Streamlining Finance: How ChatGPT-Powered AI is Revolutionizing Investment Analysis.
The finance industry, a domain defined by precision and intricate data analysis, is undergoing a seismic shift driven by advancements in artificial intelligence. Companies like Endex, in close collaboration with OpenAI, are at the forefront of this transformation, demonstrating how ChatGPT and its underlying models can streamline operations and enhance decision-making for financial professionals. Here is one example how can ChatGPT streamline operations in the finance industry.
Endex's development of an AI Analyst, leveraging OpenAI's powerful language models, exemplifies the potential of AI to revolutionize workflows. By focusing on retrieving, synthesizing, and reasoning through complex financial data, Endex addresses a critical need in the industry: the ability to move beyond simple data retrieval to structured thinking and deep analysis. Tarun Amasa, CEO of Endex, articulates this vision, stating, "Finance professionals don’t just need search results; they need structured thinking and deep analysis."2 This sentiment underscores the limitations of traditional AI tools and the need for more sophisticated solutions.
A key differentiator of Endex's approach is its reliance on OpenAI's reasoning models, including GPT-4o, o1-mini, o1-preview, and o3-mini.3 Unlike retrieval-augmented generation (RAG) methods, which can sometimes miss critical details, Endex's agents function like seasoned analysts, retrieving, reflecting, and contextualizing data. This approach is crucial in finance, where even minor discrepancies in data, such as missed adjustments in EBITDA reconciliation or overlooked clauses in legal documents, can significantly impact investment outcomes.
Endex's agents autonomously process a wide range of financial data, including financial reports, market data, and firm-specific knowledge, to perform tasks such as precedent transaction overviews, earnings performance summaries, investment committee (IC) memo preparation, and data room due diligence. The ability to deliver outputs in various formats, including emails, documents, Excel models, and slide decks, further enhances the efficiency of these workflows.
The performance of Endex's platform is significantly enhanced by OpenAI's "o-series" models, which offer long-context windows, prompt adherence, and robust reasoning capabilities. As Amasa notes, "Instead of just finding a needle in a haystack, the models can analyze and detect discrepancies in financial data the way a seasoned analyst would."5 This capability is crucial for identifying restatements in footnotes, surfacing inconsistencies, and cross-checking financial data, allowing analysts to focus on higher-level decision-making.
Endex has achieved breakthrough performance by leveraging OpenAI’s reasoning models to enable precise financial workflows:6
Multistep financial reasoning: By using OpenAI’s o1 models, Endex has simplified complex prompting and verification processes without compromising accuracy.
Faster, more efficient AI: The o3-mini model has enabled Endex to improve intelligence at one-third the latency, facilitating detailed multi-step workflows like analyzing confidential information packages (CIPs) and automating financial model reconciliation.7
AI-powered cross-checking: Endex agents can identify discrepancies in financial data, flagging restatements and inconsistencies with targeted citations.8
Multimodal analysis: OpenAI’s o1 vision capabilities allow Endex to process tabular and chart data from investor presentations, internal decks, Excel models, and 8-Ks, achieving leading Finance Agent Retrieval (FAR) scores.9
Deliverable automation: Endex automates the generation of detailed reports, reducing manual work and freeing up professionals for strategic tasks.10
The success of Endex's platform is underpinned by a rigorous evaluation and testing framework developed in collaboration with OpenAI.11 This framework allows the Endex team to track key metrics like response latency and reasoning depth, and to assess model outputs in real-world scenarios.12 Blind user testing has shown that financial experts prefer responses generated by OpenAI’s o1 model 70% of the time over non-reasoning models. Furthermore, fine-tuning models like GPT-4o mini and OpenAI’s o1 series through reinforcement learning has improved entity extraction and query intent mapping.
The collaboration between Endex and OpenAI extends beyond model provision; it encompasses a shared vision for vertical-specific AI and the development of agent-user interfaces that will redefine financial analysis.13 As Endex scales its autonomous analyst capabilities, it is poised to transform the way financial professionals work. By leveraging OpenAI's models, Endex is building systems that can plan, reason, and execute complex financial tasks, ushering in a new era of AI-powered finance.
Endex , an AI platform for financial firms, is developing an AI Analyst that retrieves, synthesizes, and reasons through complex financial data. They work closely with OpenAI to reinvent the workflow of investment professionals.
"Finance professionals don’t just need search results; they need structured thinking and deep analysis," says Tarun Amasa, CEO at Endex. "We envision a future where every firm has access to teams of digital analysts, seamlessly augmenting time-intensive workflows.”
By evaluating and integrating a range of OpenAI’s models, including GPT‑4o, o1‑mini, o1‑preview, and o3‑mini, Endex connects firms' internal data, public disclosures, and trusted financial sources to enhance research and augment key workflows.
Bringing analyst-level precision to AI-powered finance
Precision is paramount in finance, but many AI-powered tools can miss critical details that impact decision-making. For instance, a missed adjustment in EBITDA reconciliation or an overlooked “change in control provision” clause can alter the financial outlook of an investment.
Endex takes a different approach. Instead of relying on retrieval-augmented generation (RAG), its agents use OpenAI’s reasoning models to retrieve and reflect data like a financial analyst, pulling facts, identifying inconsistencies, and contextualizing metrics.
Endex’s agents autonomously process financial reports, market data, and firm-specific knowledge to complete tasks including:
Precedent transaction overviews
Earnings performance summaries
Investment committee (IC) memo preparation
Data room due diligence
"OpenAI’s o-series long-context windows, prompt adherence, and reasoning capabilities make a significant difference," says Amasa. "Instead of just finding a needle in a haystack, the models can analyze and detect discrepancies in financial data the way a seasoned analyst would."
"Instead of just finding a needle in a haystack, the models can analyze and detect discrepancies in financial data the way a seasoned analyst would."
Tarun Amasa, CEO at Endex
Agents can deliver outputs as emails, documents, Excel models, or slide decks, and enable analysts to confidently trace agent conclusions back to their sources, acting as a true extension of an investment team.
Achieving higher accuracy and automation for financial firms
Endex has seen breakthrough performance using OpenAI’s reasoning models, enabling precise financial workflows:
Multistep financial reasoning: Previously, Endex relied on complex prompting, chained completions, and multiple verification steps. With OpenAI o1, they’ve simplified this process without sacrificing accuracy.
Faster, more efficient AI: Using OpenAI o3‑mini, Endex has improved intelligence at one-third the latency per turn, enabling detailed multi-step workflows such as analyzing confidential information packages (CIPs) and automating financial model reconciliation.
AI-powered cross-checking: Endex agents can now identify discrepancies in financial data, flagging restatements in footnotes and surfacing inconsistencies with targeted citations. This allows analysts to focus on decision-making rather than manual verification.
Multimodal analysis: Endex’s Finance Agent Retrieval (FAR) benchmark measures context usage on tabular and chart data - key sources for financial professionals. OpenAI’s o1 vision capabilities allow Endex to process investor presentations, internal decks, Excel models, and 8-Ks with leading FAR scores.
Deliverable automation: Endex generates detailed reports, reducing the manual work traditionally required for financial analysis. This automation allows professionals to focus on high-value strategy rather than data formatting.
"Finance professionals require structured, referenceable reasoning with attention to detail, and traditional LLMs struggled with this level of coherence," notes Amasa. "OpenAI’s reasoning series models were the first to consistently meet this quality bar."
Developing financial agents with expert evaluations
At the core of Endex’s platform is a rigorous evaluation and testing framework, developed in close collaboration with OpenAI.
This system allows the Endex engineering team to trace model outputs directly within the OpenAI platform, tracking key metrics like response latency, first-token generation time, and reasoning depth. Professionals can then assess outputs in real-world scenarios.
Through blind user testing, financial experts preferred responses generated by OpenAI’s o1 model 70% of the time over non-reasoning models. Endex also tracks performance metrics like response latency and first-token generation time to continuously refine the system.
Fine-tuning models like GPT‑4o mini and OpenAI’s o1 series through Reinforcement Learning – critical for precedent transaction analysis and other research-intensive tasks – improved entity extraction and query intent mapping as well.
“Our collaboration with OpenAI has unlocked tools to tailor model behavior to the reasoning and output style professionals expect,” says Pratham Soni, co-founder at Endex. “We’ve deployed reinforcement fine-tuned models to convert our custom datasets into targeted reasoning improvements.”
Scaling AI-powered financial analysis
OpenAI is integral to Endex’s growth - not just as a model provider, but as a strategic collaborator in refining evaluation techniques and pushing the boundaries of AI-powered financial analysis.
“What excites me most about this collaboration is our shared vision for vertical-specific AI. Our work goes beyond APIs – it’s about building the agent-user interfaces that will change how financial analysts do work,” says Amasa.
The Endex team sees a significant opportunity to scale. They plan to refine their autonomous analyst capabilities, ensuring that the technology can handle increasingly complex financial tasks for their customers.
"Our clients will be pioneers in a world where AI systems are not just a tool, but a true co-worker," says Amasa. "With OpenAI’s models, we’re building systems that can plan, reason, and execute financial analysis. It simply seemed like science fiction before."
"Our clients will be pioneers in a world where AI systems are not just a tool, but a true co-worker."
Tarun Amasa, CEO at Endex
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