Scaling AI at Moody's

Welcome to AI Street. I’m Matt. This week we’re publishing a day early for the U.S. holiday. Happy Thanksgiving! 🦃 

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INTERVIEW
Inside Moody's Bottom-Up Approach to AI

Sergio Gago, head of AI & Quantum Computing at Moody's, discusses how the financial services firm has identified hundreds of AI use cases by involving employees in the innovation process, moving beyond an initial approach that relied on a specialized innovation team.

In this “Five Minutes With” interview, Gago explains Moody’s approach to AI implementation, including the development of tools like a Policy Assistant that answers compliance questions and a Credit Memo Generator that automates financial analysis. He addresses why innovation teams often struggle to scale AI solutions when operating in isolation and shares practical insights for implementing AI in financial institutions.

By encouraging employees to contribute ideas, Moody’s generated over 800 potential AI applications. This inclusive strategy has helped the firm uncover numerous opportunities, such as automating compliance queries and generating credit memos.

Gago also explores the potential of augmented reality in the financial sector and offers advice for entrepreneurs building AI tools for finance.

This interview has been edited for clarity and length.

Tell me about some use of those cases  

Policy Assistant: Answering Compliance Questions with High Accuracy

At Moody’s, we’re a large, regulated organization with rigorous compliance policies—covering everything from travel to client interactions. Employees often have detailed questions like, Can I accept this gift from a client? or Am I allowed to fly business class for this specific trip? Answering a high volume of questions required our compliance team to spend time and bandwidth which they could easily devote to addressing more complex issues their job demands. .

To address this, we built an internal Policy Assistant using AI. It processes and interprets policy documents, incorporating all recent updates. Employees can now ask the assistant directly and receive accurate, compliant answers almost instantly. We’ve designed it to mitigate risks significantly—especially for critical compliance issues. This tool not only improves efficiency but also allows our compliance team to focus on more complex, high-value tasks. 

EDFX Navigator Research Assistant: Providing Insights for External and Internal Users

The EDFX Navigator Research Assistant is perhaps one of our flagship AI-driven tools. It’s designed to sit on top of our extensive data platforms and acts as an intelligent assistant for both internal teams and our customers. It synthesizes vast amounts of data and presents actionable insights tailored to the user’s query.

Internally, our analysts use it to quickly extract key insights during client meetings or while preparing reports. 

Externally, it’s a powerful resource for our clients, helping them navigate market dynamics, identify risks and opportunities, and make informed decisions without having to comb through raw datasets themselves. What makes this tool special is its ability to provide contextualized insights—turning raw data into a narrative that’s immediately useful. It’s a game-changer for how we deliver value through our data.

Credit Memo Generator: Automating Financial Data Interpretation

The Credit Memo Generator is one of the standout tools we’ve developed. Traditionally, creating a credit memo—summarizing a company’s financial position and creditworthiness—was a manual, labor-intensive task. Analysts had to sift through financial statements, pull in data, and compile into a coherent report.

Using AI, we automated this process. The Credit Memo Generator extracts data from structured sources, analyzes it, and generates a detailed credit memo in minutes. It doesn’t just summarize numbers—it provides a narrative, highlighting key metrics, identifying potential risks, and even flagging anomalies or trends. This has drastically reduced the time it takes to produce these reports and ensures consistency and accuracy across the board. Analysts now have more time to focus on deeper insights and strategic decisions.

…

How is Moody’s exploring augmented reality (AR) in conjunction with AI?

We see immense potential in combining AI with AR to transform how employees interact with data and make decisions. Imagine an analyst visualizing complex datasets in 3D or a manager simulating economic scenarios within an immersive AR environment.

Read the full interview here 

IN CASE YOU MISSED IT
Recent Five Minutes with Interviews

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• PhD candidate Alex Kim on executive tone in earnings calls

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• Arta’s Chirag Yagnik on AI-powered wealth management

• Finster’s Sid Jayakumar on AI agents for Wall Street

ETHICAL AI
CFA Institute’s Pisaneschi on AI Guardrails

As generative AI gradually gains traction in finance—there's already an ETF relying on LLMs for its "investment committee"— there’s a growing need for the industry to set up guardrails to prevent unintended consequences, according to Brian Pisaneschi, Senior Investment Data Scientist at the CFA Institute, who recently spoke at the World Pension Summit on the ethical use of AI.

"Large language models reflect the biases in their training data," said Pisaneschi, who's based in London. "Investors should be able to understand why an AI made a recommendation and what factors influenced that decision."

The industry has yet to establish standardized benchmarks for measuring fairness and bias. While some financial models are tested against theoretical question sets, like those in the CFA program, these evaluations don’t always capture all the complexities of real-world decision-making.

One solution: standardized datasets specifically for testing AI fairness in financial decisions, similar to how credit decisions are monitored for bias. Whether leveraging RAG-based systems (which combine AI models with curated data sources) or proprietary financial models, firms must disclose the sources and potential biases driving their recommendations.

BANKING
Jamie Dimon Can't Wait for JPMorgan's AI to Go Mobile

Jamie Dimon is a "tremendous user" of JPMorgan's AI tools and is pushing for more access, according to the bank's AI chief, Teresa Heitsenrether.

Speaking at an industry conference last week, Heitsenrether revealed that Dimon is "desperate" to get the bank's AI tools on his phone, making mobile access a key priority before year-end.

The enthusiasm from the top comes as JPMorgan has rolled out its AI assistant, LLM Suite, to 200,000 employees. Heitsenrether herself uses the technology to sharpen presentations before meetings with Dimon. (Business Insider)

AI INVESTING TOOLS
Boosted.ai Raises $15 Million for AI Investment Platform

Boosted.ai has secured $15 million to expand its AI platform that helps investment managers automate financial analysis.

• The platform, called Alfa, claims to reduce 40 hours of analyst work to about 20 minutes by acting as an AI "coworker" that users can train to think like them.

• Notable investors include Fidelity Investments Canada and Royal Bank of Canada, bringing total funding to $61 million.

• The company has 300+ clients managing $3+ trillion in assets, including asset managers, wealth managers, family offices and hedge funds.

The Toronto/NYC-based company has evolved from its 2017 founding focus on machine learning algorithms for quant traders to now offering broader AI tools for financial analysis, research, and workflow automation. (Press Release)

AI Startup Quartr Teams up with Perplexity

Quartr has partnered with AI search engine Perplexity to integrate live and archived earnings call transcripts into Perplexity’s platform. The partnership aims to make real-time financial insights more accessible to individual investors by providing live transcriptions and AI-generated summaries of earnings calls. (Press Release)

REGULATION
Fed’s Bowman Says Regulators Shouldn’t Rush to Contain AI

Federal Reserve Governor Michelle Bowman acknowledged the risks created by artificial intelligence but warned that regulators should also be careful not to constrict the development of useful technologies.

“We need not rush to regulate,” Bowman said in the prepared text of a speech she’s set to deliver in Washington Friday. “An overly conservative regulatory approach can skew the competitive landscape by pushing activities outside of the regulated banking system or preventing the use of AI altogether.”

In the financial sector, she said, AI could be used to improve operational efficiency, combat fraud and expand access to credit. (Bloomberg, Bowman’s Speech)

RESEARCH
AI Could Boost Asset Manager Revenue 12% by 2028: PwC

Asset managers who quickly adopt "tech-as-a-service" could see a 12% revenue boost by 2028, according to a new PwC study of 500+ asset managers and institutional investors globally, according to a recent PwC survey.

• 73% see AI as most transformative tech in next 2-3 years

• Global AUM projected to hit $171T by 2028

• Tokenized investment funds to surge 51% annually to $317B

• 81% exploring M&A to enhance tech capabilities

While 80% of asset managers see it driving revenue growth, 59% of their clients - institutional investors - believe AI could reduce their need for asset management services altogether. 

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Range, the all-in-one AI WealthTech platform, raised $28 million in Series B funding, led by Cathay Innovation and joined by Gradient Ventures and other investors. This round brings the company’s total funding to $40 million. (Finextra)

Italy's Banca Investis Launches 'Digital Junior Banker' with GenAI

Italy's Banca Investis has launched an app that provides banking customers with real-time investment advisory backed by generative AI. (Finextra)