Verifying the Authenticity of Property & Net Zero Scheme Evidence
Humanly supports organisations that assess digital property and net zero evidence as part of grant approval, retrofit validation, ECO4 delivery, and fraud investigation workflows. The platform is designed to analyse submitted documents and images to identify indicators of editing, manipulation, or AI generation. By introducing an additional layer of authenticity assurance before funding or compliance decisions are made, Humanly helps departments, scheme administrators and fraud teams strengthen trust in submitted evidence.
Addressing Emerging Risks in ECO4 and Net Zero Submissions
Property and energy efficiency programmes increasingly rely on digital submissions. ECO4, retrofit schemes, insulation grants and decarbonisation initiatives require documentary and photographic evidence to justify eligibility, installation quality and funding release.
This digital shift improves efficiency and auditability. However, as advanced editing tools and generative AI become more accessible, it may become easier in some contexts to fabricate supporting documents or alter installation imagery.
For the Department for Energy Security and Net Zero and associated fraud teams, the exposure is operational rather than theoretical. Large-scale funding programmes involve multiple actors across installers, managing agents and households. When manipulated evidence appears plausible, manual review alone may struggle to consistently detect subtle digital alterations.
The consequence is not limited to financial leakage. Inaccurate evidence can undermine scheme integrity, distort performance reporting and erode public trust in net zero delivery.
Humanly’s approach is to focus specifically on the authenticity of submitted digital evidence, rather than replacing existing policy, audit or compliance controls.
Strengthening Property & Net Zero Reviews with Evidence Integrity
Humanly acts as an additional authenticity layer alongside existing governance, fraud, audit and compliance frameworks.
The platform is not a rules engine and does not assess eligibility criteria. It does not determine whether a property qualifies for funding or whether installation standards are met. Instead, it analyses the integrity of the submitted content itself, helping reviewers understand whether documents or images appear genuine, altered or synthetically generated.
For departments such as DESNZ, this can support fraud investigation teams by surfacing structured authenticity signals within high-volume submission environments. Human reviewers remain fully in control of funding and enforcement decisions.
Protection for Public Energy Funding & Government Money
Humanly helps identify manipulated documents and images used to inappropriately access retrofit grants or energy efficiency funding. This can assist fraud teams in reducing exposure to falsified claims while protecting legitimate installers and households.
Integrity for DesnZ and Retrofit Grants
The platform supports scheme administrators and managing agents in assessing the authenticity of installation evidence, declarations and supporting documentation. This helps reduce the volume of disputed or potentially fraudulent submissions progressing through manual workflows.
Support for Government Fraud and Audit Teams
Humanly provides structured authenticity signals that can assist fraud investigators and auditors when reviewing property and energy scheme submissions. Where AI-generated or digitally manipulated evidence may appear plausible to the human eye, the system is designed to highlight indicators that warrant closer scrutiny.
Operational Impact for DESNZ, Local Authorities and Scheme Administrators
Public Sector Risk Reduction
Humanly assists government departments and local authorities in identifying falsified or manipulated evidence submitted within net zero funding schemes. This strengthens assurance without replacing human investigation processes.
Trust in Submission Workflows
Architected digital-first grant application models can improve efficiency, but only if evidence integrity can be trusted. Humanly supports continued digital adoption by adding authenticity analysis to the review process.
Scalable Authenticity Oversight
Manual review is essential but can become resource-intensive at scale. Humanly is designed to support safer decision-making by analysing authenticity signals across large volumes of submissions, helping teams prioritise cases that may require deeper review.
Common Questions
How does Humanly identify manipulated property or retrofit evidence?
Humanly analyses a range of authenticity signals within submitted documents and images. These may include structural inconsistencies, indicators of digital alteration and linguistic patterns associated with AI-generated text. The output is a set of review-oriented signals rather than a binary decision, enabling human reviewers to make informed judgments.
Does this system make clinical decisions?
No. Humanly is not a clinical decision system and does not assess medical suitability or diagnosis. It focuses exclusively on the integrity of the digital evidence itself to support safer decision-making by claims handlers and reviewers.
Why is authenticity verification important for patient safety?
Inappropriate access to prescription medication (such as metabolic or weight loss drugs) can create direct patient safety risks. Verifying that supporting evidence is genuine helps ensure that treatments are legitimately authorized.
Where does Humanly fit into existing healthcare processes?
Humanly is positioned as an additional analysis layer within intake, review, or audit processes. It is designed to assist insurers, public health bodies, and administrators without replacing their core clinical or regulatory controls.
How does Humanly address the specific risk of weight loss drug and metabolic medication fraud?
Global demand for metabolic and weight loss drugs has created a significant exposure to evidence-based fraud. Fraudsters often submit altered referral letters or manipulated clinical imagery to bypass authorisation checks for high-demand medications. Humanly is designed to analyse these digital submissions for technical indicators of AI generation or editing, helping payers and providers verify that the supporting documentation used to justify access is authentic.
What is the impact of AI-generated healthcare evidence on patient safety?
When falsified medical evidence, such as prescriptions or diagnostic documents, bypasses review, it creates direct patient safety risks by allowing unauthorised access to medication or treatment. By identifying indicators of synthetic content before a decision is made, Humanly helps ensure that healthcare actions are based on genuine medical authorisation. This reduces the risk of inappropriate clinical outcomes and lessens the strain on healthcare systems caused by unauthorised or unapproved treatments.
How does Humanly differ from a clinical decision system?
Humanly is not a clinical decision system and does not assess medical suitability, diagnosis, or clinical appropriateness. While traditional medical review systems focus on the accuracy of a diagnosis, Humanly focuses exclusively on the integrity of the digital evidence itself. It helps organisations understand whether a submitted image or document appears genuine, altered, or synthetic, serving as a technical assurance layer that works alongside existing clinical and regulatory controls.
