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Automating Asset and Wealth Management Term Sheets with Enterprise AI

Jason Dzamba by Jason Dzamba - February 13, 2024

Asset and wealth managers across various verticals are at a crossroads, contemplating adopting cutting-edge solutions like enterprise artificial intelligence (AI) to streamline operations and enhance efficiency. 

In this article, we’ll cover the practical outcomes of embracing AI, particularly in automating term sheets within platforms such as Salesforce.

The Challenge of Manual Data Extraction

Asset managers grapple with the cumbersome task of handling term sheets and complex, data-dense documents that demand significant time and effort for regular data extraction. 

Whether dealing with potential investments, client portfolios, or monthly calendars, the sheer volume of data poses a substantial challenge. The traditional manual approach to inputting this data into systems is time-consuming and error-prone.

Making Term Sheets Manageable

The primary question arises: Why not automate this process? When adopting solutions like AI-driven automation, the benefits are substantial. Take, for example, the monthly calendar of a company releasing multiple products. 

Extracting data from 150 different term sheets can be a daunting manual task, prone to inconsistencies and errors. Automation, however, transforms this process, making it swift, accurate, and scalable.

The Problem of Variations in Term Sheets

Term sheets, though standard in purpose, exhibit considerable variations. Pricing structures, terminology, and information presentation can differ significantly across sheets. 

Manually handling these variations consumes time and introduces the risk of inconsistencies. AI normalizes and standardizes data, ensuring a consistent and organized view across all client interactions.

The Shift from Traditional OCR to Contextual AI

Historically, machine learning and OCR (Optical Character Recognition) were employed for data extraction. However, the limitations of this approach became evident, especially when dealing with changing document structures. 

Unlike traditional methods, Documents with GPT understand a document’s context and extract relevant data using human-like prompts. This contextual approach eliminates the need for laborious training and retraining associated with OCR.

Bots, Automation, and GPT-powered Tools

The adoption of automation and bots has witnessed a mindset shift. Traditional reservations about job displacement have given way to a realization that these tools are not replacements but enablers. 

Incorporating tools powered by large language models like GPT (Generative Pre-trained Transformer) has revolutionized data extraction. By understanding language context, GPT facilitates accurate and efficient data extraction without extensive training.

Understanding the Automation Process

The automation process involves several steps, from receiving emails with monthly offerings to extracting data and populating Salesforce. Intelligent document processing tools, like GPT, play a crucial role in pre-processing, classification, and data extraction. 

Validation steps ensure the accuracy of extracted data, with human intervention reserved for verification when needed. The process results in JSON-formatted data ready for integration into platforms like Salesforce.

Human Element and Employee Experience

Implementing AI-driven automation transforms the employee experience. While there might be initial concerns about job security, employees quickly recognize the value of these tools. 

The tedious, repetitive tasks that once consumed their time are now handled efficiently by bots, allowing them to focus on more strategic and meaningful aspects of their roles. The result is a positive and empowered workforce that contributes to the organization’s success.

Technical Considerations and Project Estimations

Embarking on an AI and automation journey requires meticulous planning. Having sample documents, precise mapping of data points to platform fields, and a well-defined understanding of the target system are essential. 

The involvement of a professional developer expedites the process. Project timelines can vary, with offshore developers offering cost-effective solutions. A ballpark estimate suggests a two-month project timeline contingent on preparedness and complexity.

Embrace the Future of Wealth Management

In conclusion, adopting AI and automation in wealth management is a technological leap and a strategic imperative. By automating data-intensive tasks, asset managers can unlock unprecedented efficiency, reduce errors, and empower their workforce to focus on value-driven activities. 

The intersection of technology and wealth management is here—those who embrace it will lead the way into a future of unparalleled innovation and success.

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Jason Dzamba

About Jason Dzamba

Director of Media Relations, Productivity Strategist, and Host of Inside the Bot Podcast, Jason uses a process-driven approach to help leaders optimize their actions and achieve their most important business objectives. His creative outlet is painting abstract art and producing music. He lives in Orlando, Florida, with his three kids.

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