service fees involved is only realised in the event that something goes wrong. In such events, the insurer will assess and pay out compensation to rectify damages.
This simplistic view of the workings of the insurance industry is the general understanding of most policyholders. In reality, however, a substantial amount of work is required in the background to ensure that policies and claims are processed quickly and effectively. In order to ensure this processes happen smoothly, insurers require access to quality data to decrease the very real risk of insurance fraud, which has a negative knock-on effect to legitimate customers as well as on minimising risk while maximising customer service.
The insurance industry as a whole experiences a high volume of claims, often with high Rand amounts, making it an ideal target for fraudulent activities. In fact, according to the South African Insurance Claim Bureau (SAICB), up to 20% of the R50-billion claims paid annually are fraudulent.
When a policy is initiated, the insurance organisation needs to assess the person applying for the policy and ensure proper checks are made for the items being insured. During claims processing, adequate information is required to eliminate false claims. Quality information is vital for the insurance industry to monitor and review policyholders and their claims and minimise fraudulent activities. In addition, the cost of verifying previous claims and claims information with other insurers — essential in identifying and preventing fraud — presents a significant challenge. This is exacerbated by poor quality data, which inflates costs, increases the likelihood of unidentified false claims and stalls the underwriting and claims process, negatively impacting on customer service.
Quality data is now coming to the forefront as an essential tool for the insurance industry. This is driven in part by legislation such as the Insurance Laws Amendment Act, as well as the requirement for Solvency Assessment Management (SAM), which requires insurance companies to have a better view of their exposure. This can only be achieved through an accurate understanding of what and who is insured, which in turn requires quality information.
Furthermore, enhanced quality of data will enable improved underwriting, risk assessment and understanding of claims, which in turn leads to improved customer service. The more information captured and available at the insurer’s fingertips, the better they will be able to identify risk, process claims and weed out fraudulent activities.
The Insurance Data System (IDS) provides an ideal platform for much of the necessary verification of claims and policies to take place. IDS is a central repository of data around insured parties, insurance policies and claims which can help insurers to understand more about the risk of insurance underwriting or a particular claim.
Using the historical information in this database, insurers can pick up trends and patterns, identify individuals or businesses making duplicate claims, and highlight other red flags that may indicate fraudulent activity. However, the accuracy of any insight derived depends upon the accuracy and completeness of data within IDS, which in itself offers a significant challenge. Incorrectly captured or incomplete information submitted to IDS prevents this data from being correctly verified when necessary.
Accurate and complete information will ensure the data in IDS is clean and provides the most effective insights. This will benefit the insurance industry by improving the verification processes, ultimately saving organisations money and decreasing the number of fraudulent activities. The quality of data within IDS is the essential component, however data quality is not a once-off exercise. Ensuring quality data now and in the future will require both the insurance industry and the bureau to work closely together, creating a win-win situation that is mutually beneficial for all parties.
