Auquan is a data science and machine learning company that provides quantitative finance solutions and tools for investment professionals.

QuantQuest

H.E.L.P (Health + Economic Long-term Prosperity)

Auquan’s Intelligence Engine uncovers financially material hidden insights early using RAG AI (retrieval augmented generation). Transform company due diligence, KYC, ESG research, and risk monitoring and focus on what you do best: high-level analysis and making strategic decisions. 

Portfolio managers, research analysts, and corporate teams use Auquan to expand the scale and scope of their research and focus only on high-value analysis so they’re always prepared to act ahead of market.

☑ Eliminate time-consuming manual research work
☑ Surface under-the-radar unknown unknowns
☑ Understand hidden risks and investment opportunities
☑ Never let the market catch you unaware and unprepared 

USE CASES: 
Portfolio Intelligence
Identify, understand, and track hidden and emerging risks and opportunities relevant to your companies, their supply chains, and industry sectors

ESG Intelligence
Go beyond third party ratings and self-reporting to uncover ESG issues concerning your portfolio companies and supply chains. 

Custom Research 
Generate in-depth research and analysis on companies, sectors, topics, and regions in a fraction of the time and at a fraction of the cost


FinTech Sandbox

Episode 1

Techstars Ventures

Charlie Songhurst

Chris Adelsbach

John Stamler

Techstars

Techstars London Accelerator

Sentiero Ventures

Auquan

Today the Auquan team introduced *Prompt Intelligence* —  the first and only capability of its kind that can generate equity, credit, risk, or impact intelligence on any company worldwide, regardless of whether prior coverage on that business exists.

Anyone working in finance knows the pain of searching for insights on a company, only to realize that your vendor doesn't cover that entity and it will take days or weeks for them to build out coverage. 

Auquan’s Prompt Intelligence eliminates these wait times, bringing the immediacy, comprehensiveness and adaptability to financial research that firms need.

While LLMs and GenAI took the world by a storm this year, we knew these tools weren’t yet suitable for the kinds of knowledge intensive use cases we see banks, asset managers and private markets customers, who set a very high bar on accuracy and timeliness of information. They were prone to hallucinations and unable to access information beyond their training cut off date, creating a huge barrier to adoption within financial services.

We found the answer in RAG (retrieval augmented generation). RAG allowed us to combine our domain-specific retrieval models, which can surface key data points from a mountain of noisy unstructured text, with the generative capabilities of LLMs to bring even more efficiency to our customers research workflows without compromising on accuracy.

Our engineering team has been hard at work integrating RAG in all of our customers' workflows, and Prompt Intelligence is the first of many new exciting features in our pipeline.

PS: Auquan customers can already access Prompt Intelligence within the Auquan Intelligence Engine. If you would like to learn more about integrating this capability in your workflow for investment pre-screening, due diligence, KYB, sustainability/ESG research or uncovering hidden controversies within seconds, let’s talk!

Link to our full announcement is in the comments! 
#RAG #finance #nlp #ai #genai #esg #pe 

Auquan CEO Chandini Jain spoke with TechRepublic about what fintech trends can we expect to see in 2024.

Last year, LLMs and generative AI dominated the attention of consumers and the enterprise alike. But while consumer adoption of tools like ChatGPT skyrocketed, adoption of generative AI for enterprise use cases has lagged. And for good reason. Issues like hallucinations, lack of source credibility, and poor stability of responses have prevented adoption for  serious knowledge-intensive enterprise use cases. 

This is particularly true for financial services, where the need for accuracy is critical.

However, this is about to change. In 2024 we’ll see enterprises  — and financial services — will finally start to embrace the productivity, efficiency, and cost gains that LLMs can bring to their knowledge-intensive workflows. The enabling technology that will drive this adoption is Retrieval Augmented Generation (RAG).

RAG has the potential to transform many strategic but repetitive workflows, like KYB, compliance checks, investment research, regulatory reporting and risk monitoring, traditionally either performed by well-compensated analysts who could rather be utilised or left to expensive data vendors who outsource the work to offshore analyst teams.

Read the full TechRepublic report on 2024 Fintech Predictions. THe link is in the comments. 

#fintech #finance #ai #rag #genai #esg #privateequity 

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