1. Sukant: What trends do you see in the data management space?Are these trends similar across Tier 1 and Tier 2 banks?
Virginie: The changing regulatory landscape has been the biggest driver for investment in data management over the last few years. Transparency requirements have increased across the globe, which has impacted both the buy-side and the sell-side and highlighted the reputational and operational damage that can be caused by poor quality data. Fines for non-compliance and onsite inspections by regulators that entail detailed review of operational practices, combined with much more frequent reporting requirements have resulted in a nexus of internal data management investment drivers. The byproduct of this has been the gradual increase in chief data officers across the industry – though they are far from ubiquitous yet.
Financial institutions overall have much more awareness of their data shortcomings (even if they still struggle to quantify and qualify these problems); hence data governance programs are much more commonplace, even within asset management firms. The desire for firms to make better use of their data assets has been a common topic of conversation over recent months – so I expect a lot of discussions to encompass this notion, even if a lot of it is just talk. Before any data optimization or monetization strategy can take place, firms first need to understand and improve their data quality issues.
The challenges that banks face really depend on their operational structure – those Tier-1 firms that have undergone a huge amount of M&A activity tend to struggle more with data management because of the high level of siloed systems. Data aggregation is by far the biggest challenge for all financial institutions and regulatory reporting is reliant on this process.
2. Sukant: What is your view on industry initiatives like DTC-Clarient, Reuters-Accelus and others?
Virginie: I think there has been a lot of noise in general about "utilities" in the market as a result of an increased focus on operational risk and cost. Firms are naturally keen to reduce duplicative processes and superfluous spending in areas that are perceived to be non-competitive – and many back office areas could fall into this category. In this light, any shared service that provides a basic level of support for financial institutions in key areas such as data cleansing support is likely to be appealing. The main benefit of a utility would be in providing scale and a single point of access for firms, clients, and counterparties, and taking away some of the manually-intensive tasks to which internal full-time employee resources are dedicated. Collecting KYC data from a client once and then disseminating it to the client's service providers is much more efficient than the client providing the same documentation to each service provider individually.
There is some reticence on the part of the industry to hand over processes to a single monopoly provider that is purely for-profit because of the potential cost monopoly but also the idea of being able to influence the service roadmap in future—there is a desire for some degree of choice in the market, rather than only one option.
3. Sukant: Can data quality management be industrialized and serviced through a subscription or utility model?
Virginie: Data quality is a tricky but important area for most financial institutions to tackle in light of increased transparency requirements and regulatory changes. Most firms struggle with the first mile of establishing data quality metrics due to the lack of industry best practices or standards, and the cultural challenge of getting various business lines to agree on common data items of importance. Certainly, having some external metrics or input could help teams charged with implementing data governance programs to get these various internal data consumers and owners to begin to collaborate in a more effective manner.
Once a framework has been agreed by internal teams, there is no reason why a firm could not also seek external assistance in putting data quality metrics into practice. Eliminating internal manual effort and providing a central framework for the implementation of common data quality metrics is an appealing prospect for data management teams that are often under-resourced and overburdened with regulatory projects.
4. Sukant: In the post utility era, what are the top 5 data quality management initiatives will help differentiate the leading banks from the rest?
Virginie: I'd say we are in the early days for the utility even though the model has been around for a while. Given that there is a lot of current interest in these utilities, however, there is the potential that they will become ubiquitous in future for areas such as KYC data collection. If this comes to pass, being able to get to a state where you have a good idea of the data assets that a firm has, where they are stored, and which functions are using them (priority internal clients) will help to differentiate firms on a data management basis. Understanding that data management and data quality cannot be solved with a one-off project and that they require continuous feedback is also a factor that will set firms apart in future. This, however, is contingent on recognition of that dynamic at the top of an organization (C-level) and commitment to continued investment and improvement in the longer term.
5. Sukant: When it comes to data management, what is the value that a service provider like Wipro can bring to capital market firms?
Virginie: Service providers such as Wipro can help financial institutions to understand and implement any emerging best practices within the realm of data management from the benefit of working with other firms. This would certainly be helpful in areas where industry-wide standards are lacking such as data quality measurement by providing a steer in terms of how to tackle common challenges in terms of technology and processes. Though operational structures differ between firms, there are certainly lessons that can be learned from the experiences of vendor partners with other clients. There is much more of a trend for firms to partner with their providers in the current environment due to the level of complexity involved in data management at a time when regulators and the market as a whole is much more aware of the importance of the function.
