Auquan uses AI to transform investment research, KYB, and ESG for financial services. Pulse 2.0 interviewed Auquan founder and CEO Chandini Jain to learn more about the company.
Chandini Jain’s Background
Jain has been in global finance for a decade. And Jain said:
“Prior to founding Auquan five years ago, I worked in Amsterdam and Chicago as a derivatives trader at Optiver, one of the largest market makers in the world. Before Optiver, I was an interest rate structurer at Deutsche Bank.”
Formation Of Auquan
How did the idea for Auquan come together? Jain shared:
“The finance industry is a very data-driven one, and both Optiver and Deutsche Bank were no exceptions. We analyzed both real-time and historical data on a large number of companies and subscribed to just about every data provider we could. The amount of unstructured data that flows in every day that needs to be processed can be overwhelming, and it’s too easy to miss material information hidden in all of the noise.”
“A significant amount of an analyst’s time is spent manually sifting through volumes of company filings, research, regulatory updates, legal documents, competitive and supplier intelligence, media coverage, and sustainability reports. It’s a very inefficient and error-prone process at every financial services firm.”
“I realized that with emerging AI technologies such as natural language processing, much of the manual work of sourcing data and finding relevant insights hidden in the noise could be automated using AI technologies. Financial services appeared to be tailor-fit for an AI-driven transformation.”
“I imagined financial industry professionals focusing much more of their time on high-level analysis and making more informed strategic decisions much faster than they could before — and consistently ahead of the market.”
“So I left Optiver and founded Auquan to make this vision a reality.”
Challenges Faced
What challenges did Jain face in building the company? Jain acknowledged:
“The financial services market is a challenging one for a startup to address, so we invested a lot of time and effort to find early adopters, work closely with them, and foster customer champions who shared our vision and understood the ROI Auquan delivers.”
“The good news for us with the financial services market is that it’s a close-knit community of peers where word-of-mouth is an important way professionals discover new things. Once our early customers found success with Auquan, they told others about us.”
“Raising initial capital is a big challenge for any startup, and Auquan was no different. There is a virtual ocean of AI startups all vying for venture capital, but technology alone is not enough. Our deep domain expertise in financial services and a strong understanding of the problem space was a story that resonated with our investors.”
“Navigating the COVID crisis was a challenge — it hit just as we were beginning to build our Auquan Intelligence Engine SaaS product when we were establishing what kind of organization and culture we wanted to have. The experience was a trying one, but we emerged stronger, having navigated through it together as a team.”
“Another challenge was a technological one. We had our vision, and we have an amazing team of AI/ML engineers, but early on, we were experiencing many of the issues with generative AI that is now widely known for enterprise use cases, such as a lack of access to up-to-date and domain-specific data, an inability to cite sources, and fabricated responses — the hallucination issue.”
“When we discovered retrieval augmented generation (RAG) AI, it was a real breakthrough. RAG AI is an AI technique developed by Meta that combines the power of retrieval-based models that can access real-time and industry-specific datasets with generative models that are able to produce natural language responses.”
“Once we implemented RAG AI under the hood, our financial services customers were surfacing relevant and meaningful insights that they, or other solutions, couldn’t produce themselves. And the information is consistently up-to-date, credible, accurate, and trustworthy. RAG AI has been a game-changer for Auquan and for our customers.”
Funding
How much was your recent funding, and what do you plan to use it for? Jain revealed:
“We just closed our seed round for $3.5 million, led by Neotribe Ventures, with participation from Episode 1 and Stage 2 Capital. We plan to use this investment to continue developing our RAG AI-powered intelligence engine and further expand our market presence in the United States. Previously, Auquan was a member of the 2018 TechStars London cohort and had earlier raised $1 million in pre-seed financing.”
Core Products
What are the company’s core products and features? Jain explained
“Our flagship product is the Auquan Intelligence Engine, a SaaS-based solution that helps financial services customers extract timely intelligence from vast amounts of unstructured data for use cases such as company due diligence, customer onboarding, risk intelligence, ESG, and controversy monitoring.”
“Auquan’s Intelligence Engine eliminates the need to invest time sourcing and sifting through volumes of information to produce the insights needed to make strategic investment decisions. Auquan automatically collects this data and surfaces relevant insights, empowering finance professionals to refocus their time away from undifferentiated, mundane manual data work.”
“Every customer has different needs, requirements, and workflows, so we built our Intelligence Engine product to be highly customizable. More and more of our customers use our product dashboard daily to stay ahead of any development concerning companies they care about, while some prefer regular email updates, and others choose to integrate Auquan’s data with their systems.”
“We built Auquan’s Intelligence Engine using RAG AI, so our customers know that they’re always getting the latest, relevant, and accurate information that they can trust to use in making important decisions.”
Significant Milestones
What have been some of the company’s most significant milestones, and what type of impact do you hope to make in the marketplace? Jain cited:
“Without a doubt, our most significant milestone was landing our first paying customer, and next would be getting our first big customer! Some of the largest asset managers, investment banks, and private equity funds in the U.S. and Europe have already deployed Auquan.”
“Closing our seed round is obviously a big milestone for us, as was getting accepted to TechStars London.”
“A massive shift is underway with AI that spans all industry sectors, and our vision is to leverage RAG AI to completely transform how financial services firms conduct knowledge-intensive research and intelligence, which is currently a significantly time-consuming and costly process.”
“Auquan will shift the paradigm for how financial services firms perform critical functions, such as company due diligence, ESG and sustainability research, and risk and controversy monitoring.”
Customer Success Stories
After asking Jain about customer success stories, she highlighted:
“One big advantage that Auquan’s customers have with our product is that they’re now consistently surfacing material information that was concealed within noisy data or hidden in supply chains or obscure data sources, such as local language media coverage.”
“One success story that demonstrates this concerns the controversy over social media moderation. In early 2022, local reports began to surface about abuses suffered by TikTok moderators based on lawsuits that were filed against the company between December 2021 and March 2022. Auquan had already identified that Teleperformance, a publicly traded company, was a provider of moderation services to TikTok. Auquan flagged this as a risk for Teleperformance and continued tracking the risk throughout 2022, ultimately leading to a front-page controversy for the company that resulted in a 35% stock decline in November 2022 and the company’s exit from the moderation business. Auquan’s customers were well aware of this risk a full six months before market reaction.”
“Some of Auquan’s customers were interested in identifying the hidden beneficiaries of the Inflation Reduction Act — the less obvious companies in the supply chain that stood to gain from the public investment, but the market hadn’t priced this in yet. Auquan’s ability to map second and third order supply chains helped our customers identify new investment ideas that others were missing, such as a supplier of welding tools for EVs that had just announced a factory expansion or a recent spinoff from a chemicals company that supplies electrolytes or cathodes for EV batteries.”
“But for us, the best customer success story is the one that all of our customers share: the return on their investment in Auquan that they get from using our product. They’re spending far less time on mundane data search and collection work and much more time on what they are actually good at — drawing conclusions, making predictions, identifying the materiality of risks, and just making overall better decisions. Auquan just makes their daily work life better.”
Market Focus
What is the market your company is pursuing? Jain replied:
“Auquan is hyper-focused on delivering the best research and intelligence solutions for the financial services industry. Private equity firms, investment banks, insurance providers, and asset managers all share the same challenge: They’re flooded with textual content that contains material information, and they’re compensating talented professionals handsomely to spend the majority of their time manually processing it all. Auquan liberates them from all of this manual data work.”
“Our customers use Auquan for a variety of knowledge-intensive functions that involve large volumes of unstructured data, including private company pre-screening and due diligence, ESG research and monitoring, continuous portfolio intelligence, Know Your Customer (KYC) background checks, and underwriting risk intelligence.”
Differentiation From The Competition
What differentiates the company from its competition? Jain affirmed:
“A lot of companies claim to have AI in their products, or perhaps they’ve integrated a standard large language model (LLM) in their product or built an application on LangChain.”
“What makes Auquan different from our competition is that we’re financial services domain experts who deeply understand the use cases and challenges our customers face, but we’re also an AI-native startup with some of the best AI/ML engineers in the industry. And because Auquan’s Intelligence Engine is built using RAG AI, we can scale to address the increasingly demanding nature of financial services use cases while maintaining the level of timeliness, accuracy and trust our customers expect. In fact, we recently published a white paper about it, The Advantages of RAG AI (Retrieval Augmented Generation) Over Generative AI for Financial Services.”
‘Auquan is easy for our customers to adopt, and the time-to-value that they experience is measured in the time it takes to go get coffee.”
Future Company Goals
What are some of the company’s future company goals? Jain concluded:
“At Auquan, we want to change the way knowledge-intensive tasks are done in the financial services industry and become the go-to solution for company due diligence, KYC, ESG research, portfolio intelligence, and risk monitoring.”
“To achieve this, we will stay relentlessly focused on working closely with our customers to ensure their continued success and keep working hard to advance RAG AI for financial services.”
