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Cyber attacks in India have tripled in the last three years, according to data released by CERT-in. Nearly 14,02,809 different cases of cyber security incidents were recorded in 2021 alone.
“The growing instances of cyber fraud are alarming for businesses, especially when digital assets have seen exponential growth in recent years,” said Ranjan R Reddy, founder and CEO of Bureau, a trusted network that provides safety net to businesses solving cyber fraud risks with its AI/ML-powered solution.
Ranjan founded Bureau in 2020 to build a single source of digital trust to counter cyber fraud. In this exclusive interview, he discusses how AI and ML solutions can help tackle the problem of cyber fraud.
AIM: Tell us a bit about ‘Bureau’.
Ranjan: We are the first identity decisioning company that offers a complete, no-code identity and risk orchestration platform for fraud-free customer interactions for the entire customer journey.
Our key differentiators include custom workflows for everything from onboarding, KYC/KYB, and AML to transaction monitoring and a trusted network where each validated customer is added to a growing consortium of merchants’ data that further strengthens the Bureau’s database.
Enabling trust between businesses and consumers is how we deliver value. We started our journey in 2020 and we have since powered several companies across sectors to design their digital user journeys in a secure manner, thereby reducing cyber fraud significantly.
In the process of enabling these trusted financial transactions, we have protected over USD 200 million of commerce from use cases such as mule accounts, synthetic ID fraud, phishing, KYC fraud, fraud rings, UPI fraud, money laundering, collusion, OTP theft, and referral abuse—to name a few. More than 70 fintech, regulated financial institutions, and new-age technology businesses use Bureau today to ensure their customer interactions are friction- and fraud-free.
AIM: How is ‘Bureau’ using AI/ML to tackle cyber fraud risk? Could you share some use cases?
Ranjan: Identity verification is the starting point of any cyber fraud detection, as securing one’s customers’ identity on the platform is the first step in making one’s platform secure. We use AI to assess the trustworthiness of customers by analysing data from various sources, such as phone and email intelligence.
Machine learning is used to build models that can predict the likelihood of a customer committing fraud. We analyse large amounts of data using advanced algorithms to identify patterns and anomalies indicative of identity fraud. Another advantage of using machine learning algorithms is that it helps analyse data with greater accuracy than traditional techniques.
Customer centricity is at the core of any business. One of the critical factors in achieving client satisfaction is by making users’ time hassle-free on platforms. This is where Bureau steps in with one-stop identity verification solutions that integrate multiple-point vendor solutions for capabilities to serve different use cases such as Know-Your-Customer, optical character recognition, AML and PEP, among others.
Our platform comes pre-integrated with all these services, saving our customers’ capital, time, and engineering resources and helping them scale their businesses to brand new heights.
AIM: Could you tell us about your models and the datasets they have been trained on?
Ranjan: Our identity verification and fraud detection models have been trained on billions of data points unique and suitable to the Indian market and have already been validated across a network of clients.
By combining pre-integrated device, persona, phone, email, and behaviour intelligence, a contextual view of a user’s identity and behaviour is formed. Performing an accurate identity verification and pre-empting fraud becomes easier, thereby safeguarding the business from financial and reputational loss.
AIM: What role can AI play in cyber fraud/crime prevention?
Ranjan: AI and ML have the potential to revolutionise the way cyber fraud can be prevented. AI/ML algorithms can detect and prevent malicious activities by analysing data from multiple sources. For example, AI can be used to detect suspicious activity in online payments by recognising patterns of fraudulent behaviour, along with detecting potential phishing attacks. These algorithms also automate the verification process, making it faster and more precise by analysing customers’ behaviours, such as online activity and purchases, to identify any suspicious or fraudulent activity.
We can expect AI to play a significant role in cyber fraud/crime prevention in the future as technology continues to evolve and improve. As AI evolves to more advanced stages and efficiency, and is trained on more data points, it will become better at detecting vulnerable sources and preventing cyber fraud and crime.
Moreover, as organisations become more aware of its benefits, they are likely to adopt the technology to protect their systems and data, thus making it a vital tool in the fight against cyber fraud/crime prevention.
AIM: What are your views on the current cybersecurity landscape in India?
Ranjan: India is one of the biggest marketplaces for digital technology that is rapidly expanding, as evident with the government’s ‘Digital India’ initiative and its vision to make the country a five-trillion-dollar trillion economy in the next few years.
Currently, India has over 1.15 billion mobile users and over 700 million active internet users, creating a vast pool of digitally vulnerable targets for identity fraud. With businesses unlocking new levels of digital transformation, identity fraud threats have become more prominent than ever.
The growing instances of cyber fraud are alarming for businesses, especially when digital assets have seen exponential growth in recent years. Data security and privacy, therefore, should be the top priority for organisations. The ability to protect users from fraud and cyber theft will be a significant competitive advantage and businesses need to invest in a wide spectrum of capabilities that—with a combination of data and technology—proactively thwarts fraud without having to choose between growth and risk.
