Author: Paul Ferretti
Auquan helps companies make faster decisions by extracting hidden insights from unstructured data, faster than anyone else. Paul Ferretti met Chandini Jain at the CogX Festival last month, to speak about how can AI help professionals in various financial institutions find hidden value in an overwhelming amount of noisy, seemingly worthless data.
Can you tell me more about Auquan’s mission?
Auquan is an AI startup. We enable customers in services like hedge funds, investments banks, private equity funds, to make better and faster decisions. We do so by getting the relevant information from a mountain of data significantly faster that they would manually.
What that means is 3 things.
They have access to a lot more of underlying data to make their decisions faster than they would earlier. They can also get access to information they usually wouldn’t be able to find because it’s impossible to make the connections our system is capable of.
We use natural language processing and machine learning in order to connect to all of the world’s unstructured text, and we run it through our language processing model. Then we connect it to what we store internally which are company and people ecosystems, and we create an online store of information that is accurate and free of noise.
We filter out the noise to surface only the most important information for a user.
For example, If you were to search for a Nokia on any browser, you would find out about all the features, but also all the discounts, all the marketing news concerning Black Friday or Boxing Day. This information is relevant for financial context, but not for users. We do all the filtering to give consumers what they are looking for. We run the end to end cleaning of data to make sure the end users gets only the most meticulous information, super customised to their case.
How can AI help professionals in investment banking, private equity, asset management, and other financial institutions find hidden value in an overwhelming amount of noisy, seemingly worthless data?
There is indeed a lot of noisy, seemingly worthless data.
The problem is today a lot of that work is done manually. I’ve heard again and again from my customers that their research team spends time just gathering, processing, and cleaning data. Their team will spend too much time reading and saying whether something is useful or not, which is not a good use of their time.
People would like it if AI could do the heavy lifting for them, and condense all the information down to what is actually useful for the associates. Employees could therefore focus on what humans are good at: Thinking, making decisions, dropping conclusions, not just pulling data from different data sources and joining them together.
Nobody grew up saying “I want to be an analyst at the bank!”. We’re therefore not building a system that can replace people, but a system that can do the mundane, boring and time consuming part and allow humans to do the creative, interesting, and decision making tasks.
Why have you come to CogX and what do you take from this experience?
I’m just amazed about how mainstream AI is now. Last year no one was talking about it. For my friends in other sectors, such as banking, consulting or even creative fields, AI was in a whole separate world. Today, they are all using tools such as ChatGPT or Midjourney. The audience at CogX has changed significantly from last year, with more people not coming from a technical field but still interested in AI, which I think is quite amazing.
There is so much excitement about what AI can do, a lot of startups are tying to build with it. There are also a lot of thinkers who are talking about the future potential of AI.
What matters is that we do it in a way where we are rational about the downsides, and we proactively catch them and build a defence. We built a system in a manner that they have an in-built defence to AI.
We have to make sure we build systems where AI is always taught to doubt itself, for it to say “I’m 99%, not 100% confident.” In order to deliver different options and different ways of solving a problem.
Are there people who have inspired you?
Yes, my mother.
Growing up in India, I encountered families where women were not meant to have serious careers.
My parents have raised me in a “gender neutral” environment. Growing up, I never had this idea that “men and women are different”. My mother is now the first one to introduce robotic surgery in her state, and is also running her entire department.
It’s never been boys do this or boys do that, it’s been “people” do that.
I grew up with not having a choice: I had to do something interesting, something technical. She has therefore been a huge inspiration in my life.
Do you have any advice for other entrepreneurs?
I left my previous job because I wanted to start my own company. I would not recommend anyone to start like that.
You should really have something in place, either an idea or a co-founder, or something grounding. I feel like I spent too much time in the early days spending energy on everything instead of having a structure.
But to me, the most important thing is your team. Great ideas with a terrible team will result in nothing, but a great team working on a mediocre idea could result in something amazing. I am so fortunate to have incredible people around me. Everyone in my company works hard and are extremely capable. They are just amazing people.
If you have a good team, everything else will fall in place.
I also don’t think you should consider your company as a family, but more like a sports team. Everybody is trying their best, including you, which is why you expect the best from everyone, and you need them to perform to win the championship.
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