Impactsure is modernising trade finance with AI and automation

Dharmarajan Sankara Subrahmanian, Founder & CEO, Impactsure on AI's potential in trade finance

The real power of data kicks in when companies can use it to drive automation and AI-enabled decision making.

“There is no reason to maintain so many manual processes,” says Dharmarajan Sankara Subrahmanian, Founder and CEO, Impactsure Technologies, an AI/ML-powered document analytics SaaS Web 3.0 company providing software solutions for the financial services and enterprises.

Subrahmanian, along with Subramaniyan Neelakandan (Chief Technical Officer) and Ashish Mohan Jha (Chief Operating Officer), founded Impactsure in 2019.

In this interaction with ET Insights, Subrahmanian shares why digitising trade finance documentation can provide real benefits, the role of AI’s potential in trade finance; and how it can usher in a new era of financial transformation. Edited excerpts:

What has been the genesis of Impactsure?

In 2019, we started as a software development and services company, offering data science solutions to a wide range of industries like manufacturing, pharma, logistics, banking, etc. The outbreak of COVID struck us hard, and we had to quickly refocus our strategy.

Rather than tapping opportunities in multiple sectors, we decided to focus on the banking and financial services sector. What we did in the logistics or manufacturing space came in handy when we focused on the financial services sector.

We started approaching trade finance as a niche segment within banking. Wherever there are documents, information, or manual processing, we can create a solution around it. That is how we started.

Our solutions can be used in corporate, retail, wealth, and investment banking in diverse areas like risk assessment, cash management, escrow, KYC, management of equity, debt instruments, bonds, derivatives, hybrid financial instruments, insurance, and ESG.

Trade finance underpins global trade. However, it largely remains paper-based and reliant on manual processes How are you helping companies leverage artificial intelligence (AI)-driven platforms to drive the next phase of trade finance growth?

Trade finance covers many financial instruments that financial services utilise to make trade transactions feasible. Multiple documents or activities, like bank guarantees (BG), letters of credit (LC), remittances, collections, etc., are involved in these transactions that the bank, buyer, and seller must scrutinise for accuracy and mitigate any risk.

If you look at LC, there are 16 to 17 different types of documents that need to be processed. It could be invoices, insurance, shipping bills, certificates of origin (COO), etc. and each document runs into several pages.

Banks need to take care of various regulations or guidelines, or there could be some country specific mandates. Sometime there could be sanction on some products in a country. Banks must be aware of all this information on a regular basis. Imagine doing this manually. It will take a lot of time.

However, it largely remains paper-based and reliant on manual processes. Corporate banking, especially trade finance, still relies heavily on paper-based documentation and manual processing.

It can roughly take anywhere from a few hours to a few days to manually create, edit, review, and approve such documents. This is again dependent on the complexity of the transaction and the proficiency level of the employees involved. Manual review can lead to inefficiencies, increased risks, higher costs, and ultimately a poor customer experience.

We are building an AI tool that can improve the output 200 times over manual efforts. That is the first part. The second area is around turnaround time which we can reduce from a few days to under 10 minutes. This creates an exceptional customer experience.

How has your growth story been in India and globally?

In India, we have some of the largest private-sector banks as customers. We are now focusing on the PSU and MNC banks.

Recently, we got a contract from Singapore Exchange to extract structured corporate financial data from its data repository. We also partnered with Temenos Exchange, an open marketplace for fintech solutions, to offer corporate banking AI solutions integrated with their core banking platform. Through Temenos, we now have access to more than 3,000 banks and customers worldwide. We are also tapping other international stock exchanges.

Another successful India story that is emerging is on the Environmental, Social and Governance (ESG) front. Companies are now looking at ESG data availability. We are developing AI solutions for extracting this ESG data from their sustainability reports that will help them with reporting and focus on their lending decisions.

Will you be entering the sectors that you were targeting when you started your operations, or will you be focusing purely on the financial space?

Within the bank itself, there are lots of opportunities that are opening. We started with trade finance and are now moving towards credit. We are looking at lending, and opportunities in Risk. In retail banking, we are looking at areas such as mortgages. We are in discussions with insurance companies.

So now we are looking at corporations and enterprises in a big way. To answer your question, yes, we will go back to all those manufacturing and logistics companies, but in a slightly different way.

We have developed a concept called Suretons like protons, electrons, and neutrons. These are microservices. Some are functional modules, some are technical, and some are hybrid. All of them address a particular use case. For example, a bank guarantee may require around ten types of Suretons, whereas an LC may need 20 types of Suretons. This can open a few more use cases without the need to develop a completely new product.

Disclaimer: The views expressed in this article are those of the author and do not necessarily reflect the views of ET Edge Insights, its management, or its members

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