Colin Gray discusses how to limit fraudulent activity and safeguard citizens amidst Liz Truss’ energy price freeze
Liz Truss is planning loans for energy companies to protect consumers and support vulnerable businesses to the tune of £150bn. Colin Gray, Principal Fraud Consultant at SAS UK, says preventative money laundering processes must be factored in from the beginning to safeguard citizens and avoid losing the substantial sums to criminals seen during the COVID-19 pandemic.
Prevention over cure
The news that Liz Truss’ new Government will act to limit the potentially devastating impact of energy price inflation is positive for UK households, and businesses, but fraud prevention must be a consideration from day one to avoid costly losses for the taxpayer.
While help for households, via energy companies, will take effect from 1 October, businesses will have to wait until November, likely due to the challenges associated with launching a scheme on this scale quickly.
High on the priority list for the architects will be to limit fraudulent activity and ultimately lost money for the UK taxpayer. Thinking about prevention rather than relying on later detection and investigation will be vital – the latter techniques proved particularly ineffective with the COVID-19 Bounce Back Loan Scheme.
This led to criminals and organised crime gangs making more than a billion pounds through underhand tactics. The latest estimate is that £1.1bn of the total lent via the bounce-back loans scheme was fraudulent. When in a crisis, like we were then and as we are now, decisions have to be made quickly, but we simply can’t allow that level of fraudulent activity to happen again.
The opportunities for fraud depend on the mechanism used. One risk, for example, is that some businesses – or organisations purporting to be businesses – claim they use far more energy than they really do in practice.
Liz Truss needs to focus on data sharing
The new Government should focus on improving data sharing between government organisations and removing any processes which needlessly slow down the data or intelligence sharing process. Artificial intelligence (AI) systems and analytics should be used to join things up and identify potential fraudsters.
Our recent research, where we surveyed 86 civil servants from major Government departments including HMRC and the Home Office, found that 90% said their department uses data for decisions, but only a quarter said they are following The National Data Strategy.
The research also found that improving and promoting data sharing across Government departments is among the top three priorities and 90% of civil servants said their government department now uses data to drive decision-making.
We’ve seen that more joined-up thinking is possible, with HMRC developing the Connect Computer System – a supercomputer designed to improve HMRC’s ability to identify those who are understating and underpaying their tax liability.
It’s this kind of thinking that needs to be ingrained in the system from the very outset.
The human impact of fraud can be devastating
The implications for fraudulent activity go far beyond the financial. Unfortunately, there is a very real human cost associated with economic shock.
Financial stressors, in this case, driven by rocketing energy prices, invariably have a knock-on effect beyond immediate support schemes. Other government-led services are likely to come under pressure from increased fraudulent activity including benefits and even the NHS.
During periods of financial hardship the incidence of domestic violence increases
For example, research has found that during periods of financial hardship the incidence of domestic violence increases. Recent Women’s Aid research has found that almost three-quarters (73%) of women living with and having financial links with their abuser said that the cost of living crisis had either prevented them from leaving or made it harder for them to leave.
More funding is required to support those affected and to minimise the broader impact on the system.
ONS figures show that up to June this year there were already 16 million people in Great Britain who had cut back on food and essentials, highlighting the cost pressures already affecting households – and that’s before the next energy price rise has even hit.
We might also see desperate individuals tampering with meters
In today’s energy crisis we might also see desperate individuals tampering with meters to reduce the impact of energy price rises. There are obvious dangers associated with this that could lead to gas explosions, electrical malfunctions and the resulting injuries and even deaths.
Data analytics and AI can help those most in need
That’s why the smart use of data analytics and AI are essential, firstly to prevent fraudulent claims, by joining disparate systems together but also to support citizens.
These same data analytics tools can be used to help legitimate claimants to apply for all the benefits and support they are entitled to and which are available to them, but which otherwise may have been missed or gone unclaimed.
There’s a difficult balancing act at play here; the need for speed versus the need to ensure a robust system minimising exploitation and supporting those in need. We’re sure AI has a vital role to play.