Upside AI is one of the first funds in India to use machine learning to make fundamental investing decisions. Today, Upside AI ranks among the top-performing PMS’ in the country delivering 71% cumulative returns since Jul 2019. In Jun 2021, PMS AIF World ranked Upside AI Multicap in the top 10 products of its peer group. On the back of performance and organic referrals, our AUM has grown by 10x over the last year to over INR 65cr with funds from several HNIs, and family offices.

Analytics Insight has engaged in an exclusive interview with Atanuu Agarrwal, Co-founder of Upside AI, to discuss the effects of machine learning in the investment space, specialized services offered by the company, and much  more.

Kindly brief us about Upside AI, its specialization, and services that the company offers.

Upside AI is a SEBI-registered portfolio management (PMS) start-up that uses technology to drive investment decisions. Nikhil Hooda, Kanika Agarrwal, and I (Atanuu Agarrwal) founded Upside AI in 2017 with the belief that technology will make better investing decisions than humans over the long term. This is because machines are unbiased, unemotional, and unaffected by market euphoria and panic. It is therefore focused on building products that follow a rules-based, systematic approach to investing.

Upside AI’s first few products focus on equity investing using proprietary machine learning algorithms to understand, recognize, and buy companies that are fundamentally good businesses.

The first step is parsing the P&L, balance sheet, and cash flow data of all companies listed on the NSE. This was a non-trivial exercise, as meticulous data clean-up and standardization. The secret sauce is however the next step where the algorithm uses ML to shortlist companies that are not just fundamentally good businesses but also in-demand stocks. We do this exercise quarterly, to pick a portfolio of 10-25 stocks. We have also developed a framework for corporate governance checks to make sure the numbers fed into the algorithm are kosher.

We are a Portfolio Management Services or PMS, which caters to HNI’s, institutions, and family offices in India and globally. The minimum investment size is INR 50 lakhs.

Today, Upside AI ranks among the top-performing PMS’ in the country delivering 71% cumulative returns since Jul 2019. In Jun 2021, PMS AIF World ranked Upside AI Multicap in the top 10 products of its peer group. On the back of performance and organic referrals, our AUM has grown by 10x over the last year to over INR 65cr with funds from several HNIs, and family offices.

What is the company’s biggest USP that differentiates it from its competitors? 

As far as we know, Upside AI is among the first investment managers to combine machine learning and fundamentals-based investing. Our algorithms are completely proprietary and have been fully developed in-house.

In addition, driven by machine learning, our algos are dynamic and are not tethered to a particular style of investing (like momentum, value, etc.) It can adapt to different market conditions and tailor portfolios accordingly. Therefore, it can consistently deliver alpha over the index, which is difficult for human managers who may thrive in some market cycles but struggle in others.

Technology and rules-based investing already dominate mature markets; in fact, the top 5 hedge funds in the world are quant. 5-10 years from now this will play out in India too and we are excited to be at the forefront of this movement.

How is machine learning impacting the investment space?

As I said earlier, ML is pretty dominant in the investment space. I think access to clean longitudinal data makes it an ideal environment for AI/ML-based algorithms.

AI is slowly driving the way investors analyze and implement trading strategies. High-performing computer-managed funds like – ETFs, quant funds, and index funds make around 35% of US public stocks. Notably, the US now has more ETFs listed than stocks. Also, the top five hedge funds in the world are now quant funds collectively managing close to $1trillion. According to Deutsche Bank, 90% of equity-futures trades and 80% of cash-equity trades in world markets are executed by algorithms without any human input

In India, algo trading is mostly associated with high-frequency trading and runs about 45-50% of the cash and derivatives market. ETFs are still in their early days here. Initiatives like Digital India and VC funding are going to further disrupt investment space in India, which so far has been dominated by star human fund managers and large bank-owned AMCs.

Kindly mention some of the major challenges the company has faced to date

The idea was really to step zero. After that, there were several milestones in our journey, including, (i) cleaning up ~20y of financial data, (ii) unbiased and robust back-testing, (iii) real-word beta testing, (iv) frameworks for qualitative issues like corporate governance, and (v) last (but not the least) acceptance of tech-driven by distributors and clients.

It took nearly a year to build out the tech and back-test it; then another year to test it in the live market, before we took out of beta and started offering to third-party distributors and clients in July 2019.

One of our major challenges was that we were pitted against established players in an industry built on trust. Adding to that was the fact that we were all perceived as outsiders since we came from a background in venture capital and technology.

Building a network of investors and distributors virtually from scratch remains one of our biggest challenges even today. Additionally, convincing people to put their trust and money into a newly introduced tech-based product was a mammoth task. However, our aim since day one has been to make investors realize that one must diversify away from human-led investing. Over the due course, on the back of our consistent performance and sustained alpha, clients, wealth managers, and distributors associated with us have come to appreciate that tech-based products should be an integral part of one’s asset allocation strategy.

What are the key trends driving the growth in the portfolio management services space? How do you plan to tap into the market?

I think one of the biggest factors has been the underperformance of mutual funds. Over the last 5 years, the biggest mutual funds have failed to beat their benchmarks. At the same time, performance on PMSs has improved, especially on the back of small- and mid-cap rallies over the last couple of years.

In general, greater penetration of household wealth will also drive growth. Today, with 5-10% penetration we are in the early days of the asset management industry. As savings are diversified away from traditional assets like real estate and gold, and with negative real interest rates, PMSs may see higher allocations from HNIs and family offices.

We are very focused on building a network of large distributors, wealth managers, brokers, and IFAs – we onboarded several distributors over the past year, and are constantly looking for new partnerships. We believe that pure performance marketing does not work and we instead want to focus on long-term community-building driven by organic content and brand-building through online and offline channels.

What are the key milestones and growth numbers achieved since inception? What are your future plans?

We want Upside AI to be a world-class 100% tech-driven asset management company (AMC). We aim to achieve this by building an array of products across asset classes and strategies. Apart from the two live products, we have another couple of products in development, which we plan to launch over the next 6-12 months. We are also working on building an end-to-end digital platform where we want tech to drive the entire chain from client onboarding to sophisticated investment tech to live tracking and reporting via a seamless UI/UX experience for clients. Over the next couple of years, we want to add 1,000 HNIs, family offices, and institutional clients and grow to INR ~1,000cr in AUM.

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Prashant Borde, a second-time entrepreneur, is the Co-founder of Recko to solve finance teams’ problems using deep tech. Before Recko, he co-founded Cubeit (acquired by Myntra) — a tech startup focused on distributed computing and machine learning on large-scale distributed systems, and spent much time writing Computer Vision and Image Processing programs.  Prashant holds a Bachelor’s in Technology, Electric Engineering, and Computer Science from IIT, Gandhinagar. He also holds an Entrepreneurial certification from Stanford University and has been part of several research projects, one of which is Computer Science for Caltech specializing in Community Seismic Network.  Prashant is an avid cricket fan and follows it religiously.

Here is an exclusive interview with Prashant Borde, Co-founder & CTO, Recko that enlightens us on how he aims to enable roadside vendors as well as hi-tech reputed companies to monitor large sets of real-time data and take smart informed financial decisions efficiently.

Kindly brief us about the company, its specialization, and the services that your company offers.

Recko is a finance operations platform for fast-growing internet companies. It provides a comprehensive and robust technology stack to manage financial data and enable financial workflows such as reconciliation, commission calculation, payout creation, and reporting for businesses to track, manage and account money end to end.

The company was set up in 2017 by Saurya Prakash Sinha and myself. At present, we are a team of 100 with stellar experiences across e-commerce and fintech companies such as Flipkart, Amazon, Nutanix, PhonePe, Ola Money, and Razorpay.

At present, Recko offers two products:

Reconciliation: Our Reconciliation product is used by finance teams to monitor and track the money coming from all the channels like payment gateways, aggregators, offline stores, and going out to marketplace sellers, and delivery partners. The whole process of reconciliation is generally done once in 35-40 days due to the effort involved, but with Recko as a financial system, our customers can do this daily.

Commission Calculation: Our Commission calculation module allows users to keep a check on the charges applied by their payment partners, marketplaces, acquirers, logistic partners, etc. It is built to handle usage, target, transaction, and tiered fee structures.

We will be releasing Ledgers and Payouts soon. This gives an edge for businesses to maintain their entire financial infrastructure on Recko.

With what mission and objectives, the company was set up? In short, tell us about your journey since the inception of the company?        

The global economy was witnessing a digital revolution. Every business out there was starting to accept digital payments. From a roadside vendor to a multi-billion internet company, everyone was getting comfortable receiving payments directly to their bank account.

And, needless to say, customers also preferred this mode of payment. It is convenient and happens at the click of a button. This digitization paved the way to get things done faster and easier. Every other day, there are also newer innovative payment methods being added like buy now pay later, UPI-based lending, etc.

While the process is simple and smooth for the customers, we noticed that the merchants faced certain issues when it comes to reconciling these payments due to outdated tools and practices. The amount of data that is generated in the last two years is more than the data generated in the last 100 years collectively. This data resides in data warehouses, data lakes, and is siloed. Especially from a finance point of view, the amount of data that the finance team has to analyze to understand the money that is flowing through their systems has skyrocketed.

Traditional tools like MS Excel cannot scale to the demands of today’s finance function. To compete fiercely, businesses are looking into the data to ensure business integrity, financial controls and identify growth avenues and increase margins. Data-driven software companies are providing cleaner, usable data to make financial operations within a business better and forward-looking.

That got us thinking, what if there is a tool that enabled internet businesses to reconcile easily and thereby helped them make informed financial decisions. As the business needs and consumer behavior evolve, their finance teams need to transform as well.

Saurya and I identified this problem in the companies we worked at.

We saw a huge uncharted business opportunity here. Having closely worked with the finance teams, ourselves, we understood how a product such as Recko would empower its users in terms of financial decisions. We aimed to automate and Fastrack this process.

Today, Recko enables businesses to monitor large volumes of transactional data without writing a single line of code. It ensures that the money flow between the beneficiaries is in correlation with what needs to be paid out.

Recko’s global financial operations platform is currently used by technology companies in three regions – Europe, India, and Southeast Asia with customers across multiple industries like e-commerce, food tech, fintech, neo-banks, gaming, etc. We work with companies like Deliveroo, eCommerce, Grofers, Meesho, Dunzo, Pharmeasy, Curefit, Udaan, MPL, Khatabook, and so on.

Tell us how your company is contributing to the AI/Big Data/ Analytics industry of the nation and how the company is benefiting the clients.    

Right now, we leverage concepts in Big Data, Analytics, and AI. We went through a unique challenge of dealing with scale early in our journey. In response, we put a lot of effort into understanding and building modern concepts in Big Data and Analytics. We have built a data platform that supports precision at scale, high consistency, and iterative data transformation and analytics. Our platform supports critical functionalities like retrospective changes with audit trail, time travel at scale, and so on.

Using Recko, customers can automate reconciliation and commission calculation. A typical month-end closure process that takes multiple weeks can be done in just a few hours. With our integrations, our customers are able to monitor money flow daily. With historical reporting and advanced analytics across multiple years, finance teams have much higher visibility. Finance teams using Recko are able to take care of strategic business decisions as Recko takes care of reconciliation, end to end.

How does Recko’s financial operations platform empower finance teams?

Finance teams often spend a lot of time normalizing the data. This is because they receive data from multiple sources such as settlement files, order management systems, banks, etc. Each of the files has a different format, but at the end of the day, they need to be cross-checked to ensure that the information available across all these files is in tandem with one another.

The finance team’s responsibility includes transforming these data and then reconciling them. More data processing is required when working with different finance tools used for accounting, tax, payouts, etc. One can only imagine how difficult things would turn out to be when the volume increases. Sometimes the traditional on-premise tools such as excel freeze, running into resource crunch due to a combination of complex logic and volume. There is a high scalability issue. It has integrity checks, sometimes lacks version control, and the ability to correct historical mistakes.

Recko smartly identifies the data that is fed into the system with the help of pre-defined rules and reconciles at a transactional level. It provides a comprehensive and robust technology stack to manage financial data and enable financial workflows such as reconciliation, commission calculation, payout creation, and reporting for businesses to track, manage and account money end to end.

Kindly mention some of the major challenges the company has faced till now.

One of the unique challenges we had was supporting scale at the very start of our journey. We needed to focus on accuracy as well. That helped us to gain the trust of the finance teams and gave us the confidence to march further.

We had to let go of the typical thinking that you find in startup product development code first. After our first release, we understood that this is not the way to move forward. Unlearning this has been a great challenge as we started scaling. We moved to a customer-first approach and started planning the roadmap and how the features that we build now will scale in the future.

What is your biggest USP that differentiates the company from competitors?

“Finance Operations Platform built for the Internet ecosystem which ensures 100% accuracy, scales seamlessly and manages complexity effortlessly.”

The Recko Financial Operations Platform empowers finance teams in fast-growing internet businesses with a comprehensive and robust technology stack to build and embed innovative financial workflows such as reconciliation, commission calculation, payment orchestration, and reporting. This allows businesses to accelerate growth, collaboration, and track and manage money end to end. Recko ensures that every dollar, euro, or pound that the company moves is accounted for and the financial needs of the ever-evolving business are taken care of

Brief us about the products/services/solutions you provide to your customers and how do they get value out of it

At present, Recko offers two products – Reconciliation and Commission calculation. We will be releasing Ledgers and Payouts soon. This gives an edge for businesses to maintain their entire financial infrastructure on Recko.

Reconciliation

Our Reconciliation product is used by finance teams to monitor and track the money coming from all the channels like payment gateways, aggregators, offline stores, going out to marketplace sellers and delivery partners. The whole process of reconciliation is generally done once in 35-40 days due to the effort involved but with Recko as a financial system, our customers can do this daily.

This has enabled the finance teams to identify the gaps and plug them right away rather than waiting for it to accumulate over a period of time. Our customers have recovered large sums from partners and prevented doubled payouts. They can reconcile their Nodal/Escrow accounts easily. Some of our customers who integrated Recko early into their finance systems drastically reduced the due diligence time during fundraising and got access to funds faster.

Commission Calculation

Recko maintains all the commercial terms and the agreed payment cycles in its system. This eliminates human errors or guesswork.

Our Commission calculation module allows users to keep a check on the charges applied by their payment partners, marketplaces, acquirers, logistic partners, etc. It is built to handle usage, target, transaction, and tiered fee structures. Our customers have recovered incorrectly charged commissions from their business partners, payment gateways and closely watch transaction ageing to ensure they don’t go short of working capital.

What’s your growth plans for the next 12 months?

Our immediate plan is to add more products like payouts calculations and ledger to our existing suite. The payouts calculation module will help startups and growth-stage companies have payouts set up without investing any time or precious engineering bandwidth in development. The ledger module will be a single source of truth for your financial data.

We are also constantly adding new features to your reconciliation and commission calculation module to solve complex use cases. Our long-term goal is to provide enough insights that enable businesses to make financial decisions in real-time.

Recko is a finance operations platform for fast-growing internet companies. It provides a comprehensive and robust technology stack to manage financial data and enable financial workflows such as Reconciliation, Commission calculation, Payout creation and reporting for businesses to track, manage and account money end to end.

Prashant Borde, Co-founder & CTO, Recko.io

Prashant is also a second-time entrepreneur and co-founded Recko to solve finance teams’ problems using deep tech. Before Recko, he co-founded Cubeit (acquired by Myntra) – a tech startup focused on distributed computing and machine learning – on large-scale distributed systems and spent much time writing Computer Vision and Image Processing programs.

Prashant holds a Bachelor’s in Technology, Electric Engineering, and Computer Science from IIT, Gandhinagar. He also holds an Entrepreneurial certification from Stanford University and has been part of several research projects, one of which is Computer Science for Caltech specializing in Community Seismic Network. Prashant is an avid cricket fan and follows it religiously.

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Qandle aims to help organizations experience the advantages of next-generation technologies. Founded in 2016, the company now has about 3 lakhs of satisfied users and they have served more than 20 companies. The company functions from three locations in Delhi, Hong Kong, and London. Analytics Insight has engaged in an exclusive interview with Himanshu Aggarwal, the former IIT Roorkee student who co-founded Quandle.

Tell us how your company is contributing to the IoT/AI/Big Data Analytics/Robotics/Self-Driving Vehicles/Cloud Computing industry of the nation and how the company is benefiting the clients.

Qandle is a technology-first startup. It has leveraged technology to develop a modular and extremely flexible solution for organizations looking to deliver the next-generation experience to their teams. The platform recently launched ‘Qanbot’, an AI-enabled bot to address day-to-day queries of employees, which leads to reducing the mundane tasks for HR Managers. The product includes other AI-based solutions such as a resume parser for faster and better recruitment and predictive analytics for data-driven decision-making.

How is IoT/Big Data/AI/Robotics evolving today in the industry as a whole? What are the most important trends that you see emerging across the globe?

There was a time when even landline phones were a big hit. But things evolved, and over the period we saw its size shrinking. Today this palm-size device has converged several tasks and technologies within itself. It is very much capable of assisting us, managing tasks, keeping records, etc. With better execution of AI, this is only going to get smoother, and unimaginably wonderful. AI holds the potential to revolutionize every industry in terms of experience and functioning. In addition to this, it also holds immense business potential. Reports forecast AI annual growth rate to be around 33.2% for the period between 2020 and 2027.

This is going to shift people to more strategic and smarter roles. For instance, today an HR manager mostly exhausts his man-hours in answering employee queries, resolving mundane challenges, and keeping records. If we replace it with an AI-enabled bot, the HR Manager can now focus on the real strategic work. Contrary to popular opinion, this technology is going to unleash the true capabilities of people.

What are the key trends driving the growth in Big Data analytics/AI/Machine Learning?

Currently, it has been observed that AI-driven chatbots are getting widely adopted. A lot of B2C brands are saving big numbers by implementing this tech product in their customer service departments. B2B companies are also getting higher leads through AI chatbots on their websites.

This takes the entire customer service experience a notch up and also saves a lot of time and money while providing a superior experience and a quick resolution to customers. Talking about figures, around 40% of internet users worldwide prefer interacting with chatbots over call center executives.

How is Machine Learning (ML) shaping the IT/Big Data/Robotics industry today? How is it changing the role of CIOs and Leaders?

In recent years, a lot of new technologies have disrupted many industries, and ML is one of the most impactful ones. As the implementation of technology has increased, adapting to the continuously evolving business dynamics has become easier. With the abundance of data, earlier people needed a lot of time to process it, whereas now one can analyze and scrutinize through ML in a short period and make smart analyses. However, building the road ahead for any technology, be it ML or Big Data, is still a job that C-Suite executives and academicians need to drive. The growth of the domain is still very much dependent on the leaders.

Could you highlight your company’s recent innovations in the AI/ML/Analytics space?

We have recently launched ‘Qanbot’, an AI-enabled chat and voice bot to address day-to-day HR queries of employees, and perform basic HR tasks like leave application, raising of issue tickets, etc., on their behalf. This saves a lot of time for both HR teams and employees themselves.

In addition, we use and provide a lot of visual analytics and actionable insights to our customers across all of our 20+ modules and promote smarter data-driven decision-making.

What is the size of the analytics team at Quandle?

We are fans of building a lean startup and have managed to keep our headcount to below 50 for about 5 years now. Our analytics team consists of 2 people.

How is your company utilizing advanced analytics and big data?

We provide a lot of analytics within our solution across modules for our clients. For example, to better understand employee productivity, we share details like productivity, desk time, effectiveness, most and least productive times of day, etc.

At the organizational, location, and department level, we share analytics like headcount trends, retention rate, employee tenures, compensation trends, etc.

All these data points are provided in beautifully designed graphs and charts, while our customers can use our report builder tool to build and share their reports as well.

What are some of the challenges faced by the industry today?

As the industry of data analytics is new, it is very much beneficial when one needs to make informed decisions and have time on their side. Since it does take some time to run computations and increase the accuracy of various analytics models, it still takes time.

However, a lot of people still expect to base their ‘not so immediate’ strategies on the solution, and then face disappointment because they have invested too much and expected a quicker turnaround. It is more advisable to utilize the solutions with precision and in sync with its capabilities and asks. As the technology grows, eventually it will become less expensive and more precise.

What would you advise aspiring big data and analytics candidates?

Looking back from where we started, it is evident that it will always be a matter of surprise to figure out successful executions and wonders of technology. Given the fact that we have only scratched the surface when it comes to data analytics, we understand that there is a huge potential, and simultaneously a big need for talent. Every field runs on data and needs experts. The career prospects shall become brighter if a candidate pursues specialization in the field of analytics. There are many courses available online nowadays. More than the certifications, what matters is, what the candidates know and if they can think logically.

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Joe Lonsdale said on CNBC on Monday that his fellow Palantir co-founder Peter Thiel was “courageous” for speaking out against Alphabet’s Google.

“Google is not a patriotic company,” said Lonsdale, also a founding partner of technology investment firm 8VC.

Lonsdale was responding to the criticism levied since Thiel on Sunday said the FBI and the CIA should investigate whether Google has been infiltrated by Chinese intelligence.

Thiel, also a Facebook board member and a supporter of Donald Trump’s 2016 presidential campaign, was speaking at the National Conservatism Conference in Washington, D.C., and Axios reported on his speech.

“Everyone in [Silicon] Valley knows that the Chinese government is very involved,” Lonsdale told “Squawk Alley” in an interview, though he didn’t point to any clear evidence. “It’s something we don’t talk about a lot. It was very courageous of [Thiel] to talk about it.”

Google, responding to Thiel’s comments, said, “As we have said before, we do not work with the Chinese military.”

The environment at Google is very “academic,” Lonsdale said, where people want to share their work across the world. “There’s nationalists in China coming and taking whatever they can learn and taking it back and using it for their own nationalist purposes.”

Lonsdale also commented on Google’s contract with the Defense Department, which expired earlier this year and was not renewed. “When Google made the choice ‘we’re not going to help the U.S., but we’re going to continue to work in China,’ it was very clear,” Lonsdale said of the company’s patriotism.

Silicon Valley-based Palantir, the data analytics miner, has worked with many agencies of the U.S. government, including the Defense Department, CIA and FBI. Lonsdale on Monday called Palantir “probably the most patriotic in the Valley.”

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