Today, the use of public sector data is something insurance companies can only dream of. Access to public data would be a breakthrough in the fight against fraud, as fraudsters are getting smarter in their attempts to evade the insurer’s radar. This data can not only benefit fraud management during the claim process, but also be valuable during risk assessment at underwriting.
Fraud Investigation
Fraudsters use different modus operandi, different insurers and fake identities, just to make sure that they do not get caught. Fraudsters are always looking for the weak spot. Access to public data could prevent fraudsters from easily moving from one country to the other, from one insurer to the other, and ultimately, from entering any insurance portfolio.
By being able to cross-reference public sector data with company-owned fraud prevention intelligence, insurers are able to:
- reduce blind spots in the investigation process
- decrease the number of false positives that they currently have to investigate
- improve the customer journey
- nuance the level of analysis and prioritize investigations
An example: when insurers have access to governmental data to validate the claimant’s profile, an investigation could drastically change. A person who is involved with social services imposes a totally different risk than an average family with a solid income. Moreover, knowing where someone lives and what their real identity is could be crucial for investigation purposes.
Privacy
Although the sharing of data between public and private sectors could help to prevent, detect and investigate insurance fraud, privacy laws are currently prohibiting the public sector from setting up such constructions. However, the growing level of interest in matching commercial data with data from various public sector databases might change this.
A turn-around is already happening in the UK. Back in 1996, the UK governmentoduced the National Fraud Initiative, which matches data between public and private sector bodies. Since then, fraud and overpayments of over €1.52bn have been identified. Up to now, this matching exercise has only been available for use within the public sector. However, the data is becoming more widely available for fraud prevention in the private sector. Accessing third-party data sources is nothing new on its own, but the incorporation of public sector data provides the missing link.
In other parts of Europe, insurers still feel that they share more data with the public sector than the public sector shares with them. Privacy laws usually say that insurers operating in a fraud investigation need a legal basis to make use of public information. Even when this data is available, there are rules that insurers have to act upon. For instance: fraud investigators need to consider alternative investigation methods to answer their research question. Besides this, the purpose and use of the data needs to be defined so specifically that it is impossible to to use it for other investigations.
Cooperation between insurers
Access to public data still seems difficult to realize, so insurers have to look at alternative options to enrich their sources. Insurers can join forces by sharing data, but also by working together on investigations and to learn together about the latest fraud schemes. This enables insurers to stay ahead of the fraud game. However, sharing data is something insurers easily talk about, but which seems to remain difficult to actually put into action. The technology is no longer the problem, and only commercial reasons stand in the way.
Data sharing will not suffice on its own
Insurers should continue to enrich their understanding of risks through access to the widest possible range of relevant and value-adding intelligence available. Furthermore, investing in expertise and technologies required to mine the information can give the best possible learnings. Technologies such as data matching and social network analysis can improve fraud investigations. Where possible, insurance companies should complement these with predictive analytics and machine-learning techniques. Insurers need to focus on the future and leverage innovative and emerging technologies such as telematics, text mining and data extraction tools.
Source: InsurancePOST
