Matchmaking isn’t just for dating or matrimony services. It’s now a model for many businesses like Marquee Equity, a disruptive fintech platform that is revolutionizing the way companies raise capital, globally.

“These two start-up founders have self-funded their new venture to keep the business afloat.”

“That founder took out two home mortgages to get money.”

These are some common start-up “corridor conversations” we often come across. And they are real.

Launching a business does come with a lot of obstacles.

Ash Narain, Co-Founder and CEO of Marquee Equity (ME), is one such entrepreneur who has been through the grind himself. For him, there is one major challenge that stands out in every entrepreneur’s mind: financing.

“In 2012, I was looking to raise capital for my company BankerBay Technologies (now Aurigin).  I faced a lot of issues, particularly in getting access to quality investors. I used to send cold messages to them via email or on LinkedIn,” recalls Narain.

Most entrepreneurs aren’t investment bankers. They lack the know-how of building financial models, pitch decks, etc. and they are single-mindedly focused on building their companies.

Early-stage fundraising is unpredictable, and it also has a high failure rate. Narain wanted to create a platform that overcame the hurdles that startups undergo to find the right investors for their businesses.

Raising AI: From handholding to matchmaking

In 2016, Narain along with Raj Kabir (who is also the CTO) founded Marquee Equity, a global fundraising platform. It operates as an unbiased, technology-driven platform catering to SMEs and early-stage companies around the world.

“Early-stage entrepreneurs have little quality representation. Through this platform we connect each entrepreneur with the best investors and guide the company to maximize their fundraising efforts,” says Narain.

The team has been doubling down on technology to pinpoint its differentiation in a diverse landscape.

“Through the use of our proprietary AI systems, we have successfully automated the majority of investment banking processes. Our disintermediation platform can handle 8X the deal volume of an average investment banker, which has drastically reduced the amount of time it takes to find the right investor – from a few months to just a couple of weeks,” informs Narain.

The AI algorithm can predict which company is likely to raise capital and when. Based on this prediction, the team then reaches out to the company and helps them decide whether they should be raising capital as an equity or debt? What valuations should they be raising at, and who should they be raising it from?

“The outreach to these companies is completely automated. We don’t have a marketing department. Our algo is our marketing team. We have enough lead generation technology built-in to also become a lead generation company, and can lease out or license our solution to create a separate line of business,” Narain says.

ME has a cohort of 6,000 plus angel investors and 25,000 investment firms on its platform across the globe. They also rely on investment bankers who bring in the human element to advise on transactions, attend calls, negotiate, and so on.

The company charges its clients on a two-tier basis, which includes an initial setup fee and a commission on the total deal size.

Once a company registers, it is onboarded on the platform. The algorithm is fed with all the details of the company like the background of founders, the sector it represents, how much capital they are looking to raise, etc. Based on these inputs the algorithm then returns a ‘match’ list of investors.

“Our level of match-making is very comprehensive, and we can identify the right person for the deal basis their profile and the area of focus,” informs Narain. “Once the match-making returns the list of potential investors, we just hit a button and those investors start receiving the information from us,” explains Narain.

These mails are then followed up through automated communication using AI-built engines. “Since we manage hundreds of deals at any given time, we have created crawlers for inboxes. We are able to read the inboxes and can know which inboxes investors are interested in. We can also determine if the response is positive, negative, or neutral,” says Narain.

Having sent millions of emails to investors, the system can also predict when a particular investor is likely to check their mails, at what time of the day, and when they are likely to respond.

“We have been able to use these data points to effectively decide when our customers should be reaching out to investors. This has helped us to improve the results that our clients can get from our platform,” says Narain.

A ME client can log in to a dashboard and check the status of their fundraising campaign.  They can also view the list of investors who have been reached out to, whether they are interested in the deal or not, and so on.

Currently, ME has around 800 transactions that are running on the platform and these are managed by only 10 transactional managers. Had this been an offline investment bank they would have required a minimum of 80 transactional managers to lead it.

“The technology has helped us operate at one-tenth the size that otherwise we would have required to run the same number of deals. It has lowered the service cost, increased efficiency, and has also enabled more companies to use our services,” says Narain.

What next? Finding El Dorado

Venture capitalists have long funded artificial intelligence startups. They are now, with some reluctance, turning to AI to help them navigate potential deals and get a competitive edge in their own investment decisions.

“Many investors don’t want themselves to be replaced by AI tools or they feel that machines can’t be trusted with making investment decisions,” says Narain.

Researchers at the University of St. Gallen, built an investment algorithm to select the most promising investment opportunities. They then compared its performance with that of 255 angel investors. Their algorithm outperformed by 184%.

According to Gartner, AI will be involved in 75% of venture investment decisions by 2025.

“If tech can get robust enough to judge a deal and allocate capital, it will be the final frontier as far as VC and private equity are concerned. With AI and natural language processing (NLP) stacks evolving, maybe in a decade, we can see this happen,” says Narain.

Till then ME, which itself is bootstrapped, and has been funding its own growth, will play the ‘matchmaker’- helping startups get investments faster.

By Ashwani Mishra

Ashwani Mishra is the Executive Editor at DynamicCIO.com and DynamicCISO.com. In his previous role he was the Editor at The Economic Times (ETCIO.com and ETCISO.in). He has around 17 years of experience in the IT Media space, and has also worked in senior editorial positions at The CTO Forum (now CIO & Leader), CXOtoday.com and UBM (Network Computing).

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