AI, Machine Learning, Data and Analytics – The impact of Local and Regional Government
According to a study by leading UK data analysis firm GlobalData, local authorities are losing £2.1bn to fraud every year. This is a concerning statistic, especially given the extended period of austerity facing the UK economy. It’s thought that the thread of fraud transcends local authorities, with the suggestion of devolution encouraged to increase regional collaboration.
There are many different methods of fraud, with two of the most prominent being procurement fraud and housing fraud which together account for 40% of the overall losses in councils. Procurement fraud is the fake procurement of goods or services for the organisation, this could be done through the manipulation of accounts or simply failure to supply.
Social housing fraud is also rife and is simply taking advantage of the system for personal gain, usually through fraudulent applications or sub-letting fraud. There are many other forms of fraud going on within g councils, and the fact £2.1bn of public money is being stolen is a travesty. Local authorities are having to make significant cuts to staff, services and resources in order to save money, when there is a huge amount stolen which could be going towards issues that really need it, such as social care or helping the homeless.
Current prevention methods such as audits, spot checks and approvals are clearly not enough. The unfortunate fact is that people are easily manipulated or afraid to speak out. Added to which, the people playing the system clearly know every trick in the book to avoid detection, and will often rely on blending in with the crowd as humans fail to spot some of the fraudulent claims – because there is no way that we can possibly review every interaction that goes through the system. The fact that so much fraudulent activity is slipping through the net means there has never been more of a need to adopt advanced analytics and machine learning into our systems.
This technology can go beyond what any human is capable of, to act as a permanent observer for systems and ensuring all documentation, activity and payments adhere to the guidelines and flag every anomaly for review. This gives the permanent watchful eye that councils need, without recruiting tens or hundreds of staff to double and even triple check everything. The system is implemented to monitor existing data and document sources, and machine learning can be trained to understand an organisation’s way of working, which minimises disruption to daily tasks.
Given time and when trained correctly, advanced analytics and machine learning can recognize when something looks off. These technologies can notice a shift in the pattern in terms of spend or activities. In such cases, analytics will follow purchasing trends and can recognise when something seems suspect, which may be what correspondence is sent to suppliers or is proper processes being followed etc. The system will automatically identify anomalies, giving the human user a helping hand in detecting potential cases of fraud.
As this is a solution based on machine learning it gets better the longer it is in place (i.e. the training improves the likelihood of successfully spotting patterns). It will not replace spot checks and audits, but helps to ensure that individuals or transactions don’t slip through the net based on human error – the machine is working 24/7. Artificial intelligence and machine learning is being directed by IT to drive better insights and security across an organisation. This can greatly improve operational efficiency as well as security, by making it much easier to spot potential anomalies and to then quarantine them.
The insights provided by advanced analytics can help to restructure strategic assets and develop innovative new services/product. Data analytics can open a world of previously hidden analytics and insights. While machine learning is destined to impact many different industries in the future, it’s important that we don’t neglect the need for human intervention. Local regional government can sometimes be accused of ‘stagnation’ when it comes to adapting to a technological future, but with machine learning and data analytics emerging as a game-changer, that thought will surely be put to bed.
