Fraud and abuse are constant challenges for online businesses. The digital explosion has brought many complex and cross channel risks to business than ever before. Typically, fraudsters attempt to get past various cross-channel and security protocols with stolen data and credentials obtained through sim swaps, man-in-the-middle attacks, phishing keylogging or password guessing attacks. They can also buy sensitive data from the darknet with your data housed in separate silos or residing with the third-party digital platforms. Apart from that, frauds happen with credit-based financial businesses with deliberate loan delinquency and similar malicious behaviours from some users.
Such instances can create severe financial and reputational damages for companies and, therefore, it is important to get real-time fraud analytics across digital channels. India being one of the largest digital economies in the world, there are many firms launching analytics-based fraud solutions in the market for not just financial companies but across different industries. In this article, we take a look at the top five new-age firms using advanced analytics to fight fraud and business risk.
Founded in 2006, Bengaluru-based Clari5 is considered one of the market leaders in fraud detection and sells its financial crime risk management software product. The company serves Tier-1 banks in 15+ countries and processes data generated by over 10 billion transactions for real-time, cross-channel enterprise fraud management and anti-money laundering. It also has the world’s largest fraud analytics implementation, with 200 million financial accounts at a single site. The firm uses intelligent models based on neural networks, time series and complex analytics to provide insights into fraud and risks.
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In 2011, the company raised Series A funding of $4 million from investment firm JAFCO Asia and also received funding from Microsoft Accelerator. Also In January 2015, the company collaborated with EY to help banks fight enterprise fraud by linking the forensic capability of EY’s fraud investigation and dispute services (FIDS) practise, and Clari5’s cross-channel fraud management to present specialised solutions. Clari5 also partners with Microsoft, RedHat, Cisco and Intel to co-provide real-time fraud management and customer experience solutions to financial institutions.
Hyderabad and Palo Alto-based Simility was founded in 2014. It provides cloud-based and on-premise fraud detection software solutions. The main product is an adaptive fraud prevention solution which delivers enterprise-level performance and scalability. The adaptive fraud solution identifies complex fraud and abuse in real-time by ingesting any type of data – structure, unstructured and third-party data. Together with a complex device history plus new data feed, their product can be operational and provides value in just a few hours without requiring assistance from developers.
It uses machine learning, giving users deep insights on user behaviour. It also uses ML to feed data back into an instant data label for optimal cross-channel and fraud detection capabilities. The rules and models can be easily updated without the need to write a single line of code. It uses the simple user interface that lets data analysts easily configure rules which can then give a 360-degree view of the customer with drill-down analysis, decision workflows and network graphs. In 2018 PayPal Holdings acquired the startup for $120 million in cash. The company had raised around $25 million in funding prior to that also.
Last year, Razorpay acquired Gurugram-based fraud analytics startup Thirdwatch. Today the firm is one of the most prominent Indian startups that leverage AI for e-commerce fraud analytics. On the Razorpay platform, the team captures billions of events each day and uses that data to feed into AI models. This is then used to prevent fraud in digital and e-commerce transactions.
As the payment gateway and as a payment service provider, Thirdwatch assists Razorpay to prevent losses of its merchants when it comes to fraud in e-commerce transactions. Razorpay Thirdwatch has captured 200 plus parameters from e-commerce websites and applications using plugins, SDKs and REST APIs. It uses these parameters to generate over 300 features associated with user behaviour such as location, IP, device, user journey events, historic transactional data, etc. Within milliseconds, the platform can predict whether it is a fraudulent or genuine transaction. If the transaction is found fraudulent, the particular merchant is notified.
Mumbai-based AdvaRisk provides products on fraud prevention, detection, investigation and funds recovery. The early-stage startup raised $700,000 in a seed round led by Sprout Venture Partners, along with participation from SEA Fund.
Founded in 2016 by Vishal Sharma and Rahul Metkar, AdvaRisk has built an AI-powered platform for fraud prevention, detection, and recovery in the corporate loan portfolio of financial institutions. The company said it is working towards becoming the most reputed and trusted solution for banks, NBFCs, and corporates in India.
Its AdvaSmart proprietary monitoring platform highlights actionable credit negative transactions connected to borrowers facilitating early detection of possible frauds. This solution is trusted by major financial institutions in India. Other than that, the firm’s AdvaNPA helps maximise fund recovery by highlighting undisclosed data and unidentified patterns linked to a defaulter by leveraging 600+ data sources. It has led to Rs 20,000+ crs recovery for banks and NBFCs so far, according to the firm.
TrustCheckr was founded in March 2017 by IIM-Lucknow graduate Ramesh and IIM-Calcutta alumnus Praveen Raj. The startup provides cloud-based APIs that enables businesses to identify fraud, fake and bot profiles on their digital platforms using artificial intelligence. The startup is working to help businesses enrich customer data to make key decisions like fraud detection, identity verification, defaulter prediction, and purchase propensity scoring.
For businesses, it provides algorithms to find the TrustScore of the user and eliminate them at the stage of onboarding and improve the sales funnel. Custom AI/ML engines calculate with a ‘trust score’ based on 100+ parameters of a person’s profile such as social profiles, location, education, employment details, interests, purchase, spending and credit history, etc.