AI and Machine Learning are revolutionary technologies that are being aggressively adopted by Indian Fintech startups.
Artificial Intelligence (AI) is one of the Fourth Industrial Revolution’s foundational pillars.
Machine Learning (ML), a subset of AI, is of particularly interest because it enables computers to learn independently, without requiring additional human intervention. Programmers ‘simply’ create a complex architecture of Artificial Neural Networks (ANN) and let the computer analyze, learn and improve all on its own.
This technology presents innumerable benefits:
- Automation of everything.
- Wide range of applications.
- Accurate and in-depth analysis of structured, semi-structured and unstructured data.
- Near-instantaneous analysis.
- Pattern recognition.
- Predictive analysis.
- Comprehensive risk assessment.
- Identification of threats, anomalies and defects.
Did you know that India is one of the global leaders in the adoption of AI and ML technology?
A recent global study conducted by PwC India revealed India witnessed the highest increase in AI use compared to major economies like Britain, Japan and the US. Indeed, over 70% of Indian organizations implemented AI in some functional areas in 2020, compared to around 62% last year. Further, over 90% of companies are implementing or planning to invest in AI solutions to address current business concerns.
In 2021, a worldwide survey of data professionals revealed that adoption of Machine Learning in their company is 45%. However, there are important disparities between regions. Israel (63%), the Netherlands (57%) and the USA (56%) boast the highest adoption rate.
In India, the adoption of AI and ML technology is clearly on the rise:
- 34.5% of respondents say their employer is using ML methods.
- 10% say they are using ML methods for generating insights but have yet to put working models into production.
- 21.6% say they are exploring ML methods and may use them one day.
This data is highly encouraging and suggests that an incredible transformation is taking shape.
India is embracing technology and rapidly emerging as a global hub.
In particular, Indian Fintech startups are adopting AI and ML technology at a rapid pace.
Here are 11 ways they are using AI and ML to disrupt the financial industry.
1 – Digital Payments
India is digitizing as a phenomenal pace.
A large portion of the population is under-banked and unconnected to the internet. They enter the digital economy by immediately adopting technology. A smartphone is often their first device, which means many never use legacy payment systems.
As a result, digital payments are on the rise.
In 2021, their total transaction value is expected to reach nearly $140bn. By 2025, they will reach $208bn, growing at a CAGR of 10.61%.
Indian Fintech startups are leading the way for adoption of digital payments. Razorpay is one such startup: it serves as a gateway for online payments.
Razorpay allows businesses to accept payments and automate payouts to vendors and employees. In addition, it uses AI and Machine Learning technologies are used to improve business outcomes and devise robust cybersecurity strategies. They rely on transaction analysis to figure out variations, seasonality and determine business cash flows the next year. This data helps the company offer loans based on whatever amount comes out of that model.
2 – Wealth Management
Traditional financial advice relies on human judgment, which is rife with biases and information asymmetries. In truth, you never know if you’re receiving an honest opinion or a sales pitch. As a result, retail investors are increasingly looking for transparent and rational investing recommendations.
Thus, it is not surprising that the coronavirus pandemic has accelerated the rise of a new global phenomenon: “do-it-yourself investing” is increasingly popular, especially among younger generations.
Indian Fintech startups are catering to growing this need.
One startup leading the pack is INDwealth, a full-stack wealth management platform designed for high-net worth individuals. It leverages AI and ML to deliver advice at scale. The software’s ML algorithm, which draws on large pools of data and research, provides unbiased recommendations.
The company’s popularity shows that the financial advisory industry is at the dawn of significant changes that will radically change the investment landscape.
3 – Virtual Assistant
Why hire humans when computers can do the job?
This solution makes sense for many reasons:
- Paying for software is cheaper than paying salaries.
- Sophisticated software rarely makes mistakes.
- While software can periodically bug or malfunction, it is rarely down for prolonged periods of time, contrary to humans who are often sick or on vacation.
As you can imagine, these reasons mean that virtual AI assistants are taking over from humans.
These programs understand natural language voice commands and complete a wide variety of tasks. As AI and ML technologies mature, these programs are able to perform tasks of increasing complexity.
Vymo is an Indian Fintech startup that provides virtual assistants for sales representatives and customer resource management software for field teams. It uses AI and ML technology for geo-tracking, activity-detection, sales metrics and analytics reports, among other things.
Clearly, most business leaders will continue hiring humans to greet customers and provide services where human contact is important. However, we can expect more and more basic office tasks to be handled by AI.
4 – Anti Money Laundering Monitoring
Anti-Money-Laundering (AML) regulations are a very important aspect of all financial activities.
Indeed, financial institutions are required by law to monitor all transactions and report suspicious activity to the competent authorities. This is a task that historically was mainly done manually.
In recent years, AI and ML are automating the process, with great success.
Further, these technologies are capable of crosschecking data and establishing seemingly counterintuitive or unexpected connections.
The unfortunate truth is that humans are unable to do this consistently and on a large scale. Realistically, banks who have tens (if not hundreds) of thousands of clients cannot ask a team of individuals to accurately monitor the daily volume of transactions.
Tookitaki is an Indian Fintech startup that uses AI and ML technology to monitor suspicious activity and prevent false alerts. The software scans all activity and uses specific criteria to identify cases where further investigation is needed. Humans are then called upon to verify the suspicions and take further action.
As the Indian economy continues digitizing, such services will be in greater demand.
5 – Market Intelligence
In our hyper-connected and ultra-competitive globalized world, information is power.
Financial institutions such as private investment funds and large corporations require in-depth market intelligence that will help them identify innovative companies and acquire them before their competitors.
Tracxn is a platform powered by AI and ML that scans billions of data points to facilitate daily deal sourcing, identify M&A targets, perform deal diligence and track emerging themes across industries and markets.
Their software is used by important clients trying to outsmart their competitors.
6 – Back-Office Solutions
AI is particularly useful to automate onboarding and back office operations.
In fact, it is capable of reading documents, analyzing data, recognizing faces and automatically filling forms. ML enters the equation by independently improving processes and refining analysis over time. This frees up humans to perform more productive tasks.
Signzy is a startup that uses AI and ML to offer businesses interactive digital onboarding systems and scalable backend operations. It is notably used for identity verification and anti-money-laundering compliance by retail and corporate banking clients, insurance firms and mutual fund brokerages.
As banks and brokers enter the digital payments and cryptocurrency spheres, Know Your Customer (KYC) regulations and identity verification procedures will become more systematic. Startups such as Signzy will play a very important role in guaranteeing compliance and avoiding fraud.
7 – General Software Solutions
AI and ML software are very useful for helping banks and insurance firms rationalize their daily operations. These firms deal with complex issues that require constant crosschecking of data to ensure risk is minimized, costs are controlled and profits are maximized.
Gradatim is an Indian Fintech startup that supports and automates standard insurance, pension and banking core processes. The platform utilizes AI to enhance digital customer experience through behavioral analysis and nudge engines that grow and scale businesses.
As cloud computing grows, software solutions become more intelligent and interconnected. Many financial institutions still rely on outdated legacy software. The rise of cloud-based AI solutions means that startups such as Gradatim will onboard many important clients looking to modernize their software.
8 – Expense Management
Every business owner will tell you that cost control is one of their highest priorities.
Indian Fintech startups are leveraging AI and ML to optimize expense management.
Fyle is AI-based expense management software. It offers 3 main features: expense tracking of employees, automated compliance and analytics for in-depth insights.
The software has innovative features such as email plugins to extract expenses straight from inboxes and mobile apps for scanning receipts to track travel expenses. AI is used to manage, categorize and store receipts in the cloud and ML is used to help the algorithms improve over time. Integration with other software such as QuickBooks provides clients with a complete package that revolutionizes budgeting.
9 – Credit Scoring
Credit scores are one of the most important metrics of an individual’s or business’ financial life.
Accurate analysis of past and present data is crucial to ensure that banks provide economic agents with the capital they need to invest, while minimizing risks of defaults. One major challenge is analyzing the financial situation of first time borrowers.
Indian Fintech startup CreditVidya is an alternate credit scoring platform which uses AI, Big Data and advanced ML techniques to analyze more than 10,000 data points. This allows he lender to obtain a comprehensive credit score.
This feature is especially useful for analyzing the financial situations of lower-income individuals who need micro-credit to finance relatively small purchases. For example, many of CreditVidya’s clients use the software to establish credit scores for individuals who want to buy a smartphone or equipment to open a very small business. While the loan amounts are small, the risk of default is high.
Software such as CreditVidya enables quick analysis of large sets of data to provide almost immediate conclusions. Traditionally, getting a small personal loan can take up to one week, while small business loans can take up to three months.
Thanks to AI and ML software, clients receive an answer in less than 4 minutes. This means they can apply for a loan and receive the funds the same day.
The revolutionary potential of such technology is simply astonishing.
10 – Checkout Credit Solutions
A recent study published by Cardify.ai revealed that “Buy Now Pay Later” offers increased 197% from Q2 2019 to Q2 2020. This means that consumers want to buy things they can’t immediately afford.
In India, startups are enabling this trend by offering exactly what the consumers want.
However, the country’s lenders face a significant challenge: a large portion of customers do not have the formal documentation to qualify for credit. What’s more, India’s complex geography means that customers living in tier 2 and tier 3 cities are often neglected by credit institutions.
That’s where companies such as Capital Float come in.
These Indian Fintech startups offer checkout credit solutions for consumers who wouldn’t normally obtain credit through traditional institutions. Their technology based on AI and ML quickly analyzes the customer’s situation and underwrites an application in real-time.
Such services mean that digital services will quickly expand beyond India’s major cities, bringing millions of new consumers into the economy.
11 – Payment Collection
Finally, every financial institution is very sensitive to debt collection.
In America, nearly 30% of people have at least one debt in collection. In India, debt collection is also a major problem. For example, 5-10% of the country’s farmers are not repaying their tractor loans on time. With time, and the development of Buy Now Pay Later schemes, Indian borrowers will face the same challenges as their American counterparts.
You may be surprised to learn that the US debt collection industry’s revenue decreased to $11.5 billion in 2018 from $13.5 billion in 2013. However, this is not due to a decrease in consumer debt.
This decreased is explained by rising automation.
In India, India Fintech startups such as CreditMate are using AI and ML to help lenders collect overdue payments from borrowers. Their software allows lenders to upload cases using their API. The platform them offers a host of services: access to a network of collection suppliers, reporting and insights, machine learning and automation, millions of data points and aggregation of cases.
Ultimately, their technology increases collection rates, decreases defaults and lowers operational costs.
Indian Fintech Startups are Revolutionizing Finance
Indian Fintech startups are leaders in AI and ML adoption.
Clearly, they are disrupting the traditional banking sector and democratizing access to financial services.
As the use of AI and ML becomes widespread, the Fourth Industrial Revolution will spread to other major sectors of the Indian economy, creating a more inclusive social environment, driving economic growth and increasing the quality of life of millions of people.