Credit bureaus in India, including CIBIL, Equifax, Experian, and CRIF Highmark, are playing a crucial role in driving changes in the lending space and financial services sector. These agencies provide detailed credit reports and scores for individuals, and they are undergoing a significant digital transformation. To predict customer behavior and lending patterns, credit bureaus are investing in advanced technologies and practices, such as AI/ML, data analytics, and blockchain, to make faster credit decisions and add value to their clients.
Pinkesh P Ambavat, the CIO and IT Director of CRIF India, shared insights into the credit bureau market in India and the role of technological innovation. CRIF Highmark, headquartered in Mumbai, claims to be India's first full-service credit bureau, offering comprehensive credit information for all borrower segments, including retail consumers, MSMEs, commercial borrowers, and microfinance borrowers.
The credit industry in India has witnessed rapid evolution over the past decade, with a shift in consumer mindset from a savings-focused and debt-averse country to a more consumption-focused, leveraged economy. Unsecured lending has experienced growth, especially with smaller ticket sizes. The volume of consumer inquiries for personal loans and credit cards has significantly increased, while inquiries for loans against property and home loans have remained unchanged or slightly decreased. Digital transformation has disrupted lending, making it possible to approve loans within minutes through a few touches and clicks on a smartphone. Lenders are constantly innovating with the latest technologies to enhance customer experience and convenience. Those who fail to adopt digital acquisition may face challenges in the future.
The Covid-19 pandemic has had a major impact on financial institutions, and individual borrowers and lenders are expected to adapt to the new normal. To ease the financial burden on borrowers, the Reserve Bank of India (RBI) announced debt servicing relief using a moratorium policy. Credit bureaus had to make changes to their scoring models to comply with RBI regulations and ensure that individuals' creditworthiness was not affected by the ongoing pandemic. Despite the challenges posed by the pandemic, there has been a gradual increase in the number of inquiries made by customers, indicating significant growth potential for credit bureaus.
Credit bureaus in India face several challenges, particularly in the online lending segment. They need access to alternative data sources to assess the creditworthiness of borrowers who may not have a formal credit history. Fintech companies are using AI to create alternate lending data scores for the significant portion of the Indian population that lacks credit scores. Analytics play a crucial role in gaining market insights and building products tailored to customer needs. Blockchain technology can be used to update customer data in credit bureaus in real-time, ensuring accurate and up-to-date information. Cybersecurity is another challenge that credit bureaus face, and they prioritize the use of the latest security tools and industry practices to protect customer data.
As the CIO of CRIF India, Pinkesh P Ambavat is responsible for driving digital transformation through emerging enterprise technologies and strategic initiatives. He assists CRIF in providing innovative product solutions related to open banking, anti-fraud measures, and digital banking business lines. Ambavat leads various initiatives to deliver high-performance solutions by capitalizing on cutting-edge technologies. He also oversees overall operations, infrastructure, security, and applications, with cross-cultural engagements across India and Asia.
One significant moment in Ambavat's career was the implementation of machine learning in the customer matching algorithm at CRIF. With the increasing volume and variety of data, traditional analytics methods were unable to keep up with the demand. Machine learning models provided deep insights and understanding needed to improve credit decision models and assess risks accurately. Machine learning algorithms integrate real-time data trends and human decision-making, offering advantages over human judgment or traditional statistical models. Ambavat emphasizes the importance of squeezing every ounce of information from different sources and using improved algorithms. The objective is to enhance the efficiency of the credit scoring model and further improve the digital strategy. CRIF is working on creating partnerships for alternative sources of data to identify new parameters for credit scoring and enhance scoring mechanisms. Alternative data plays a vital role in improving credit scores. Robotic Process Automation (RPA) is being implemented in various business processes to automate and standardize repeat tasks. RPA programs increase flexibility, scalability, and operational efficiency while reducing the risk of errors. CRIF has automated repetitive requests in the product support teams, allowing them to focus on innovative and challenging tasks. Custom data analysis reports are also being developed to provide analytical solutions to new clients, addressing their specific business problems. Credit bureaus in India are witnessing significant growth and undergoing digital transformation. They are leveraging technologies like AI/ML, data analytics, and blockchain to improve customer experience, make faster credit decisions, and add value to their clients. Challenges such as sourcing credit score data, cybersecurity, and adapting to the post-pandemic landscape are being addressed through innovative solutions and advanced technologies.