Digital Transformation: Technology, Risk and Regulatory Judgement
What you must understand
Candidates should understand how digital channels change distribution, onboarding, servicing, and risk. Key concepts include open banking and application programming interfaces, cloud computing, robotic process automation, artificial intelligence and machine learning in credit scoring and advice, distributed ledger technology, digital identity and e-KYC, and mobile payments. Know the regulatory themes: data protection and consent, operational resilience, outsourcing and third-party risk, model risk and explainability, cybersecurity, and consumer protection including fair treatment and suitability of automated advice.
Traps that appear in questions
- Automation versus advice. A robo-adviser that gives personalised recommendations is providing advice and must meet suitability obligations; a comparison tool that only ranks products may not.
- Outsourcing does not outsource accountability. The regulated firm remains responsible for third-party failures.
- Explainability. A model can be accurate yet non-compliant if decisions cannot be explained to customers or regulators.
- Data minimisation. Collecting more data than needed is a breach of principle, not a sign of thoroughness.
- Resilience versus security. Cybersecurity is one component; operational resilience covers the ability to keep serving customers through disruption.
Worked example
A bank deploys a machine-learning model to approve small-business loans. It improves approval rates but rejects applicants with thin credit files. The correct response is not simply to keep the model because it is profitable. The firm should test for disparate impact, document the model, provide adverse-action reasons, keep human review for edge cases, and monitor outcomes. A question offering "retrain the model and continue" as an answer is usually the trap; governance and explainability are the expected answer.
Rule of thumb
For any digital initiative, ask: who is accountable, can the decision be explained, is customer data minimised and consented, and can the service survive disruption?