Justin and his team are responsible for defining Clearwater’s strategic development roadmap and analyzing markets and market participants to allow Clearwater to react quickly to changing client needs, new regulatory guidance, and shifting strategic priorities. Justin helps ensure our product meets clients’ needs and maintains a high level of client success and satisfaction. Justin joined Clearwater Analytics in July 2004 and served as one of the original system architects for a number of core Clearwater systems and processes.
Justin holds a bachelor’s degree in computer science from Boise State University.
How many places do you need to look to access data related to your organization’s investments? Can you count all the systems, spreadsheets, and statements on one hand? On two?
Many organizations manage their investment data using multiple systems and processes, each chosen for one specific purpose. Investment operations teams might extract portfolio data from an accounting system into a data warehouse, then use additional business intelligence tools to draw from the data warehouse to create usable reports. Meanwhile, complex asset classes are handled separately, requiring accounting teams to manually gather that data and create regulatory reports, general ledger entries, and other products. Add a risk system, and some sort of performance calculation method, and the list only grows.
This multi-system approach worked for a time, but it has grown inefficient, expensive, and unsustainable.
Not only is your data management likely disorganized, but investing in so many systems is costly to an organization in terms of money and effectiveness.
How did we get here? As many buy-side organizations grew their investment accounting and reporting operations over the past few decades, they would seek out the best solutions for individual challenges, and they had room on their balance sheets to afford these solutions. Over time, their data management became like a cargo ship over-stacked with shipping containers. Not only are they disorganized, but investing in so many systems is costly to an organization in terms of money and effectiveness.
Technology has fundamentally changed over the past several decades. Sophisticated tools for data automation make it possible to maintain a centralized set of continuously validated investment data. With that in place, integrated tools for a variety of purposes can be placed on top, ensuring the data is consistent and accurate across reporting and analytics tasks.
Many have found this consolidated structure is the most efficient way to manage their data. Additionally, cloud-based platforms can make it more efficient to access this information. Software-as-a-service (SaaS), a technology model based in the cloud, is widely seen as a leader in the financial technology industry because of its accessibility and seamless platform-wide updates.
I can think of at least three reasons why integration is key for efficient data management.
SaaS systems are multi-tenant, meaning all users access a single core system. This means certain data can be shared. For instance, a security master file can be maintained to the highest degree of accuracy for all users. When a custodial error is caught, it’s updated for everyone.
Integration of reporting and analytics tools also increases accuracy because the data points will harmonize. Your analytics will agree with each other because they are calculated using the same source. In a fast-paced environment, organizations need data that is trustworthy and up-to-date. Seamlessly delivered, clean data will help you make the most informed decisions about your investments.
An integrated data management platform is accessible to users across the company, opening up lines of communication and transparency within your organization. Siloing one individual, or a small team, with all the data and information increases your key-person risk — if someone suddenly leaves the company, your team is left with a hole in its operational knowledge that can take months or even years to fill.
An integrated platform also improves your ability to share information about key projects across teams, allowing for smoother workflows and increased efficiency. The added benefit of using a SaaS system is that information can be easily accessed by whomever has user permissions.
As I’ve already mentioned, integration of reporting and analytics tools is only possible with data automation as the foundation. And if you invest in an automated system as the core of your data management infrastructure, the result is simplification across the board, which lowers overall costs to purchase, update, and maintain single-use systems.
Integrating your data management is the most efficient way to improve the accuracy, accessibility, consistency, and reliability of your financial information. More than ever, organizations are relying on their financial data to make strategic and informed investment decisions to be profitable in a competitive environment. Investing in the right technology, like SaaS automation, can provide tangible benefits to your organization as it seeks stay relevant in the years to come.