In a financial industry that keeps growing more complex and challenging, holistic solutions for managing high-quality reference data have become a competitive advantage for leading firms. For most investment banks, the current infrastructure is fragmented and expensive to run and maintain, and data management requirements have far outgrown the effective capacity of existing infrastructure. By outsourcing reference data operations, firms can conserve resources, meet regulatory demands, leverage expertise, access best-practices, increase scalability, and create an enduring cost advantage.
In fact, forward-thinking firms no longer view a managed data service as a potential solution, but rather as the new table stakes for competing in a changing industry. Even so, there are perceived obstacles that can delay initiatives or hinder decision-making. If a firm is paralyzed with indecision, or tries to respond to change with incremental internal projects that fail to produce desired results, it can be hard to overcome inertia. To make a positive impact, banks may first need to “clear the path” – i.e., address the perceived obstacles.
Although the obstacles vary with the size and culture of each firm, they often are variations on five themes. In each case, practical, simple answers can help put the obstacles in perspective, articulate a way to overcome them, and clear a path forward.
Obstacle #1: Cost-savings are projected, but don’t materialize. Internal projects are always over-budget.
Solution: Focus on driving and documenting all types of cost-saving. Broadridge has estimated that banks on average are spending between $75 million and $125 million annually to acquire, clean, normalize and distribute reference data across the enterprise. In addition, inaccurate data is the source of about 75 percent of costly operational problems in investment banks. Therefore, the issue is not a lack of cost-saving opportunity, but rather the ability to drive all types of cost-savings to the bottom line, in ways that can be clearly documented.
Taking a granular view of errors and exceptions, with detailed statistical analysis, can help to achieve cost control and document savings. Meeting expanding regulatory requirements more efficiently and confidently will result in a huge savings of both time and “worry cost” for top managers.
Obstacle #2: A lack of data quality standards and methods for monitoring and enforcing them.
Solution: Understand the capabilities a managed data service can provide, including quality-of-service metrics and service level agreements (SLAs). The core of a managed data service is its ability to define the state of data quality and then achieve measureable improvements in that quality over time. Working as the bank’s partner, a qualified service provider will deliver the experience and technology to support granular service-level agreements (SLAs), which can help to achieve this goal.
SLAs should provide financial penalties for breakdowns in service. They also can include a mature governance model and meaningful penalties for failure to perform up to standards. An emerging industry benchmark is to create customizable SLAs geared to each firm’s business model and profit drivers. For example, a firm’s trading desk may require reporting commitments every five minutes to meet timely processing requirements, while its asset management unit may only need an end-of-day SLA.
Obstacle #3: The transition process is disruptive. It’s difficult to navigate shifts in trust and responsibility, from inside the organization to outside.
Solution: Simplify the transition process by breaking it down into a series of pre-scheduled projects or steps. The transition to a managed data service is qualitatively different than buying software or choosing technology vendors. It should be viewed as a transformational project for the enterprise, with long-term benefits. The transition process must consider the maturity level of the firm, its regulatory challenges, and its ability to navigate transformations by completing each project or step successfully, on-budget and on-schedule.
Obstacle #4: Outsourcing a critical component of operations means a loss of control.
Solution: Carefully define the competitive advantages you hope to achieve. Consider objectives such as time to market, data quality, data inventory, improved customer service, or other areas.
Many firms are embracing the maturity of the mutualization concept, also known as the utility model. This concept aims to delivers efficiencies in areas that are not defined as competitive differentiators for each firm. It provides scale-ability and the uniformity regulators are demanding, and it can be customized to the needs of each firm. But, keep in mind that mutualization is a complex undertaking. Implementing the concept requires flexibility as well as managers’ control over data-intensive operations across the enterprise, with sensitivity for each unit’s special needs. Few firms currently have the expertise or infrastructure to meet these customization challenges through internal resources alone.
Obstacle #5: The first-movers face the highest adoption and transition risks.
Solution: Understand that the industry is moving toward this model at a rapid pace, and the greater risk is being left behind. Early-movers will have a better understanding of how to leverage competitive advantages, cost-savings, and regulatory compliance solutions. In many banks, these goals can be best achieved by working with experienced partners who offers the depth of resources and top-level commitment to deliver risk-mitigation strategies. Without such relationships, firms will continue to demand that managers constantly produce more results working with ever more scarce resources. That’s a career path that’s destined to lead to frustration, and perhaps ultimately failure.
All investment banks face the same risks in adapting to change. Yet, the high cost of maintaining aging infrastructure and using it to meet new business and regulatory demands will only continue. These challenges mandate timely and decisive action. As such, the adoption of a managed data service can help to achieve high-level strategic objectives, such as controlling the growth in operations headcount and increasing shareholder value.
Across the industry, firms that have launched piecemeal internal technology initiatives have consistently achieved limited success. A better way forward is to clear the path through mutualization of common costs and industry best-practices on a state-of-the-art platform.