SIFMA: DTCC’s adoption of fintech

DTCC is working on several initiatives to assess and use fintech capabilities, including:

Today: Robotic Process Automation (RPA)

Billing – DTCC’s Finance Revenue Cycle team used to use two different legacy systems for billing, requiring end-of-month reconciliation. Given a lack of human capacity to reconcile each invoice, staff sampled 10% of the total to check overall reconciliation rates. By utilizing RPA, capacity constraints disappeared, and every single invoice is now reconciled. Staff were freed up to focus on analysis/solving cases that fail to reconcile, and clients benefit from more accurate invoicing.

Onboarding – In an ongoing project, DTCC is working to automate some of GTR’s complex onboarding workflow (operates in multiple regulatory jurisdictions; 6,000+ client base). When a new client submits onboarding forms, staff review the forms and move them into a Salesforce queue if the information is deemed valid. Then a bot processes the application and either funnels it into an exception handling queue (for non-standard or questionable data) or marks it successfully completed. The goal is to reduce the complexity and time of the onboarding process. However, even small changes in the other systems (ex: Salesforce) can cause the robotic process to fail. DTCC has, therefore, discovered that developing standards and utilizing an open-source model provides for structure as the bots are developed.

Tomorrow: artificial intelligence (AI) and machine learning (ML)

Mutual Funds – In June 2017, DTCC implemented an automation initiative incorporating AI and ML to strategically enhance Mutual Fund Profile II, a central repository maintaining prospectus and operational processing rules for 27,000 mutual fund securities. By applying AI-driven enhancements, DTCC automated data sourcing and boosted the number of data points (minimum/maximum sales charges, underwriting fees, social codes, etc.) covered by the database to 5 million from 4 million, streamlining clients’ collection and sharing of this data. The repository now captures higher-quality information with increased frequency and faster speed to market. If discrepancies arise as a fund updates its data points, the application automatically generates a notification prompting a data review and prevents the system from being updated with incomplete information.

Long-term: Distributed Ledger Technology (DLT)

Post-Trade Infrastructure – DTCC continues to test DLT applications, yet the technology needs to be proven to be considered enterprise-ready or widely adopted by the industry. In other words, the technology is still evolving. As DTCC experiments, it continues to develop its internal capabilities with the technology to drive advancements in post-trade processing for the industry. Moving DLT’s capabilities forward for real-world financial transactions will take scalability, interoperability and governance.

Trade Information Warehouse – DTCC is preparing to move its Trade Information Warehouse (TIW) from a traditional database to distributed ledger and leveraging cloud computing to enhance scalability, improve flexibility, optimize performance and reduce costs. Additionally, they are using this project as a means to test the technology’s potential and its limitations.

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