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The Challenges and Benefits of Generative AI in Financial Services

By Amy McCloskey Tobin | November 15, 2023
image representing generative ai in financial services

Forward-thinking leaders in the financial services sector are paying attention to generative AI in the form of ChatGPT and other Large Language Models (LLMs) and how they will impact asset management. Generative AI can produce a wide array of content, including marketing content and client communications, and it can also automate investment commentary when integrated with technology that can act as a guardrail and ensure accuracy.

Concerns for Financial Services with Generative AI

Financial service sector leaders are naturally cautious; accurately understanding data is the foundation of wise investment decisions. However, issues with LLMs give pause to leaders in the financial sector concerning implementing the technology. Those issues include:

Accuracy: LLMs such as GPT are trained on vast amounts of information from the internet and elsewhere, and that information is not necessarily accurate.

Explainability: The methods used by LLMs to make decisions are not always transparent, and financial analysts need to be able to explain how decisions are made.

Data privacy: Financial services rely on highly sensitive data; feeding that data straight into an LLM introduces security issues.

Compliance: Governance is critical in financial services, and legal questions need to be answered regarding the ownership and use of datasets LLMs use.

Fair use concerns: OpenAI and Google face class action lawsuits regarding their LLMs ingesting copyrighted works without permission.

The Positive Impact of Generative AI on Financial Services

Despite some concerns, Generative AI is transforming how financial services work in cases where it can be introduced securely. AI is changing the insurance, banking, and financial services sectors. Here are some uses of generative AI for financial services:

Risk modeling: Large datasets and economic indicators can be quickly analyzed to assess the market, credit, and operational risks.

Investment commentary: Generative AI can analyze fund data and automate fund commentary within the guardrails of rules-based, deterministic AI, saving analysts countless hours of work.

Compliance: Generative AI can automate Suspicious Activity Reporting (SAR) and Anti-Money Laundering (AML) reporting, save human hours, and produce more reports than humans can generate.

Fraud detection: Generative AI can recognize anomalies and patterns and instantly detect fraudulent claims and transactions.

Process automation: AI can automate claims processing, compliance checks, and loan origination – reducing errors and increasing productivity.

Customer service: Financial services companies are using improved conversational chatbots to handle routine customer questions, allowing financial services companies to reduce call center costs.

At Arria, we’ve been helping financial services companies streamline their investment analysis and automate investment commentary with 100% accuracy and security. Integrating our natural language technologies, we remove the chance of human error in fund data analysis and produce investment commentary from fund data in seconds. To ensure the commentary is in your firm’s voice and sounds like your expert analysts wrote it, the commentary is editable, but the facts are not.

Our technology can also automate fraud detection, including Suspicious Activity Reporting and Anti Money Laundering reporting, generating reports on a scale impossible for humans alone. If you would like to understand better how Arria’s natural language technologies can help you implement generative AI and reap the benefits of its ability to produce narratives in reporting while safeguarding your critical data, speak to one of our experts.