By David Rochford, Managing Director, Global Head of Public Markets, MUFG Investor Services
As part of the digital transformation of the financial services industry, artificial intelligence (AI) is helping to speed and streamline the perennial challenge of onboarding new clients. The paper-intense onboarding process is a frequent target of frustrated investors who question why they are submitting PDF documents in the digital age. Financial institutions, which manually review the documents and share them with multiple stakeholders, know the process to be time-consuming and error prone, often creating a poor investor experience.
Investors are receiving some relief as firms increasingly re-engineer their processes to eliminate documents and use AI—specifically, natural language processing (NLP) and machine learning—to streamline data-gathering capabilities, provide more efficient data processing and workflow. The combination of online forms for data entry and know your customer/anti-money laundering documentation creates a golden source of data that is fed into machine learning flows and is used across the entire investment ecosystem. Investor data submitted on these platforms is digitally extracted and processed, eliminating the need for manual input and reducing human mistakes. Then the data is distributed throughout the client onboarding process, as systems insert personal information, tax status, anti-money laundering disclosures, subscription disclaimers and trade data to the relevant fields.
Digitizing data when client onboarding begins significantly improves accuracy and speeds straight-through-processing. Currently, documents submitted through archaic paper-based systems require manual approval and corrections across levels of review. By automating the process with extraction tools, managers can evaluate information for exceptions and make minor corrections in the system, reducing manual review tremendously.
The digitized data also increases transparency, as outputs are rapidly processed into data warehouses, triggering notifications to asset managers and providing a near real-time view of positions in dashboards or other investment tools. Faster access to this data enables fund managers to adjust their strategies and make decisions more quickly. In addition, building digital workflows from the outset creates a cohesive structure for building more effective data models. The improved data flow to these models reduces the risk of processing or execution errors leading to time-sensitive and costly manual overrides. The implementation of AI technology to digitize onboarding and data models poses some concerns. Integrating new technology into existing systems can take time and may require new investments and ensuring data security and privacy is always a prime concern.
The potential benefits far outweigh any downsides. It’s increasingly clear that financial institutions willing to invest in digitizing investor data now—on their own or working with trusted partners — are better positioned to compete in the future. By providing automated operational support, these partners enable firms to redirect resources and avoid the cost of a technology stack upgrade. These partner firms make the significant technology investments and continuous process improvements at manageable costs, while working with clients to update data, provide market insights and manage operational challenges to leverage digitization. Looking ahead, AI-powered chatbots and virtual assistants will help improve the client experience and client retention by identifying behavior patterns early and enabling firms to tailor products and services to specific needs. And AI also can be used to help internal operations protect client data, predict operational incidents and help to resolve those issues quickly. Moving away from manual, paper processing means that managers can finally move away from trying to obtain delayed information from operations teams. Investors will enjoy a more streamlined process, faster processing times and greater optionality, and service providers will feel more secure about the accuracy of the data they’re receiving. By automating the process and digitizing data, investors and financial institutions alike can focus on making the important decisions to grow their portfolios and better serve clients.
