Gather                         Consolidate                        Optimize                      Distribution

Source data from various locations and providers

Business Processes, best source selection, valida- tion, normalization

Data distribution based on Entitlement, Intraday up- dates, Delayed data up- dates, queries from down- stream applications

Master data, rules, model, maintenance

  1. Establish End-to-end data footprint of an organization.
  2. Define information model of the organization.
  3. Document and standardize application landscape, interfaces and information flow.
  4. Document and standardize business rules catalogue.
  5. Orchestrate business value chain of an organization and link it to actual process and capabilities.
  6. Define organization capability map (three dimensional map of organization capabilities, asset classification, IT systems).
  7. Define target landscape and outline roadmap to realize it within an agreed timeframe.
  8. Classify Information Entities according to Maturity Level, Criticality and Impact.
  9. Define relationships between Information Entities, IT Systems and Processes.
  10. Define Logical and Physical Financial Market Data Model of the organization. This model can be integrated within Operational Data Store, Reporting Data warehouse and other functional databases.
  11. Standardize data consumption and publication across data warehouse or enterprise data bus. Define shopping cart’s to simply information consumption from the data warehouse.
  12. Define Canonical (standardized) formats for transaction data consumption like trades, positions, valuations etc.
  13. Assess Data Quality of an Organization and place it on a Maturity Model.
  14. Define and set-up key data indicator’s (KDI’s) to monitor and control data quality.
  15. Establish governance structure, business rules and processes to maintain High Data Quality standards.
  16. Assign data governors, data owners and data stewards to key data sets creation, procured and/or derived in the organization.
  17. Establish framework for creation and/or amendment of data sets like addition a new management reporting attribute in multiple IT systems.
  18. Establish forums to discuss and highlight data quality issues. We cover setting-up of the forums, establish clear mandates, bring everyone on the same page, define forum policies and ensure participation. Forum are initially chaired and coordinated by us before internalizing it within the organization itself.
  19. Business case creation and senior stakeholder alignment within the organization for set-up of Data Quality, Governance, Transformation and Management initiatives. We offer consulting on what can or can’t be part of such program’s, organization structure, guiding principles, key milestones and timeline.
  20. Evaluate middleware, messaging infrastructure of an organization. Assist organizations in set-up of Enterprise Data Bus involving info broker, data dictionary, business integration layer and operational data store.
  21. Assist organizations in vendor survey (RFI, RFP evaluations, creation of questionnaire, ranking system) in the area of data quality, integration, publication, consumption etc.

  1. Document and Evaluate present vendor contracts and suggest ways to improve it.
  2. Establish internal market data cost allocation and propose ways to introduce transparency and ownership.
  3. Evaluate market data IT landscape and underlying processes.
  4. Propose enterprise-wide target landscape vis-a-vis market data.
  5. Evaluate market data life cycle processes (corporate actions) of the organization.
  6. Evaluate and harmonize market data vendor terminals. Propose user profiles to assess market data terminal requirements.
  7. Assess market data consumption within IT applications and suggest ways to optimize it.
  8. Architect and implement market data enterprise platform for the organization.
  9. Define gold & silver copies for relevant Market Data like Security Master, Ratings, Prices, Analytics, Timeseries, Corporate Actions etc.

  1. Document all key internal data items produced in the organization along with their processes, business rules and IT systems.
  2. Optimize Master (internal) data creation, amendment and termination processes.
  3. Define gold & silver copies for relevant Master (internal) Data.
  4. Define target landscape for creation and maintenance of Master (internal) data.
  5. Define relevant reconciliations to maintain Master (internal) data quality.
  6. Establish processes, repositories, workflows, validations etc. for key internal data sets like Legal Entities, Portfolios, Counterparties, Cost & Profit Centre, Settlement & Payment Instructions, Bank Accounts etc.
  7. Define Master (internal) data consumption rules and policies.

  1. “Evaluate needs of organization
  2. B2B – With a focus on Asset managers, Relationship managers, External Asset Mgmt companies, etc
  3. B2C – With a focus on customer porfolio, Private banking customers and bank book”
  4. Define Landscape for creation & maintenance of Reference data
  5. Propose structure to organization to introduce LEI, usage monitoring, Trade expense, transaction reconciliation, FIX connectivity, etc

  1. Formulate data retention policy for the organization and work with respective IT systems owners to ensure the agreed policy is reflected within the system and processes.
  2. “Access Data Set-up and Security of an organization in light of regulatory mandates like Sarbanes-Oxley Act (SOX), Payment Card Industry
  3. Data Security Standard (PCI-DSS), Federal Information Security Management Act (FISMA), and the EU Data Privacy Directive.”
  4. Prepare organizations against five most common data theft related risks – Review data access set-up to ensure Excessive privileges and privileged user abuse, Unauthorized privilege elevation, SQL injection, Denial of service and Exposure of backup data.
  5. Propose process, technology and governance structure on how organizations can leverage a holistic data security and privacy approach.
  6. Define Data Confidentiality (Data Access Controls, Data Encryption and Data Anonymization), Data Integrity (Modification Tracking, Data Accountability, Data Authenticity), Data Availability (Data Access Mechanism, Data Loss Prevention, Downtime Prevention).

  • Evaluation of Business reconciliation processes like position, PnL or Cash reconciliations.
  • Evaluate maturity of IT landscape supporting reconciliation needs of the organization.
  • Propose ways to optimize, centralize and automate reconciliations.
  • Propose ways to align reconciliation processes with data governance needs of the organization.
  • Gap analysis between as-is and proposed reconciliation set-up of the organization.
  • Reconciliation catalogue along with documenting all key dimensions.
  • Define guidelines to evaluate and benchmark any future reconciliation needs.
  • Define reconciliations to support data quality & governance processes.
  • Assist organizations to set-up center of competency (CoC) around Reconciliation. This can lead to consolidation of reconciliations within a single team or a distributed set-up with clearly outlined responsibilities.

  • Prepare reporting catalogue along with documenting all key dimensions like who uses it, for what, when & how it is generated.
  • Establish reporting IT landscape of the organization.
  • Propose ways (technical, process related) to optimize, centralize and automate reporting landscape.
  • Establish end-to-end data lineage for reports and identify areas of concern.
  • Design and implement reporting data warehouse.
  • Define guidelines to evaluate and benchmark any future reporting needs.
  • Define MIS and Operational reports to support Data Quality & Governance processes.

  1. Assess IT release, change and deployment management processes and propose ways to improve it.
  2. Assess cost allocation framework for any cost and/or profit center of an organization and propose ways to improve it.
  3. Access project management best practices of the organization, benchmark it against industry standards and develop roadmap to achieve agreed maturity level.
  4. Access Business Analysis capabilities available within the organization, align it with industry standards and propose ways to improve it.
  5. Evaluate incident reporting infrastructure of an organization and propose ways to fill the gaps identified during the analysis.

  1. Assess testing set-up, approach and its maturity.
  2. Establish Quality Assurance as a horizontal concept applicable to all projects and BaU activities.
  3. Define case (project, bau) based cost efficient testing approach’s and models for organization.
  4. Evaluate testing automation tools and methodologies for a given project, department or organization.