UK Government faces a potential loss of £15 billion to £26 billion through businesses not being able to repay ‘Bounce Back Loan Scheme’ loans; and fraud, according to a National Audit Office (NAO) report. The official auditors concluded that the Government ‘prioritised one aspect of value for money – payment speed – over almost all others and has been prepared to tolerate a potentially very high level of losses as a result’, whether because of fraud or businesses unable to repay.
Gareth Davies, head of the NAO, said: “With concerns that many small businesses might run out of money as a result of the COVID-19 pandemic, government acted decisively to get cash into their hands as quickly as possible.
“Unfortunately, the cost to the taxpayer has the potential to be very high, if the estimated losses turn out to be correct. Government will need to ensure that robust debt collection and fraud investigation arrangements are in place to minimise the impact of these potential losses to the public purse. It should also take this opportunity to consider now the controls it would put in place to protect against the abuse of any future such schemes.”
As the NAO point out, a third-party review commissioned by PwC for the British Business Bank found that, while some risks can be mitigated, there remains a “very high” level of fraud risk, caused by self-certification, multiple applications, lack of legitimate business, impersonation and organised crime.
Responsibility for managing fraud risk on the lenders as part of the loan approval process. To support lenders, the Bank established fraud prevention forums to share best practice and aid implementation of additional fraud measures, including a method to prevent duplicate applications. The Bank, alongside the Department for Business, Energy & Industrial Strategy (BEIS) and lenders, intends to start using the information they collect centrally to provide monthly fraud reports from October 2020 onwards. The report noted that the Bank is unable to estimate the overall level of fraud. The Cabinet Office’s Government Fraud Function believes that fraud losses are likely to be significantly above the 0.5 per cent to 5pc which is generally estimated for public sector schemes.
The report sets out that the Bank was not able to prevent duplicate applications across lenders for the first month of the scheme.
For the full, 51-page report, visit the NAO website.
Briefly about the scheme; it launched on May 4, as the report acknowledged, to respond to small firms’ ‘acute cash flow issues’; and remains open until November 30; loan repayments do not start to become due until May 2021. Most, around 90pc of the loans went to micro businesses (turnover below £632,000) which received £29.4 billion from 1,039,000 loans. The five largest UK lenders (Barclays, HSBC, Lloyds/Bank of Scotland, NatWest/RBS and Santander) provided £31.3 billion of loans under the scheme.
Comment
Simon Dennis, Future Government and AI Evangelist, at the analytics company SAS UK and Ireland, said: “In the rush to contain COVID disruption, public and private sector organisations implemented measures, at pace, to protect the economy. Expediency may compromise some aspects of the usual safeguards to design out fraud, leaving systems open to unanticipated exploitation by (cyber)criminals. In reality, any significant change or new initiative will attract fraudsters, even if designed and implemented well. The quick roll-out of the Government’s Bounce Back Loan scheme is just one example of this.
“The pandemic and the accompanying drive to digital channels has made it easier for organised crime groups and opportunistic individuals to exploit the situation. With new initiatives like this there will inevitably be error as well as fraud, which can make it more difficult to pinpoint the genuine fraud cases. Ultimately it’s law-abiding businesses and taxpayers that pay the price as these groups steal from the public purse or operate under the guise of actual government bodies to trick the less-wary citizen.
“The ‘unprecedented’ nature of the pandemic also hampers investigators and automated systems alike as components such as Anomaly Detection, for example, which relies on recognising significant deviations from normal behaviour, is more difficult given the raft of new initiatives and changes in what is the new “normal” behaviour brought on by the pandemic. Nevertheless automated anti-fraud technology using AI is one key to catching the criminals and helping to protect the public.
“In banking, fraud detection models must quickly adapt to the new loan systems necessitated by COVID, for example by making use of scenario-based modelling to quickly learn from multiple ‘what-if’ scenarios and understand all the key inputs in this new environment. From here, efficient models with a low rate of false positives can help detect criminal behaviour and protect public funds at this critical time.”
“Even the human isolation that has been the nature of the pandemic aids the criminals. Humans are very good at sharing concerns and networking starts to build a group picture that reinforces legitimate doubts. When this is disrupted it gives the crook more time to operate. Luckily, many modern systems incorporate social network analysis that allows the group picture to be assessed by the models that spot fraud.
“Being wary and asking yourself constantly whether it could be fraud remains a top tip and its always best to talk if in doubt.”
