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What the Bounce Back Loan Scheme taught us about collective fraud defence

A blueprint for public-private defence against crisis-scale fraud using shared intelligence and cross-sector collaboration.

Overview

1. The Ambition

Protect emergency public funds at speed while distinguishing genuine need from organised abuse across multiple lenders.

2. The Solution

Unite private sector consortium intelligence with public sector and commercial data to surface BBLS abuse. 

3. The Results

Half of accepted loans reclassified for review, organised fraud isolated earlier and investigations prioritised. 

Industry

Public Sector | Finance

Location

United Kingdom

A national fraud crisis

More than 1.5 million Bounce Back Loans worth £47 billion were approved during the COVID-19 pandemic. The Government’s emergency support for those businesses affected was defined by urgency.

Six years on, we see clearly how this environment of urgency exposed the UK to a wave of fraud that is still affecting the economy today.

Key questions remain:

  • How do you protect public money under exceptional time pressure?
  • Separate genuine need from organised abuse when checks are deliberately light?
  • Understand risk when it’s spread across thousands of applications and dozens of institutions?

This case study focuses on Bounce Back Loans specifically; what happened, how fraud was uncovered, and why the response from lenders, Synectics and public partners is still a private-public defence blueprint.

 

A scheme built for survival, but not without a cost

Concerns surfaced within weeks of BBLS going live. In May 2020, the Chief Executive of the British Business Bank warned the scheme poses “very significant fraud and credit risks” and was “vulnerable to abuse”.

By October, the National Audit Office estimated that up to 60% of BBLS loans – as much as £26bn – might never be repaid because of fraud, organised crime or default. By the end of the year, £68bn had been paid out in emergency loans.

BBLS was dubbed the “riskiest of the set”, with loans issued within 48 hours and with limited application, credit and affordability controls applied.

How the abuse took shape

This was a calculated trade-off with good intent, but with much of the context normally used to judge risk absent. The result was large loan books containing a mix of genuine businesses, inaccurate applications and organised fraud – without a reliable way to tell which was which.

As lenders and investigators compared notes, clear patterns emerged.

  • Criminal groups set up companies purely to apply for loans, often at scale. Limited companies were advertised for sale, marked “No BBLS” or “No CBILS”.
  • At the same time, identity fraud was widespread. Personal data was harvested and businesses were incorporated using stolen identities.
  • Bank accounts were opened and loans taken out, sometimes from multiple lenders.
  • And BBLS funding was frequently misused as start-up capital or for personal loans

In many cases, applicant businesses also showed no evidence of trading before or after the pandemic, sometimes operating separate active companies in parallel. Each bank could see parts of this picture. Nobody could see the whole of it. 

The visibility problem

As with identity fraud more broadly, activity was rarely confined to a single organisation. The same applicants, directors and business structures appeared across multiple lenders in slightly different forms.

Working in isolation, lenders prioritised investigations using what they could see locally, which made it difficult to answer the most important question: Which cases reflected genuine business distress – and which were organised abuse of a public scheme?

What changed when intelligence was shared

Synectics worked with UK banks to bring clarity to BBLS risk by combining National SIRA consortium intelligence with public sector data and commercial context.

The aim was to establish who had traded before the pandemic, who was linked to known fraud, and where behaviour repeated across organisations.

In one Tier 1 bank review, only 50% of accepted applicants showed reasonable evidence of pre-pandemic trading. The remainder were referred for investigation. Within that group:

  • 45% showed no evidence of trading before or after the pandemic
  • 14% began trading only after the scheme launched
  • 6% had other active businesses suggesting funds had been diverted
  • 18% were linked to known or suspected fraud.

Even among applicants that initially appeared legitimate, 35% were flagged as higher risk once cross-bank and cross-sector intelligence was applied.

The role of National SIRA

For lenders, National SIRA allowed lenders to move beyond individual applications and see behaviour in context – exposing applicants with no trading footprint, repeated company structures, and directors linked to earlier fraud.

This insight shifted the BBLS fraud response from broad uncertainty to targeted action:

  • Investigations could be prioritised.
  • Fraud proof became easier to assemble and act on
  • Recovery efforts could focus on the cases most likely to involve organised abuse

Why this still matters - and the wider lesson

The BBLS model – a public initiative delivered through private infrastructure, governed by public eligibility rules – is an expanding one. Large-scale programmes in economic support, energy and digital identity increasingly rely on the same mix of public policy and private execution, and face the same exposure of public money when speed becomes non-negotiable.

BBLS showed what happens when the balance between time pressure and fraud prevention is disrupted – and that prevention is certainly easier than recovery.

It also exposed a structural limit. When risk is national in scale, no single organisation can see enough to reliably separate genuine need from coordinated exploitation.

For future public‑sector initiatives, the lesson is clear: when programmes are large, fast and high‑impact, collective visibility is one of the strongest defences available.

About Synectics

Synectics Solutions works across the private and public sectors to help organisations use shared intelligence to make defensible decisions in high‑risk environments.

At the heart of our approach is collective defence - bringing together cross-sector partners to share intelligence, detect emerging threats, and strengthen protection across the system.

Our National SIRA risk intelligence consortium has over 160 contributing members, a unique view of both confirmed and suspicious behaviour, and has saved £8bn in losses in the last five years.

Got a challenge or a question?

Got a challenge or a question?

Get in touch to see how we can work together to prevent fraud and reinforce your defences against emerging threats.

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