Megan Kurka, Vice President, Customer Data Scientist, H2O.ai H2O Open Source GenAI World SF 2023 Discover the transformative power of Applied Gen AI. Learn how the H2O team builds customized applications and workflows that integrate capabilities of Gen AI and AutoML specifically designed to address and enhance financial use cases. Explore real world examples, learn best practices, and witness firsthand how our innovative solutions are reshaping the landscape of finance technology.

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MEGAN KURKA
VP Customer Data Science,
H2O.AI

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Applied Gen AI for the Finance
Vertical

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Ex: Answer an analyst’s
questions based on internal
and external documents.
Virtual Agent
Ex: Write me a report that
summarizes what happened
to these stocks based on
tweets from that day..
Content Generation
Ex: Analyze an earnings call
for sentiment and
defensiveness.
Analyze Content
Ex: Of all the content
available, find which ones are
outliers.
Needle in the haystack.
Trends & Anomalies
Powered by H2O.AI
Applied Gen AI for Finance

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Strategy
Use RAG (Retrieval Augmented Generation) to help answer
questions that are grounded in some private or public
content.
Virtual Agents
Applied Gen AI for Finance

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Use Case Why H2O?
Use Machine Learning to
recommend, forecast,
classify, etc.
Virtual Agents with Machine Learning
MACHINE LEARNING
LLMs to Answer Questions on the Model
Which bond had the greatest prediction and why?
The model predicts Bond: XYZ because the following attributes increase the
prediction:
● the maturity date is within 2 years (maturity date of 2025-06-01)
● the sector of the bond is Consumer Healthcare

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Strategy
Use LLMs to create novel content grounded in specific
details via RAG.
Content Generation
Applied Gen AI for Finance

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Strategy
Use LLMs to iteratively analyze the latest data. We can specify the specific
output we want via prompts and create interactive dashboards on top of
the results.
Analyze Content
Applied Gen AI for Finance

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Strategy
Use LLMs to iteratively analyze large amounts of data. Analyze
correlations between LLM output and stock movement.
Trends & Anomalies
Applied Gen AI for Finance

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Analyzing Earnings Call
LLM Ratings
Split the transcript by speaker and analyze
the overall sentiment and defensiveness
from 1 to 5.
Detailed View
01
LLM Reasoning
Ask the LLM to explain the reason for its
rating for each speaker.
02
Dashboard
Create an interactive dashboard using
Wave that allows us to see parts of the
conversation that we should review.
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Detailed View

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Ask the LLM to
summarize the content of
the call with a focus on
the company’s
expectations.
Summarize Transcript
Based on the summary,
rate the transcript based
on how well they were
able to meet
expectations.
Rate Summary
Ask the LLM for
justification on their
ratings.
LLM Justification
Analyze how these
ratings correlate to the
stock performance.
Correlations
Automatic Process
Analyzing Earnings Calls

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Finding the Best Process
Analyzing Earnings Calls

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Analyzing Earnings Call
LLM Ratings
Ask the LLM to rate the transcript from
each quarter from 1 to 5.
Trends View
01
LLM Reasoning
Ask the LLM to explain the reason for its
rating for each quarter.
02
Dashboard
Create an interactive dashboard that shows
us the overall sentiment over time and how
it correlates with the stock price.
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Anomalies
Applied Gen AI for Finance

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Trends View

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