Significant regulatory pressures and fierce competition have made data quality management a core organisational requirement and, more importantly, a source of competitive advantage. If the reliability and quality of data is inconsistent it can be potentially misleading and faulty, resulting in harmful conclusions.  

Problems in data management often arise from poor definition of roles and responsibilities, and lack of senior management and/or steering committee sponsorship and buy in. Although data quality is not purely an IT issue, it also relies heavily on strong partnerships between business and technology functions.

Common weaknesses in data quality management include:

• A lack of institutionalised data strategies and governance frameworks;
• An absence of a vision for data management change;
• A lack of performance targets or allocation of resources;
• Data quality enhancement frameworks and policies developed in silos and not spanning across the functions or the various levels within an organisation.  

We help organisations to improve data quality. Our offerings, which are supported by a proprietary methodology, include:

• Establishing a data management governance structure by defining roles and responsibilities, and developing and implementing data quality management strategy;
• Developing, documenting and rolling-out data quality policies and standards;
• Designing a common data architecture across the organisation, developing and promoting data quality awareness and communication plans, and defining data quality requirements and business rules (for data transformation);
• Designing, implementing and monitoring operational data quality management procedures, testing and validating data quality requirements;
• Analysing, profiling, measuring and monitoring data quality, setting data quality service levels, certifying and auditing data quality, identifying, escalating and resolving data quality issues;
• Planning and conducting data cleansing programmes.

Case studies

Credit Risk Weighted Assets Quantitative Impact Analysis;

Basel II Credit Risk data integration / Common Reference data implementation;

Basel ll Advanced Internal Ratings Based (IRB) Approach;

Economic Capital Calculation and Management Data;

Basel II Subject Matter Expertise;

Credit Risk Model Validation;

Credit Risk Model Waiver Application Process;

Regulatory Compliance Strategy – Internal Ratings Based (IRB) Approach;

Market Risk Diagnostic;

Pan-European Credit Data Consortium (PEDC) Membership Application Process;

Basel II Reference Data Solutions;

Property Management Information Database;

End to end evaluation of the collateral management process;

Integration of credit risk reporting for global and institutional exposures;

Credit risk integration;

Credit Operational Reporting Tool (CORT) application;

Scenario Planning & Stress Testing;

Banking Integration - Capital Optimisation Project;

Integration of the Investment Banking Business Unit of a banking group acquired by the client - Post Migration Requirements Forum;

Global Risk and Capital Reporting;

Data Quality Project;

Risk and Capital Reporting;

Risk Data Management Information and Reporting;

Solvency II Programme mobilisation