Bounce Back Loan Scheme and Lenders: How Automation Technology can Help Banks With Fraud Detection, Auditing, and Debt Recovery
Having been asked by Government to administer the Bounce Back loan scheme, banks have been left with several extremely difficult challenges if they are to maximise ROI from the scheme.
Setup by the Government to help small and medium-sized businesses stay afloat as the pandemic hit, the scheme had an overwhelming deluge of applications – original estimates expected the total value of the bounce-back loan scheme to be around £18-26bn, however the total value issued cleared £47bn based upon 1.5m loans issued. Banks were expected to carry out KYC and anti-fraud checks, but borrowers were allowed to self-certify their applications despite the Department of Business, Energy and Industrial Strategy recognising that this might lead to greater risk of fraud. And the banks were expected to approve applications with 24 – 48 hours, while also having a duty of care and staffing shortages due to the pandemic.
The scheme suffered unprecedented levels of fraud with the National Audit Office (NAO) revealing that taxpayers could lose up to £26bn due to fraud, organised crime or non-payment. A September 2020 investigation by the BBC uncovered a string of sham companies set up by fraudsters, with more than 100 receiving the full £50,000 pay out.
Unfortunately, as lenders know, those losses are not entirely the burden of the taxpayer with banks saddled with numerous costly obligations and responsibilities around fraud detection and debt recovery made much greater due to the scale of fraudulent activity.
Read on as we explore implications for the banks, what can be done, and how technology can help in this process.
Auditing and Administration
The Government has said that, if scheme rules have been followed and appropriate KYC and anti-fraud policies complied with, banks could apply for 100% reimbursement. However, the extent of the fraud and the speed the Government required banks to carry out approval for loans, it might be that in some circumstances loans were issued without the time to carry out the requisite checks.
At the same time, the unfortunate consequence of that massive amount of fraud detected and the public interest it has received, is that it is likely that any applications to receive reimbursement from the Government will be heavily scrutinized. While there is no indication, or talk, of a fine if a bank submits an application that later it is found that the appropriate due diligence wasn’t done and it proves to be fraudulent, the bank will have to repay the money. It is unlikely that repeat offending in this case will go unnoticed and may result in a request for a full audit of all COVID loans and stricter supervisor of future applications. At the very least, the actual of manually submitting thousands of loans only to get them rejected, is incredibly inefficient and costly for the bank.
It therefore in the banks best interests to conduct a full audit of their Bounce Back Loan portfolios. It will help to identify the fraudulent loans where correct procedures were not followed, and if done correctly will provide them with the requisite audit evidence to quickly get approval for any loans from genuine businesses who simply have not been able to make the repayments. In addition, mean that lenders can start the process of pursuing fraudsters quicker, will give them a better understanding of genuine businesses’ affordability situation who may wish to pay but are struggling, and it will give them an understanding of the good and bad loans in their portfolio for future financial planning.
Unfortunately, an audit of this scale and complexity, when done manually is an incredibly time-consuming and expensive task. Not only is there a requirement to be able to remediate large amounts of data at once, but to look for different types of risk with the British Business Bank identifying no less than 36 fraud risks in their assessment of 27th July 2021. With so many cases it will also be necessary to define and utilise a risk-based approach to identify cases that need to be investigated further. For example, even a basic search to confirm against company dormancy or to verify they accurately stated their turnover when done manually through Companies House will likely overwhelm your team.
Fraud
An audit of this nature will help lenders understand their portfolio, what percentage is fraudulent, and the compliance that was done when the loan was approved. If fraud is discovered for which, for one reason or another, it is hard to clearly prove compliance procedures were followed this will mean the bank has to make the decision to pursue that fraud themselves. In the event, they can prove they followed the BBL scheme rules, there are still obligations to pursue the debt. After creating 3 fraud tiers, the Department and HM Treasury has made it clear that they expect, lenders to pursue fraudsters from the lower two tiers. In July 2021, the Financial Conduct Authority, the main regulator for lending, again reminded Scheme lenders of their wider obligations to report fraudulent activity.
It is unlikely that this requirement for banks to help with pursuing fraudsters as the National Investigation Service (NATIS), tasked with pursuing organised criminal groups is reported to be overloaded, only managing to handle 50 cases a year when they had 2100 intelligence reports on their desks in October 2021.
While the costs of recovering that debt might lead a lender to have to make the choice between writing it off and pursuing it, they have been advised not to.
The reality therefore is that lenders will need to commit considerable resources not just to the identification of fraudulent loans, but the pursuit of the fraudsters and recovery of funds. Investigations for the latter, given the types of fraud, the sophistication of the criminals and difficulty of tracing individuals behind it, is an even more complex process requiring multiple data sources from across consented, internal and open source.
Debt Recovery
It may appear that for businesses identified as genuine ones, as there is a loan guarantee from the government, there is little to worry about for banks. However, the government has mandated that banks are obliged to pursue the borrower and attempt to get them to repay before submitting for reimbursement. An audit therefore to identify the affordability of the business owner, in much the same way as the lender would have done in normal circumstances, would go a long way to identify what loans are likely to be defaulted on, and what ones the owners are likely to need more time. This information would help the bank more proactively deal with loans and manage them to repayment. It also would act as solid evidence to show they have used due process to pursue the debt. To support that process of managing the debt, ongoing monitoring of the businesses’ situation will also help to alert the bank and keep the repayment on track.
As part of that audit, when unfortunately, the borrower is unable to repay, it is necessary to also show all has been done to find the individual.
In the case of successful credit risk affordability evaluation – as it is for fraud risk and investigations to find individuals – it is increasing the case that multiple data sources are used to get a more accurate picture of the subject. In turn, contributing to the cost and complexity of the process for your team.
How Technology Can Help
With banks facing the need to carry out a complex mass audit of their bounce back loans portfolio, fraud investigations and reporting, the efficiencies of automation to reduce costs and speed up this process are an absolute necessity; however, the automation required here is beyond the scope of onboarding and basic due diligence software. As this is also a unique situation, it is unlikely that the solution can be found from just data modelling on internal databases. What is required is the ability to carry out risk assessments at scale with multiple data sources, to have automated reporting, and ongoing monitoring.
Synalogik’s automation and data aggregation platform, Scout, offers the ability to carry out complex investigations and checks. Designed to be data agnostic, and already integrated with all major third-party data providers, open source and internal data, it makes it possible to automate any kind of investigation and ensure the economies of automation are carried out over all your data sources rather than having to resort to manual combining of the data.
Scout allows you to set up any number of search or risk assessment workflows to address your different needs – for example, risk assessments to identify likelihood of fraud, investigations to find fraud perpetrators, and affordability assessments on creditors, and ongoing monitoring through Companies House. It can perform those searches concurrently delivering results in less than sixty seconds and auditable reports.
With Scout®, banks, faced with decisions on whether to write off debt where possible due to the costs associated with having to manually audit their portfolios – now have an alternative. An alternative which can save up to 85% of their time and redress the risk/benefit equation of carrying out the audit and allow them the chance to maximise the return on their bounce back loans.
References
