- Focus Areas
|Benchmark V2 Test Page|
"The 2017 benchmarking study consists of 22 DCAM-derived questions that highlight the most essential concepts in data management. The results include comparison to the previous study performed in 2015. Participants included the full spectrum of financial services companies (universal, buy, sell, asset servicing, insurance) with an emphasis on G-SIBs and Tier 1 firms. We hand selected a "control group" of companies that we knew had demonstrated an organizational commitment to data management as the baseline for evaluating overall industry progress.
There are clearly some bright spots for the practice of data management. We have made progress in overcoming the intertia of organizational change management. But the underlying truth remains. We can't respond to regulatory pressure, achieve automation or put data to work until we fix the underlying data challenges. The EDM Council believes these obstacles can be addressed."
Highlights and Key Findings
The biennial study, done in collaboration with industry leader Sapient Consulting and Pellustro, the DCAM assessment platform developed by boutique strategy firm Element22, found progress toward setting up enterprise-wide data management programs and implementing data governance, but also highlights several key areas where industry capabilities lag in meeting the requirements set out by global regulators and market authorities.
The survey covers 22 of the most essential concepts extracted from the Council’s Data Management Capability Assessment Model (DCAM), and received responses from over 150 financial institutions.
Establishing the Program
Data management as a core part of the way financial institutions operate is growing, but not fully entrenched. There has been some advancement in establishing a true “data management culture” particularly among G-SIBs and Tier 1 buy-side firms.Over 70% of the industry, and 90% of G-SIBs, now have a Chief Data Officer.
The industry has made substantial progress in establishing foundational governance, defining organizational structures, implementing data stewardship and implementing operational policy.
Work is underway on defining lineage, managing critical data and implementing data management glossaries. This is the core building block for meeting the regulatory goals of harmonized data necessary for linked risk analysis but progress has been slow to mature. Only 8% of the industry has achieved the harmonization of meaning of data across all internal repositories.
The industry is still mired in manual reconciliation of data and mapping from physical repositories to applications and reports. Trust and confidence in the data used for regulatory reporting and business analytics remains an elusive goal of these data management programs. Just 13% of the industry has achieved the definition and implementation of control procedures for managing data quality.
There is a growing understanding of data as a shared resource and timely progress in managing the collaboration between data, information technology, business applications and control functions such as information security and privacy.