Investment firms are diving into AI, using it in many different ways. From automation to data aggregation to generative AI portfolio management, organizations are finding unique ways to apply this technology.
Generative AI is a specific subset. It uses generative models to then produce images, text, audio, video, code, or other data. Most of the time, the use cases have much to do with areas like marketing and media. However, there are key features of generative AI that can be valuable in portfolio management and trading.
In this article, learn about three use cases for generative AI and asset management.
Data Interrogation: Save Time in Reporting Building
Generative AI works well when conducting data analysis. Traditional methods for this exercise rely on things like system-generated standard reports. They are often not granular enough to be practical or beneficial.
Because of these deficiencies, portfolio managers and traders must spend a lot of time pulling data from multiple sources to answer questions. If they are concentrating on this, they have less time for their core activities relating to managing portfolios and making trades.
Additionally, they may have to depend on other end users in their organizations with technical skills to query data and create custom reports and outputs. It’s time-consuming and difficult when working in systems with complex data structures like trade order management systems (OMS) or portfolio management systems (PMS).
Implementing generative AI for data interrogation removes this bottleneck. All users can then query data via natural language and produce quick results. The AI features within INDATA are also easy to launch with a “no code” approach. The solution also allows for review and verification of results before acting on AI-generated information.
Monitoring Portfolio Information: Customized Dashboards and Screens
With ever-changing market conditions, portfolio managers and traders need accurate and up-to-date information on their client portfolios. Typically, portfolio monitoring involves setting up screens, dashboards, and reports to allow for high-level views of the most important information based on the strategy and approach of the investment manager.
The challenge is often that there’s no “perfect” dashboard or report to capture everything. In an event-driven environment like portfolio management, so many changes occur every day. Generative AI portfolio management monitoring tools provide a solution.
The portfolio data screens are configurable on the fly based on real-time events. Users can monitor individual securities, sectors, industries, asset classes, cash, or security reference data. The INDATA generative AI capabilities enable the use of the Master Data Model (MDM). This ability ensures data completeness and accuracy.
As with any AI, its effectiveness depends greatly on how good the model it’s using. The adage of “garbage in, garbage out” applies. With INDATA’s MDM, portfolio managers and traders can select what type of data they want for AI purposes, all while keeping their organization’s investment data private in the process.
Client Servicing: Personalized Responses
For portfolio managers who interact with clients, keeping them informed and answering questions is critical. Internal or external stakeholders are also inquiring about various things. Currently, most look to screens, dashboards, and reports to answer these requests. It’s limited and can be a lot of work to extract data that is not readily accessible. It’s more work that Generative AI can help support.
For this to be a real solution, the right data is necessary. APIs play a big role in pulling data from external systems that contain commonly used demographic information that is part and parcel of wealth management.
For those working with large numbers of portfolios that include multiple asset classes, Generative AI portfolio management tools are a game-changer in providing fast and personalized client servicing.
More About INDATA Generative AI for Trading and Asset Management
INDATA’s Generative AI features take the tech work out of AI with no integration or implementation necessary. Using an agnostic approach to AI, clients can use whatever Large Language Model (LLM) provider they want.
Additionally, INDATA clients have complete control over data security and data privacy, which is in line with fiduciary best practices. INDATA’s AI Agent, available within INDATA’s SaaS-based solutions for TOMS, compliance, portfolio management, and portfolio accounting, offers a scalable, complete solution for investment firms seeking to leverage AI without a huge time or monetary investment.
Adopting Generative AI for Portfolio Management
These three use cases showcase how firms can implement Generative AI into their business. It supports data analysis and interrogation so that portfolio managers can act on insights. Generative AI also assists with creating monitoring platforms that are meaningful and enable quicker and more customized customer interactions.
Learn more about INDATA generative AI tools today by requesting a demo.
FAQs
What is “Generative AI” in the context of investment management?
Generative AI is a subset of the technology that generates new data based on models. In investment management, it applies to analyzing or using data sources to create some type of output or report.
What benefits does Generative AI deliver for portfolio managers and traders?
It’s a huge time saver in terms of analyzing and integrating data to find insights. It also provides a way to build custom dashboards based on the needs of each user. Further, it can help with compiling answers to questions from clients quickly so they receive fast responses that are personalized.
Why is a strong data foundation (like a Master Data Model) essential for Gen AI in investment management?
Gen AI outputs are only as good as the accuracy and completeness of the data models it uses. If they are lacking in either, the responses generated won’t be useful.
Are there risks or challenges with implementing Generative AI in asset management?
There can be risks associated with any AI technology. What’s crucial is working with a partner that understands how to implement tools that are compliant and secure. Additionally, firms will want a solution that’s customizable to their needs.
How can a firm get started with Generative AI for portfolio management and trading use cases?
Firms should start with their goals for using Generative AI and then align with the tools available. Starting with a demo from INDATA can reveal all the key features of Generative AI capabilities, with the ability to ask questions and gain more knowledge.
