See how real hazards are named, rated before and after controls, and assigned to an owner. Each assessment is built around a vaayaa course, so you learn the method in the field you are studying.
Choose the field closest to your course.
Every page follows the same simple pattern.
Each hazard describes what could go wrong and who could be affected.
Likelihood times impact gives a score from 1 to 25, first before controls and then after.
Existing and additional controls explain how the score comes down.
A named role owns each hazard and a trigger says when to look again.
A worked example of how an investment banking analysis team finds, scores and controls risks in valuation models, deal processing, market exposure, confidential data and professional conduct.
A worked example of how a deal and trading team finds, scores and controls the risks that threaten accurate transactions, sound valuations, market and counterparty exposure, and trust in capital markets activity.
A worked example of how an IT service team finds, scores and controls the risks that threaten access, service availability, data and recovery, from identity compromise and malware to failed changes and supplier exposure.
A worked example of how an enterprise IT operations team identifies, scores and controls the risks that threaten service availability, data confidentiality and integrity, and recovery from disruption.
A worked example of how a clinical and research laboratory team identifies, scores and controls the risks that affect specimens, instruments, patient data, research integrity and staff safety.
A worked example of how a small team that runs a large language model finds, scores and controls risks to confidential data, access keys, output quality and service availability, with owners, warning signs and review triggers.
A worked example of how a small lead generation team identifies, scores and controls the risks that affect campaign results, brand trust, privacy duties and budget.
A worked example of how a team leader finds, scores and controls the risks of managing people, from biased decisions, conflict and overload to skills gaps, confidential records, policy duties and key person dependence.
A worked example of how an insurance operations team finds, scores and controls risks in life and health claims, policy administration, customer data, conduct and reporting, showing inherent and residual ratings.
A worked example of how a boutique hotel finds, scores and controls risks to guest safety, privacy, service quality, payments and reputation, with named owners and review triggers for each risk.
A worked example of how an engineering team finds, scores and controls the risks that threaten training data, model integrity, deployed AI services and the people affected by their predictions.
A worked example of how a marine engineering team finds, scores and controls the risks that threaten vessel stability, machinery, electrical safety, people, the marine environment and the build programme.
A worked example of how a research team finds, scores and controls the risks that threaten valid consumer insights, from biased samples and faulty pipelines to privacy breaches and misused third-party data.
A worked example of how a marketing analytics team finds, scores and controls the risks in tracking, attribution, paid spend, fake traffic, creative claims and vendor reliance, so budgets and customer data stay protected.
A worked example of how a marketing team finds, scores and controls the risks that threaten campaign results, brand trust, legal compliance and customer data during strategy and positioning work.
A worked example of how a marketing team identifies, scores and controls the risks that can waste budget, mislead customers, breach privacy rules and damage the brand during strategy development and campaign delivery.
A worked example of how a marketing and public relations team finds, scores and controls the risks behind campaign claims, customer data, ad spend, accounts and public reputation, with owners and early warning signs for each.
A worked example of how a small metallurgy laboratory and heat treatment workshop identifies, scores and controls risks from furnace operation, alloy specification mismatch, test sampling errors and operator decisions.
A worked example of how a small equipment manufacturer finds, scores and controls risks from machine guarding, component failure, supplier quality, maintenance backlogs and conformity records.
A worked example of how a media and publishing business identifies, scores and controls risks to titles, events, rights, data, finances, people and reputation, with clear owners and review triggers.
A worked example of how a hospital imaging department finds, scores and controls risks to patients, staff, equipment and image data, from dose and identification errors to contrast reactions, staffing and handover.
A worked example of how a diagnostic laboratory finds, scores and controls the risks that threaten specimen identity, analytical quality, result reporting, staff safety and service continuity, with owners, warning indicators and escalation routes.
A worked example of how a mental health service finds, scores and controls risks to patient safety, escalation, consent, records, staffing, infection exposure and professional scope.
A worked example of how an advisory team identifies, scores and controls the risks that can undermine an acquisition or merger, from weak valuation and leaked deal information to conflicts, funding gaps and failed integration.
For Learning Reference Only: This assessment demonstrates how risk assessment principles are applied in a practical setting, providing a useful reference for learning and understanding. Actual assessments may be adapted to suit specific site conditions and circumstances.
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