Brokerage and custodial firms like Fidelity, Charles Schwab, Goldman Sachs, and J.P. Morgan—among others—must deliver regular statements to their clients and investors. Whether these statements are delivered on-demand (ad hoc), monthly, quarterly, or annually depends both on regulatory mandates and the cultures and business models of the individual financial services firms or custodians. These documents contain valuable data on everything from investment holdings to pricing and allocation of investments (stocks, bonds, cash) and transaction and tax data.
The data in brokerage statements is essential to key processes at brokerages, banks, and other financial institutions to enable:
- Client investment proposals: Feed financial data into investment proposal systems that generate analytics on prospective clients’ current holdings and recommended investments.
- Trust accounting: Capture and record trust client holdings in accounting systems to capture transaction and tax information known as shadow posting.
- Client onboarding: When transferring client assets between firms, everything the client owns must be moved from the previous manager, providing a full accounting of all assets.
However, getting the data from the scanned PDF brokerage statements into these various systems is time-consuming and costly. For example, the current value of a particular mutual fund must be manually located on the document, rekeyed, and validated by operations employees before it’s uploaded into the target system. This manual data extraction and processing status quo generates process bottlenecks and a poor client experience.
Cutting out the manual labor
Financial data aggregators offer digital services that simplify how investment data is consolidated and delivered into financial services firms’ reporting, analytics, portfolio management, and accounting systems. But such firms are limited in that they only aggregate data where electronic feeds are available—mostly from the largest brokerage and custodial accounts. Anything else must still be manually processed.
What’s needed: an intelligent data processing solution that can streamline the error-prone manual extraction of all brokerage data.
Advantages of automation
Previously, workflow automation solutions lacked the ability to deal with unstructured data. Today, leading solutions use AI and machine learning to liberate the data to power business workflows with clean, actionable information that gives banks and brokerage firms a competitive edge. By implementing leading intelligent data extraction solutions, these institutions break free from the limitations imposed by manual extractions and experience fascinating results, including:
Enhanced data confidence
Banks and brokerages need to have the utmost confidence that the data they are putting into their backend systems is accurate. A mistaken digit or misplaced comma resulting in potentially lost money could cost you a client. With an intelligent, AI-driven data extraction platform, the information from brokerage statements and other reports is automatically aggregated virtually error-free. An auditable trail to the source of your data and exception flagging—paired with a human-in-loop review—guarantee the accuracy and authenticity of your data.
Sophisticated data extraction solutions enable businesses to expand the sources and the amount of data they are able to process while simultaneously giving employees the necessary time for analysis and customer service. More data and more time to process the information result in better recommendations and enhanced trust.
Accelerated client reporting
Clients expect to get reports on how their investments are performing at the speed of the market, especially in volatile times. Many don’t want to wait for the traditional quarterly report. You can upgrade your client reporting schedule while leveraging dramatically more data by eliminating time-intensive manual data collection. Accelerate the production of portfolio summaries, performance reports, fact sheets, allocation, exposure, and sector reports.
Enhance customer experience & grow revenues
When your teams are not stuck manually extracting critical data from unstructured documents like brokerage statements, they can redirect their time toward enhancing the customer experience. This enables investment professionals to spend time on growing revenues and back-office workers to focus on higher-value tasks than simply rekeying data. Not incidentally, the employee experience in both cases is improved by automating the previously tedious job of extracting data from documents.
Alkymi has been supporting leading organizations with their data automation initiatives and can help you improve your processes around complex, unstructured use cases such as brokerage statements. Contact our experts today to see how easy it is to make the switch from legacy processes to automated workflows without impacting any of your existing systems.