Capital Markets Data, AI & Transformation — Consulting / Business Analyst

Accenture Global Network · Capital Markets (Financial Services) Data, AI & Transformation

Join the Global Network to work on high-impact transformation programs with leading global clients, contribute to differentiated offerings, and build your consulting career in a fast-paced, collaborative and innovation-led environment.

Practice Overview

This role focuses on Data, AI, and Transformation, covering data management, analytics, governance, data quality, reconciliations, regulatory initiatives, and AI-enabled business transformation.

Role Requirements:

• Operating Group: Capital Markets (Financial Services)
• Location: Manila
• Level (Experience): ○ Analyst (3–6 years) ○ Consultant (7–11 years) ○ Manager (12–16 years) ○ Senior Manager (17+ years)
• Travel Requirement: ○ Expected travel may range from 0% to 100%, depending on project and client needs.

Role Summary

The candidate will work with Accenture’s Global Network Capital Markets practice to deliver consulting and transformation engagements for global financial services clients. The role requires a strong combination of Capital Markets domain knowledge, consulting skills, business analysis capability, data transformation understanding and AI-enabled reinvention mindset.

The candidate will help clients assess current-state processes, data flows, systems and controls; define target-state operating models; design data and analytics solutions; support business requirements; and drive execution across large-scale transformation programs.

• Deliver Capital Markets consulting, business analysis, and transformation projects.
• Lead initiatives in data management, governance, quality, analytics, and data products.
• Improve reconciliation, controls, and exception management processes.
• Define target operating models and support business requirements, testing, UAT, and change management.
• Drive AI-enabled process transformation, automation, and operational efficiency.
• Collaborate with clients and stakeholders across global teams.

• Data Management: Data strategy, architecture, governance, and AI-ready data foundations.
• Analytics & Insights: Reporting, KPI development, analytics, and AI-driven business insights.
• Data Products: Design and delivery of reusable data products for business and regulatory use cases.
• Data Governance: Data ownership, stewardship, lineage, controls, compliance, and AI governance.
• Data Quality: Data quality frameworks, monitoring, issue remediation, and governance.
• Reconciliations & Controls: Trade, cash, and regulatory reconciliations, exception management, and process automation.

Technical Know-How (Nice to Have)

Candidates should have working knowledge of Capital Markets data platforms, data feeds, and industry processes, including:

• Market and reference data sources (e.g., Bloomberg, Refinitiv, ICE, S&P Global/Markit)
• Financial messaging and integration standards such as SWIFT, FIX, FpML, ISO 20022, APIs, XML, and JSON
• Trade lifecycle processes across trading, risk, settlement, accounting, reporting, and reconciliation functions
• Data governance, master data management (MDM), and data quality tools such as Collibra, Informatica, Reltio, Alation, Ataccama, and IBM MDM
• Capital Markets platforms such as SmartStream TLM, Murex, Calypso/Adenza, Aladdin, SimCorp, Charles River, Duco, ReconArt, and Broadridge

Responsibilities by Level

Analysts / Consultants

Analysts and Consultants are expected to support project delivery and independently own defined workstreams under guidance. Key responsibilities include:

• Support business analysis, data analysis, PMO, testing and presentation development.
• Conduct process mapping, current-state assessment and gap analysis across Capital Markets functions.
• Own BRDs, FRDs, user stories, functional specifications and requirement traceability.
• Support data discovery, data profiling, source-to-target mapping and data lineage documentation.
• Support design of data quality rules, data controls, reconciliation rules and exception workflows.
• Analyze data issues, reconciliation breaks and operational exceptions.
• Support UAT planning, test case preparation, test execution and defect triage.
• Prepare stakeholder-ready documentation, dashboards, operating model packs and executive presentations.
• Work independently with client SMEs, product owners, operations users, technology teams and delivery teams.
• Contribute to problem structuring, insight generation and recommendation development.
• Demonstrate foundational understanding of Capital Markets products, processes and data flows.
• Build awareness of AI, automation and data modernization use cases across Capital Markets.

Manager

Managers are expected to lead workstreams or projects end-to-end, manage teams and own client delivery outcomes. Key responsibilities include:

• Lead independent workstreams or full project delivery across Capital Markets transformation programs.
• Drive data strategy, data governance, data quality, reconciliation, analytics and operating model workstreams.
• Lead current-state assessment, target-state design and roadmap development.
• Define Target Operating Models covering people, process, data, technology, governance and controls.
• Manage delivery teams across onshore, offshore and client environments.
• Own program governance, project planning, RAID management, status reporting and delivery quality.
• Lead stakeholder workshops, requirement discussions, playback sessions and solution walkthroughs.
• Drive data issue resolution, reconciliation remediation, control uplift and operational efficiency initiatives.
• Support AI-enabled process transformation and identify automation opportunities.
• Lead proposal development, RFI/RFP/RFQ responses and solution shaping.
• Build client relationships and support account growth.
• Contribute to offering development, POVs, methodology refinement, training and capability building.
• Manage people development, staffing, delivery quality and risk management.
• Perform responsibilities expected at prior levels, where required.

Senior Manager

Senior Managers are expected to drive strategic client relationships, sales, offering development and end-to-end delivery accountability. Key responsibilities include:

• Build trusted relationships with senior client stakeholders and account leadership.
• Drive Capital Markets data, AI and reinvention-led transformation opportunities.
• Shape large-scale programs across data management, governance, analytics, reconciliations, operations and technology modernization.
• Lead client conversations on strategic direction, value case, operating model and implementation roadmap.
• Own end-to-end delivery accountability for quality, risk, stakeholder management and business outcomes.
• Lead sales pursuits, solutioning, commercial shaping and client orals.
• Run CoE-aligned campaigns for new account growth and offering adoption.
• Develop market-relevant offerings across Capital Markets data products, AI-ready data, data governance, data quality and reconciliation transformation.
• Mentor teams, counselees and future leaders.
• Support hiring, retention, utilization, engagement initiatives and skill development.
• Collaborate with industry leads, account teams and global delivery teams to secure and deliver high-impact deals.
• Perform responsibilities expected at prior levels, where required.

• Prior experience in consulting or transformation projects is required.
• Experience working with Capital Markets, Investment Banking, Asset Management, Wealth Management, Market Infrastructure or broader Financial Services clients.
• Strong understanding of front, middle and back-office processes.
• Experience in strategy, operations, process redesign, business architecture, data transformation or technology improvement programs.
• Experience preparing business requirements, functional specifications, operating model documents, process maps, project plans and executive presentations.
• Experience working in Agile or hybrid delivery environments.
• Experience collaborating with business, operations, technology, data, risk, finance and compliance stakeholders.
• Strong problem-solving, communication, documentation and stakeholder management skills.
• For Manager and Senior Manager levels, strong experience in client management, delivery leadership, proposal development, RFI/RFP/RFQ support and team management is required.

Capital Markets Knowledge

Candidates should have understanding of one or more of the following:

• Equities, fixed income, FX, listed derivatives, OTC derivatives, structured products, funds and alternatives.
• Trade lifecycle from order capture to execution, confirmation, clearing, settlement, accounting and reporting.
• Front-office, middle-office, risk, finance, operations and post-trade processes.
• Reference data, market data, product data, trade data, position data, pricing data, client data and counterparty data.
• Regulatory reporting and change programs.
• Control, reconciliation and exception management processes.

Data and AI Skills

Candidates should demonstrate experience or strong interest in:

• Data management and data operating models.
• Data governance and stewardship.
• Data quality management and remediation.
• Data products and data ownership.
• Data lineage, metadata and cataloging.
• Data analytics, reporting and KPI design.
• Data migration, source-to-target mapping and data validation.
• Reconciliations, controls and exception management.
• AI-ready data foundations.
• Generative AI and agentic AI use cases in Capital Markets operations, risk, reporting and client servicing.
• Intelligent automation, workflow digitization and process optimization.

• Master’s degree in management or equivalent qualification is preferred, such as MBA, PGDBM, MMS or equivalent.
• FRM, CFA, PRM or other industry-specific certifications are an added advantage.
• Data, cloud, AI, Agile, product management or platform certifications are also desirable

Key Competencies and Skills

The candidate should demonstrate:

• Strong Capital Markets domain knowledge.
• Strong consulting mindset and structured problem-solving.
• Ability to translate business problems into data, process and technology requirements.
• Strong analytical mindset and ability to derive insights from complex information.
• Excellent written and verbal communication.
• Strong presentation and client interaction skills.
• Ability to work with senior stakeholders and cross-functional teams.
• Ability to manage ambiguity and deliver in fast-paced environments.
• Understanding of AI, data, digital, automation and emerging technologies.
• Ability to keep pace with changing industry trends, regulatory expectations, market practices and technology shifts.
• Ability to build and maintain trusted working relationships across client, Accenture and partner teams.