- Kingland Platform
Data silos isolate information, and generally speaking, the larger the organization, the more data silos tend to develop. This is either a natural evolution of individual business units modifying data to fit their needs, which can evolve into specialized data silos. This can also be the result of corporate growth through acquisition, where an acquired company's client data is generally left untouched so it can continue to power the applications of the acquired company. Either way, the result is sub-optimal data quality, data duplication, difficulty in reusing data across applications or to power analytics, and increased data maintenance costs. What's needed is a common language, a holistic view, and a management focus requisite to the importance of the data.
Remember. We're collecting client data which includes who they are, what they do, where they are, and who they might do business with. Duplicates here. A missing field there. Without an enterprise view, we're flying blind.
A good client management system can move the business forward by reducing risk and cost, and it can present opportunities to generate revenue to help clients.
Prioritize Client Data
Many decisions about client data are made at the departmental level by a business manager responsible for their own profit and loss (P&L). It's difficult to centralize the business case among all the P&L owners, each of whom likely have different investment priorities. Also, even if client data is identified as an area worthy of investment, the investment needs to be prioritized against others, and there are never enough investment dollars to go around. Client data investment usually takes a back seat to other projects that could generate revenue. This is especially true if the client data is viewed as "good enough" so that patches and other short-term fixes can be applied, further exacerbating the silo issues and raising maintenance costs. Therefore, understanding the full value of good client data at a corporate level should be prioritized. A moderate increase to the customer experience by improving client data management processes generated an average revenue boost of $823 million over three years for a business with $1 billion in annual revenues.
Client Data is Foundational
Look around the enterprise. Client data is connected to everything. Onboarding. KYC. Regulatory reporting. Many areas of the middle and back offices are impacted by the quality of client data. Because of that, banks and other industry firms are wary to mess with it for fear it will have unforeseen downstream consequences. They are right to be fearful, but conversely, they should understand the opportunities that may arise by using client data to develop client-centric models, products and services that can generate revenue, and reduce risk and operating costs. It is an opportunity to liberate client data to be a driver of business, not a drag on it. But doing so is not easy. Client data is continually changing as new clients are added, existing clients are dropped, and reference data associated with existing clients changes. The technology required to support effective client data solutions is not generally a component of legacy systems. Building and maintaining client hierarchies and incorporating data from unstructured sources are two examples of where many legacy technologies fall short.
Transform the Enterprise
Getting to the point of truly transforming the business is an arduous task. Legacy systems. Legacy sources. Business applications. You won't find an easy fix. If it was easy, it would have been done by now. But you can find a path because the reward is substantial. The path leads to greater opportunities when the enterprise is using up-to-date information and can provide complete, accurate client data to all applications and business processes that require it, while allowing each business to use the data in a manner best suited for them. Whether related to client onboarding and maintenance, corporate actions processing, counterparty risk monitoring, regulatory reporting, there are few areas where this data can't improve operations. For example, think about how lengthy onboarding times can lead to a loss in revenue. Think about the opportunities if you were able to extract data from documentation and automatically route that data to where it needs to be. The 'single source of truth' eliminates guess work, means that true client risk profiles can be developed, and clients start trading faster. Risks are reduced, operating costs are lowered, and additional revenue is generated. It is a journey worth taking.