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How This Fintech Startup Is Developing Low Latency Algorithms For Financial Markets

Emerging technologies have played a significant role in democratising the financial markets in India. For instance, in the case of financial-service companies, tech has helped to cut down the client onboarding time from a few days to a few minutes. With open APIs, various functions like trading, KYC processes, mutual fund operations, etc. can now be automated and customised to suit any requirements of organisations.

With a similar vision, Mumbai-based startup, Nerve Solutions is creating products for real-time risk management and surveillance in financial markets allowing market participants to identify and quantify risk and anomalies in live markets and take corrective actions at sub-second speeds. For this week’s feature, Analytics India Magazine caught up with the founder of the company to gain more insights on how it is using emerging techniques like AI and ML into their products.


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Founded in 2018 by Mihir K. Malani, Nerve Solutions is a team of software engineers with a deep understanding of financial markets as well as technology. It specialises in developing low latency algorithms for financial markets be it trading, risk management or real-time surveillance of trading behaviour and have exhaustive experience in handling large volumes of streaming and transactional data, an attribute peculiar to financial markets. 

n.Prime Performs The Risk Management

The flagship product, n.Prime is an advanced real-time risk management system that provides clients with a single dashboard to monitor and control enterprise-wide portfolio risk, suspicious trading activity and market manipulation attempts. 

n.Prime is built and tested to perform close to a million runs per second on complex derivatives portfolios. With the ability to function on-premises as well as on cloud, it has a flexible architecture enabling high performance and scalability.

How is it different from other products in the market? To this question, Malani replied that most incumbent systems are not fully automated and mostly operate in silos. These systems are hardly scalable and are managed by individual risk managers as per their discretion.

n.Prime solves this problem by standardising the risk management process across the entire organisation. The product makes the process of identification and quantification of risk and the follow-on process of decision making extremely transparent, bringing together all key stakeholders across the firm. 

Use Of AI At Nerve Solutions

The company uses AI techniques like Neural Networks, to implement predictive capabilities in n.Prime. Malani stated, “The process required us to work on large sets of historical data from various exchanges to build and train our models. Once built, they were plugged into n.Prime.” 

He added, “The models take in live transactional data during trading hours, run predictive analysis and throw results that aid risk managers in taking the right calls. These models are constantly trained to keep them updated with current market trends.”

At the technology side, the system uses a combination of low latency languages, databases and compression techniques to achieve a large number of computations per second. The company is mainly dependent on its proprietary ‘Best-Fit’ algorithm to identify risky assets and instruments within a portfolio.

How Is Nerve Solutions Fighting COVID

According to Malani, n.Prime and other by-products of the tool have helped the clients effectively manage and mitigate risks. These tools have enabled them to reduce their response time in situations of extreme uncertainties drastically. 

During the crisis, the focus of the company has been to altogether remove human error from the risk management process, ensuring a safer environment for traders, investors and all other market participants.  

What will be the environment for the fintech startups ecosystem who are not established yet? To this, Malani stated, “The current scenario is challenging but not without its share of opportunities. Startups who have just begun their journey will concur with this. There is no dearth of problem statements globally, and more so in the financial domain and if you are solving the right problems, there are enough takers out there.” 

He added that with the right approach, client acquisition costs could be brought down significantly, giving the much-needed push to early-stage startups.

Tackling Hiring Phase

The company does not test candidates for specific programming languages or capabilities. At Nerve Solutions, the emphasis is given to the overall aptitude and knack for problem-solving. 

Malani said, “This helps us broaden the talent pool as we are happy to evaluate candidates even from non-finance and non-computer science backgrounds. A flair for mathematics is an added advantage though.”

“Moreover, at Nerve Solutions, we have set training and assignment modules for all new team members. Given the complex nature of the domain, these modules help them get up to speed relatively quickly and internalise domain-specific concepts,” he added.

Future Roadmap

The global RegTech market size is currently $7 bn and expected to grow to $55 bn by 2025, expanding at a CAGR of more than 52%. In the coming years, the company is aiming to capture a global market share of 2% over the next five years. 

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Ambika Choudhury
A Technical Journalist who loves writing about Machine Learning and Artificial Intelligence. A lover of music, writing and learning something out of the box.

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