Ways to Work with Data to Improve Fraud Detection Issues in Insurance

Fraud is, sadly, a threat to all insurers. Yet, despite many efforts to the contrary; it remains difficult to detect fraud. Common factors impeding fraud detection include legacy systems which are not fully interoperable with other data management systems and giving vendors too much control over critical data.

So, how could data be managed better to improve fraud detection in the insurance industry?

Single Data Sources

If you took all the data you have currently hanging out in different systems across the business and brought it together; how much easier would it be to manage? It’s certainly easier to detect trends, problems, and of course the fingerprints of fraud when you bring all your data together. This should also include, wherever possible, “informal” sources of data like your analysts’ spreadsheets and any documentation generated informally around the business. When it comes to beating fraud – the quantity of data is a better safety net.

Quality of Data

Once you’ve got your data together it’s time to revisit it and see if you’ve got any areas to address. It’s not all that uncommon for big chunks of data to be missing; for example because at some point your system didn’t insist on collecting people’s post codes or phone numbers. The more reliable your data is – the better it can be analysed. Spend some time bringing the data up to scratch and you’ll be rewarded for it.

Connect Your Data

There’s a process known as “entity mapping” where you connect discrete entities in different data sets. For example; you have data on a customer in a legacy system, your CRM database and in your marketing database. Flagging and connecting each of these data items so that they can be seen as facets of a relationship with a single entity rather than 3 entities can make it much easier to find problems with an individual account or policy.

Label Your Textual Data

This is similar to entity tracking; you need to automate this process but going through the text in your data sets and tagging it with useful descriptors (such as an industry body being mentioned) can help you connect what would otherwise seem to be unrelated bits of information. If fraud is being conducted; it’s likely to follow a similar pattern (it’s too challenging for most criminals to create completely unique fraudulent claims if they’re doing them in bulk). Tagging text enables you to see deeper into your data sets and recognize when something’s amiss.


These steps are not always as simple to implement as they are to talk about. However, insurers need to look to the bottom line and eliminate fraud wherever possible and these are excellent initial steps to managing your data for fraud prevention.

Insurance Fraud

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