The CDO: Key To Success of Financial Big Data Initiatives

The CDO: Key To Success of Financial Big Data Initiatives

Chief data officers (CDOs) are necessary to help companies solve challenges when it comes to implementing effective Big Data strategies, according to a new report from Capgemini Consulting.

However, even though financial services firms understand that they need to better manage their data to meet increasing regulatory requirements as well as increase profitability, many of them are still unable to put effective big data practices into place.

In fact, half of all financial services executives cite ineffective coordination of Big Data and analytics teams as the biggest challenge to implementing Big Data initiatives, according to the report.

Even so, only 16% of these firms have appointed CDOs to help get the job done, while most of the others are not really taking full advantage of Big Data analytics.

In a Q&A published in bobsguide, Capgemini Financial Services vice president Ramana Bhandaru explains why the CDO will be the key to the success of Big Data strategies at financial services firms.

First, he points out that companies in the financial services sector are facing several challenges: the lack of Big Data professionals; the lack of data quality; and the lack of a customer-centric focus, which calls for a significant organizational realignment from a focus on products to a focus on customers.

Additionally, since Big Data has emerged as the platform for analytics, Bhandaru says the traditional line that separates a company’s IT team from the analytics team on the business side has started to blur in terms of their skills. And because the requirements for analytics roles have changed dramatically, data scientists now have to have a strong understanding of Big Data technologies–as well as statistics and traditional SQL-based tools–so they can create the analytic models.

“The technology teams have acquired the Big Data skill set faster and can bridge the gap on the analytic[s] side by hiring data scientists or training people internally,” Bhandaru notes. “This shift has started to create a power struggle between the organizations in terms of ownership of analytics.”

Also as Big Data technologies are still maturing, recent data breaches at well-known companies have thrown a spotlight on data security, data quality, and data governance specifically. The impacts of such breaches are not only financial, but reputational as well, Bhandaru says.

The impact of a data breach can result in significant financial, as well as reputational, losses for firms in the financial services sector. To overcome the challenges they face, financial services companies need to advocate for a new organizational structure that combines these two roles under a common leadership.

“Given all these factors and the importance of data, having a strong leadership role, such as a chief data officer, is as vital to an organization as leadership roles in areas like finance, marketing or risk,” he notes.

But how does a CDO achieve success in light of these challenges?

“With the introduction of Big Data capabilities in organizations, the demand for rapid access to more data has increased exponentially,” Bhandaru says. “Data science and analytics organizations tasked with deriving value and insights from the data are looking to eliminate the traditional IT cycles for access to the data.”

Rather, they’re insisting on self-service data discovery and business intelligence capabilities–and from a data management perspective that makes a CDO’s job tough, according to Bhandaru.

For a CDO to be successful, an organization must put in place a sound data governance practice that clearly delineates between sensitive and other data but still has the proper security and privacy capabilities in place, he notes.

“In summary, a CDO can achieve success by upgrading their capabilities to keep pace with this rapidly evolving data landscape,” Bhandaru says.