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Postgraduate DiplomaInsurance, Risk & Actuarial Data Applications open

Postgraduate Diploma in Digital Loss Adjustment with AI and Drones

Online 800-hour Postgraduate Diploma in Digital Loss Adjustment with AI and Drones. 8 modules covering Commission Implementing Regulation (EU) 2019/947 (UAS operations), Commission Delegated Regulation (EU) 2019/945 (unmanned aircraft systems) and Pix4Dmapper. Assigned tutor and enrolment open.

Duration800 h
ModeOnline
AwardSEIUM Institute diploma
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Learning outcomes

What you will be able to do

01

Compare traditional and digital loss adjustment methods.

02

Apply computer vision techniques to identify and quantify damage.

03

Plan drone operations in line with European UAS regulations.

04

Generate 3D models and orthophotos through photogrammetry for damage measurement.

05

Organise mass loss adjustment following catastrophic events.

06

Automate the preparation of the claim file and the expert report.

07

Ensure quality, traceability and the ethical use of AI in loss adjustment.

Profile

Who it's for

  • Digital insurance loss adjuster who wants to specialise in Digital Loss Adjustment with AI and Drones.
  • Drone pilot for expert inspection who wants to specialise in Digital Loss Adjustment with AI and Drones.
  • Photogrammetry technician who wants to specialise in Digital Loss Adjustment with AI and Drones.
  • Computer vision analyst who wants to specialise in Digital Loss Adjustment with AI and Drones.
  • Loss adjustment coordinator for catastrophes who wants to specialise in Digital Loss Adjustment with AI and Drones.
  • Claims innovation manager who wants to specialise in Digital Loss Adjustment with AI and Drones.
  • Graduates in engineering or science seeking to enter insurance loss adjustment.
Standards & tools

What you'll work with

  • Commission Implementing Regulation (EU) 2019/947 (UAS operations)
  • Commission Delegated Regulation (EU) 2019/945 (unmanned aircraft systems)
  • UNE 197001 (general criteria for expert reports and opinions)
  • Law 1/2000 on Civil Procedure (expert evidence)
  • Law 50/1980 on Insurance Contracts
  • Royal Legislative Decree 7/2004 (Legal Statute of the Insurance Compensation Consortium)
  • Regulation (EU) 2024/1689 (Artificial Intelligence Act)
  • Regulation (EU) 2016/679 (GDPR)
Syllabus

8 modules · 800 h

  1. 1.1Role of the insurance loss adjuster and professional framework
  2. 1.2Types of claims that can be assessed
  3. 1.3Classic inspection and valuation methodology
  4. 1.4Video assessment and self-assessment by the insured
  5. 1.5Chain of custody of digital evidence
  6. 1.6Expert report requirements and evidential validity
  7. 1.7Timelines and loss adjustment processes
  8. 1.8Loss adjustment efficiency indicators
  9. 1.9Limitations of remote loss adjustment
  10. 1.10Case study: comparison of an on-site and a digital claim file
  1. 2.1Fundamentals of convolutional neural networks
  2. 2.2Classification of damage images
  3. 2.3Object detection with YOLO and Faster R-CNN
  4. 2.4Semantic and instance segmentation of damage
  5. 2.5Severity estimation from images
  6. 2.6Creation and labelling of claims datasets
  7. 2.7Data augmentation and class imbalance
  8. 2.8Metrics: precision, recall, mAP and IoU
  9. 2.9Model biases and typical errors
  10. 2.10Laboratory: dent detector for vehicle bodywork
  1. 3.1Types of RPAS: multirotor and fixed-wing
  2. 3.2RGB, thermal and multispectral sensors
  3. 3.3Planning inspection flights
  4. 3.4Commission Implementing Regulation (EU) 2019/947 and categories
  5. 3.5Royal Decree 517/2024 and requirements in Spain
  6. 3.6Operational safety and SORA risk analysis
  7. 3.7Compulsory insurance for drone operators
  8. 3.8Data protection in aerial capture
  9. 3.9Weather and airspace limitations
  10. 3.10Practice: flight plan for a roof damage claim
  1. 4.1Principles of photogrammetry and image overlap
  2. 4.2Structure from Motion (SfM)
  3. 4.3Point clouds and 3D meshes
  4. 4.4Orthomosaics and digital surface models
  5. 4.5Software: Pix4D, Metashape and ODM
  6. 4.6Measurement of damaged areas and volumes
  7. 4.7Accuracy, control points and RTK
  8. 4.8Thermography applied to damp and fire damage
  9. 4.9LiDAR mounted on drones
  10. 4.10Laboratory: 3D model of a damaged roof
  1. 5.1Household and community claims
  2. 5.2Water, wind and hail damage
  3. 5.3Industrial fires and valuation of remains
  4. 5.4Floods and the Insurance Compensation Consortium
  5. 5.5Agricultural claims and crop damage
  6. 5.6Mass assessment following catastrophic events
  7. 5.7Satellite imagery as expert support
  8. 5.8AI-driven prioritisation of claim files
  9. 5.9Coordination of teams in large-scale events
  10. 5.10Case study: loss adjustment after a DANA (flash flood event)
  1. 6.1Data extraction with OCR and NLP
  2. 6.2Automatic cost estimation
  3. 6.3Integration with vehicle valuation systems
  4. 6.4Business rules and straight-through workflows
  5. 6.5Detection of fraud indicators in images
  6. 6.6Detection of manipulated or reused images
  7. 6.7Deploying models in the cloud and on mobile
  8. 6.8Human oversight and review thresholds
  9. 6.9Logging and traceability of decisions
  10. 6.10Workshop: automated workflow for a glass claim
  1. 7.1Regulation (EU) 2024/1689 on Artificial Intelligence
  2. 7.2Model explainability for the insured
  3. 7.3GDPR and processing of images of people
  4. 7.4Loss adjuster's liability for AI-assisted decisions
  5. 7.5Validation and auditing of loss adjustment models
  6. 7.6Change management across networks of loss adjusters
  7. 7.7Service quality and customer experience
  8. 7.8Cost and cycle time indicators
  9. 7.9Return on investment in digital loss adjustment
  10. 7.10Case study: impact assessment of an AI system
  1. 8.1Selection of the type of claim
  2. 8.2Design of the drone capture protocol
  3. 8.3Building the image dataset
  4. 8.4Training the damage model
  5. 8.5Generation of the 3D model and measurements
  6. 8.6Integration into the expert report
  7. 8.7Validation against conventional loss adjustment
  8. 8.8Cost-benefit analysis
  9. 8.9Dissertation and presentation
  10. 8.10Final review with the tutor
Methodology, software & labs

How you'll learn

100% online training on the SEIUM campus, with downloadable material, recorded classes and an assigned technical tutor. No fixed timetable: students progress at their own pace within the intake, which makes it easy to combine with work.

Each module combines theory, guided reading of the original standard and applied exercises. The working software is Pix4Dmapper, Agisoft Metashape, DJI Terra, CloudCompare, Python (OpenCV, PyTorch), in free, academic or evaluation versions. Trials are studied using real inspection flight procedures for damaged roofs and façades, 3D photogrammetric reconstruction of damage, and automatic classification of damage in images. Assessment is continuous, module by module, plus the final integrating project.

Accredited laboratories(EN ISO/IEC 17025) with a rotor test rig, EMC/Lightning pre-compliance, HIL/SIL, vibration/acoustics.
Evidence-focused thesis:safety case, test plan, compliance dossier and operational limits.
Industry-led mentoring:lecturers with experience in training, , eVTOL/UAM and flight test.
Flexible format(hybrid/online), international cohorts and support from SEIUM Career Services.
Ethics and safety:a safety-by-design approach, with cyber-OT, DIH and compliance as its pillars.
Capstone project

Build it end to end

Your final project follows the real engineering workflow, step by step, reviewed by your tutor.

Selection of the type of claim

Compare traditional and digital loss adjustment methods.

Design of the drone capture protocol

Apply computer vision techniques to identify and quantify damage.

Building the image dataset

Plan drone operations in line with European UAS regulations.

Training the damage model

Generate 3D models and orthophotos through photogrammetry for damage measurement.

Generation of the 3D model and measurements

Organise mass loss adjustment following catastrophic events.

Career opportunities

Where this takes you

Digital insurance loss adjusterDrone pilot for expert inspectionPhotogrammetry technicianComputer vision analystLoss adjustment coordinator for catastrophesClaims innovation manager
Admissions & scholarships

Requirements

  • Prior technical training or professional experience in the sector. A university degree is not required.
  • Internet connection and a computer capable of running the programme's software.
  • Sufficient Spanish to follow technical regulatory texts.

Ready to start?

Send your application today. Our admissions team replies within 72 hours with your study plan and funding options.

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FAQ

Frequently asked questions

The programme totals 800 hours spread over 6 to 8 months. That is an average of 10 to 15 hours per week, compatible with a full-time job.

You will work with Pix4Dmapper, Agisoft Metashape, DJI Terra, CloudCompare, Python (OpenCV, PyTorch). Free, academic or evaluation versions are used, and the tutor indicates the free alternative where one exists.

An SEIUM own diploma upon passing the continuous assessment and the integrating project. This is in-house training, not an official qualification from the Ministry.

Yes. Modules passed in a course or postgraduate diploma in the same area are recognised in the advanced programme. Check the recognition policy when enrolling.

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