Business Analyst

MORELA Business Analyst AI Transformation Programme | Financial Services | London, Hybrid About the Client Morela is supporting a leading UK management consultancy with a strong Financial Services practice, known for delivering complex change and transformation programmes for regulators, banks and insurers. They pair senior business consulting with hands-on delivery, and work closely alongside their clients’ own teams rather than handing over a report and walking away. This engagement supports a major UK financial services regulator’s AI transformation programme. Having established its initial AI foundations, the programme is now scaling AI across the organisation, including building the technical foundations needed for an increasingly agentic operating model. The Role This is a 9-month contract, with the option to extend by a further 6 months, starting early to mid November 2026. The role sits Inside IR35, so you must be comfortable working under those arrangements. It is based in London on a hybrid basis, with 50% of your time in the office. There are two Business Analyst positions available. You will support delivery of a key workstream within the programme, working across senior business stakeholders and technology and product delivery teams. A big part of the job is taking complex human workflows and turning them into measurable processes that are ready for AI-enabled delivery, with the right human-in-the-loop controls, decision thresholds and guardrails built in. We are looking for someone with around 5 to 7 years of relevant experience. Responsibilities Lead requirements elicitation, capturing use cases, user stories and acceptance criteria. Model As-Is and To-Be processes across complex business workflows. Translate human workflows into measurable processes suitable for AI-enabled delivery. Define human-in-the-loop controls, decision thresholds and appropriate guardrails. Translate policies and standards into processes, procedures and technical requirements. Facilitate workshops and manage stakeholders across senior business and technology teams. Turn business requirements into clear functional outcomes for product, technology and data teams. Identify opportunities to improve and simplify processes as the programme scales. Essential Requirements Experience working within Financial Services, regulatory bodies or similarly complex regulated environments. Substantial Business Analyst experience across the full project lifecycle on complex projects or programmes. Strong requirements gathering and process modelling capability, including As-Is and To-Be. Able to operate effectively in uncertain or challenging environments. Excellent facilitation and stakeholder management skills. Strong written and verbal communication, with the ability to translate business requirements into functional outcomes. Strong business acumen and the ability to get up to speed on new subject matter quickly. An innovative, process improvement mindset. Ability to translate policies and standards into processes, procedures and technical requirements. Desirable Experience Technical experience implementing Agentic AI. Defining requirements for AI-enabled solutions, including use cases, user stories, acceptance criteria and measurable outcomes. Understanding of AI governance and Responsible AI. Defining human-in-the-loop controls, decision thresholds, escalation and override mechanisms. Working alongside product, technology and data teams. Business architecture, service design or transition experience. Considering AI fairness, bias, transparency and impacts on vulnerable groups. Working Environment You will work hybrid, spending half your time in the office in London and the rest remotely. You will be part of a consultancy team embedded in a high-profile regulatory programme, working directly with senior stakeholders on work that shapes how AI is used across the organisation. It suits someone who is comfortable with ambiguity, enjoys bringing structure to complex problems, and wants real exposure to agentic AI in a regulated setting.