How organisations can use business analytics software to reduce fraud
13 February 2017
The 2016 Annual Fraud Indicator, an industry report produced at the University of Portsmouth, estimated that fraud costs the UK £193 billion every year, with £144 billion attributed to business fraud. Having more financial services and more personal information online can entice fraudsters but companies can also leverage this information to monitor and reduce risk. Here, Greg Richards, Sales and Marketing Director of business intelligence specialist Connexica, looks at how organisations can employ analytics software to manage the risks of fraud.
From paying council tax to paying a leisure centre membership, many tasks that previously required a trip to the local council office can now be completed online. While this is far more convenient for customers, it also gives the organisations a chance to cross-reference this large amount of data to prevent fraud.
According to the National Fraud Authority, fraud and corruption costs local government £2 billion a year. At a time when budgets are tight for local authorities, any financial savings have a large impact. Fraud and corruption reduce the amount of resources that are available for legitimate claimants and also reduce the money available for public services.
In response to these figures, Kent County Council’s counter fraud team set up the Kent Intelligence Network (KIN). Local authorities involved in the partnership unified a wide range of data before using analytics software to scrutinise the data to find matches and patterns which could potentially indicate fraudulent activity.
By using business analytics software, organisations can search for discrepancies between previously separated data sets such as council tax, benefits and leisure centre records. Council tax records may show that someone claims to live alone but leisure centre records may show multiple people registered at an address. Councils can use analytics software to flag up such discrepancies and investigate further based on quantitative findings.
Streams of data that need to be analysed may come from different types of software, especially when they come from different organisations. To successfully identify any potential fraudulent activity, business analytics software should be able to monitor data from different sources. For example, Connexica’s CXAIR software is able to monitor data from a number of common business applications such as Sage. CXAIR also uses plug-in adapters to import information from other services such as Twitter or LinkedIn.
Every day, we create 2.5 quintillion bytes of data. Due to this huge amount of data that large organisations record every day, it is impossible for employees to manually monitor all data to look for any suspicious activity, or to look for patterns. In banking, analytics software is often used to search for suspicious activity, such as a series of withdrawals or transfers to offshore accounts, and these can then be flagged for further monitoring.
It is vital that large companies have safeguards in place to protect against fraudulent activity. For example, bank employees have authorisation limits on the payments that they can make, but even these measures have previously been circumvented by making two smaller transactions rather than one large one. By using business analytics software, companies can trace all of the transactions that have been made by a teller if suspicions are raised. Software that uses natural language search makes this much easier for non-technical staff, who can search for all records by name. They will then see a record of all of the payments authorised by that teller and can identify any fraudulent activity.
With experts predicting an increase in fraud over the coming years, the annual fraud report recommends that companies should make investments into the development of anti-fraud detection systems. By using business analytics software, companies have increased control and management over the wide range of data that they hold and can better mitigate the risk of fraudulent activity.
For more information, please contact:
Greg Richards or Jennifer Jones
Unit 20 D,
Staffordshire Technology Park
Tel: +44 (0) 1785 246777
Fax: +44 (0) 1785 876447