The Fintech space in India has seen tremendous growth in the last few years. According to a recent report by Bain by 2026 the fintech sector in India is expected to grow to $350 billion in Enterprise value and will account for nearly 15% of Financial Services market cap. With this, the demand for innovative fintech solutions is also on the rise.
AI-powered risk decisioning platform, Provenir helps fintech companies and other financial services providers make smarter decisions faster by combining the three essential components needed – data, AI, and decisioning – into one unified risk-decisioning solution. Founded in 2004, the company today works with disruptive financial services organizations in more than 50 countries and processes more than 3 billion transactions annually. In an exclusive interview with CXOToday, Mr. Varun Bhalla, Country Manager – India at Provenir, shares his insights on how Provenir helps fintech drive innovation and optimize risk decisioning with the help of Artificial Intelligence in India.
- Tell us about Provenir and how it has grown over the last couple of years.
In a digital-first market, agility and innovation are key. The banking, financial services and insurance (BFSI) industry need purpose-built technology designed to power decisioning innovation across the full customer lifecycle.
We are seeing unprecedented demand for real-time credit decisioning solutions that will enable organizations to innovate faster than ever before, driving the continuous optimization they need to power growth and agility, without increasing risk.
With the unique combination of real-time, on-demand data access, embedded AI and world-class decisioning technology, Provenir provides a cohesive risk ecosystem to enable smarter decisions across identity, fraud, and credit – offering diverse data for deeper insights, auto-optimized decisions, and a continuous feedback loop for constant improvement both at onboarding when assessing risk and monitoring ongoing transactions for fraud.
The company has made significant investments over the past few years to expand into new markets, grow our employee base, and continue providing the leading-edge products our customers need in this digital-first world. These investments resulted in a 190+ percent increase in new customers and a 55 percent SaaS revenue increase in 2021. Demand for our solution is exploding globally so we will continue to invest to serve this market need.
Currently, we work with financial services organizations in more than 50 countries and process more than 3 billion transactions annually.
- Who are some of the customers that Provenir serves and which verticals are they primarily involved in, especially in India?
At Provenir, we work with BFSIs regardless of size – from innovative small business lenders driving job creation and economic development to larger, well-established financial services providers. Along with our AI-powered platform, the Provenir Data Marketplace is a one-stop data hub that offers easy access through a single API to data sources covering open banking, KYC, fraud, credit risk, verification, social media, analytics, auto, affordability and more. We currently have more than 100 data vendors around the world in the Marketplace with about 25 of them providing India- focused data across the above categories.
Lenders can pick and mix data sources that perfectly fit their business needs in a matter of minutes.
For instance, our partnership with Decentro, a full-stack API infrastructure platform provider in the region, enables plug-and-play banking integrations for NBFCs, fintech lenders and banks.
We are also particularly proud of our partnership with AMU Leasing, India’s only woman-led, tech-driven non-bank lending startup. Using our offerings, AMU Leasing has fully automated its loan underwriting to develop an efficient, frictionless ecosystem for leasing, financing and purchasing electric vehicles. We look forward to helping them meet their goal of one million EV disbursements by 2027.
- How can AI-powered risk decisioning play a part in transforming the entire credit risk decisioning process?
AI gives lenders the power to do things that have been out of reach with traditional decisioning capabilities, such as enabling approvals for unbanked consumers, adapting to rapidly changing markets without sacrificing the customer experience, and continuously optimising decisioning across the customer lifecycle.
When lenders use multiple alternative data sources instead of relying on credit scores only, AI will identify the patterns that will optimize decisioning. This allows lenders to expand their customer base without increasing risk. Moving from a rules-based approach to a self-learning AI model also maximizes fraud detection – AI will spot irregularities immediately.
With the insights provided by AI, pricing can also be personalized for each applicant while allowing the lender to maximize profitability and increase its potential customer base.
- What are some of the approaches or strategies that businesses can take to power financial inclusion with alternative data and advanced analytics?
The way lenders handle their credit risk decisioning has changed. The traditional credit score is no longer the only way to evaluate creditworthiness. Today, alternative data enables you to create a more inclusive approach to your credit risk decisioning process.
Over the last few years, the Government of India and RBI have taken several forward-looking measures including the launch of IndiaStack, the dynamic growth of UPI transactions and now increasingly the adoption of Account Aggregators by banks and other regulators, leading to unlocking of a large amount of alternate data which can play a significant role in driving an alternative approach to credit risk decisioning.
Using the right types of alternative data plus advanced analytics or AI allows for a more comprehensive and accurate credit risk picture so lenders can more effectively serve those who would not have qualified using traditional data only. This encourages new players to play crucial roles in providing credit.
- What is the competitive advantage that you have to offer?
Our competitive differentiators are the usability, speed and agility our platform offers. It is the only unified platform combining real-time, on-demand data access, embedded AI and world-class decisioning technology. The Provenir Marketplace makes it easy for customers to access both traditional and alternative data sources and bring that data into their decisioning models.
Our no-code platform solves key challenges that stand between organizations achieving their business goals: reliance on vendors, overworked development teams, and talent shortages. It is business user-friendly with a visual, drag+drop, user interface. Risk, credit and analytics teams can easily make changes and fast integrations, decision-making workflows, and analytics processes. This allows businesses to make changes in minutes and deploy models, connect to data sources and launch products faster.
It’s also cloud-native and cloud-agnostic, meaning we support AWS, Azure, GCP and more. It can automatically scale up or down on demand, adapting to business needs as required.
Provenir was founded in 2004 so we have vast experience dealing with decisioning for a variety of financial services products and use cases, including unsecured loans, consumer durables, two-wheeler and auto financing, SME lending, banking and loan origination, mortgage financing, consumer lending, telco and more.
- Can you tell us about the different ways in which AI can impact the entire customer lifecycle?
Today’s risk decisioning is about evolving beyond the basics. However, truly leveling up decisioning hinges on more data, more automation, more sophisticated processes, and more forward-looking predictions. Doing this is impossible without AI, which goes beyond better decisions and predictability.
For instance, AI models can identify patterns within data and then help lenders decisions using those patterns. This drives growth and performance by enabling lenders to confidently say yes to customers they weren’t able to approve before.
AI also boosts confidence about the risk a credit application poses, which improves accuracy of how to price the credit offered. Lenders can optimise pricing, making offerings more attractive and maximising profitability.
Finally, AI empowers fraud detection, due to its ability to learn from each transaction. As a result, AI can keep pace and anticipate fraud even as methods evolve.
- What are your expansion plans in India? Tell us about the opportunities at Provenir for Indian tech talent.
We plan to continue investing to grow our presence and meet the growing need for our solution not just in India, but South Asia and the rest of the Asia Pacific.
We are also looking to leverage existing tech talents in India to accelerate these efforts. In September, we announced that Provenir India will serve as Global Hub for Technology and Operations, so we are actively recruiting. India may be the largest base outside of the US in a year or two. In less than 9 months of operations, we already have 35 employees in India and are expected to have about 100 employees by the end of FY23.
- What are the trends that we can expect in the next year in the AI-powered risk decisioning space?
The digital lending landscape has been changing rapidly in the country led by new regulatory requirements and increased expectations from customers regarding personalized products available on demand with minimal friction which has forced lenders to take a deep look at their existing credit risk technology platforms.
The IndiaStack including Aadhar, UPI and now Account Aggregator (AA) and Open Credit Enablement Network (OCEN) has made available a lot of data to lenders beyond the traditional sources. To be able to consume these data points and make decisions in real-time, they will require technology systems that are agile, easy to use and can scale rapidly while providing customized offerings to customers.
While lenders are adding new ML-based scorecards in their loan decision-making process, there is an inherent need to control biases and to be able to explain those decisions to both internal and external users. Explainability becomes an important part of optimising the decision-making process and platforms such as Provenir AI that can help understand the ML scorecards become increasingly relevant.