Insurance Claims & Banking

Digital evidence now sits at the centre of modern insurance claims. Images, documents and supporting files are routinely submitted to validate loss, damage and liability across motor, property, travel and personal lines. As artificial intelligence and editing tools become more accessible, the reliability of this evidence can no longer be assumed.

Insurance fraud remains a significant and growing challenge for the financial services sector. Motor claims are increasingly affected by manipulated accident imagery, staged damage and reused photographs from unrelated incidents. Property and household claims often rely on images that may have been altered to exaggerate loss or misrepresent the timing and cause of damage. In personal injury and liability cases, supporting documentation can be digitally edited or partially fabricated to strengthen a claim narrative.

The introduction of AI generated content adds a further layer of complexity. Synthetic images can now be created that convincingly depict vehicle damage, flooding, fire or theft without any real world incident ever taking place. When combined with genuine background details or previously captured images, this content can be difficult for human reviewers to identify through visual inspection alone.

For insurers and financial services providers, the risk is not limited to financial loss. Disputed claims increase operational costs, slow down settlement times and place pressure on claims handlers. Incorrect decisions can damage customer trust, expose firms to regulatory scrutiny and undermine confidence in digital first claims processes.

Humanly’s Insurance Claims Model is designed to support claims teams by assessing the authenticity of digital evidence at the point it is reviewed. The model analyses claim images and supporting content to identify indicators of manipulation, editing or AI generation. This allows insurers to flag higher risk submissions early, prioritise investigations and reduce reliance on subjective judgement alone.

In motor insurance, this capability supports the validation of accident imagery, vehicle damage photographs and repair evidence. It helps identify reused images, digitally altered damage and synthetic content intended to exaggerate or fabricate loss. For household and property claims, the model assists in assessing images relating to flooding, fire damage, subsidence and theft, where authenticity is critical to fair outcomes.

Within broader financial services, the same risks apply to supporting documentation used in underwriting, claims validation and dispute resolution. As firms increasingly rely on digital submissions, ensuring that evidence has not been manipulated becomes essential for compliance, audit and customer protection.

Humanly does not replace claims handlers or existing fraud systems. Instead, it acts as an additional layer of assurance, providing objective analysis that supports decision making. By integrating authenticity assessment into existing workflows, insurers can improve efficiency, reduce fraud exposure and maintain confidence in digital evidence without disrupting established processes.

As digital claims volumes continue to grow, and AI generated content becomes more widespread, the ability to verify what is real will be a defining capability for the insurance sector. Humanly supports insurers on that journey, starting with claim evidence authenticity today and expanding as digital risks evolve.