The financial services industry has undergone significant changes over the years, driven by a variety of factors. Changes in regulatory requirements, an evolving competitive landscape, emerging customer preferences, and an outlook on future trends have all sparked these adaptations. Notably, digital transformation has emerged as a key driver for change in the finance sector. It is not only seen as an efficiency enhancer but also as a means to secure a competitive advantage.
Artificial intelligence (AI) is now ushering in another transformative era for the financial services sector, and one of its most notable applications is AI-powered lending solutions. These innovative systems operate autonomously, relying on sophisticated algorithms and machine learning to assess credit risk and determine loan eligibility, among other critical factors. By harnessing the capabilities of AI, financial institutions can realize multiple benefits, including expedited decision-making, more precise evaluations of borrowers’ creditworthiness, elevated customer service quality, and enhanced loan pricing strategies. The role of AI in digital lending will take on greater importance, as the sector is expected to reach a market value of 350 billion US dollars by the end of 2023, as per a report by Statista.
As a result, various opportunities have emerged within the Indian fintech industry, fundamentally altering the dynamics of lending and borrowing. The traditional loan acquisition process was often characterized by overwhelming paperwork, extensive follow-up and approval procedures, and extended turnaround times for loan disbursement. However, the advent of cutting-edge AI-driven technologies has reshaped this landscape, rendering the process entirely paperless and remarkably efficient. Borrowers can now access funds within hours rather than days, ushering in the era of digital lending businesses. These fintech firms specialize in providing rapid financial solutions to borrowers, marking a significant departure from the conventional lending process.
Role of AI in digital lending
Artificial intelligence has gained significant traction in the loan approval realm, offering valuable support to lenders in enhancing their decision-making. AI-driven systems possess the capability to swiftly and precisely analyze extensive datasets, uncovering hidden patterns that might elude human observation. This proficiency empowers lenders to more comprehensively evaluate a borrower’s creditworthiness and ascertain their likelihood of repaying the loan promptly. Moreover, AI streamlines aspects of the loan approval procedure, such as document verification and background checks, thereby diminishing the need for manual intervention and expediting the overall process. Consequently, borrowers benefit from expedited approvals.
Additionally, AI-based systems excel in fraud detection, surpassing human capabilities, which aids lenders in safeguarding against potential losses arising from fraudulent activities. By integrating AI into their loan approval workflows, lenders can curtail operational expenses while simultaneously enhancing precision and efficiency.
Some ways in which BFSI organizations can leverage AI in digital lending are:
- Faster customer onboarding: Establishing a favorable initial impression hinges on the efficiency of client onboarding. The traditional lending systems heavily leaned on human networking, a dependency that exerted influence not only on the speed of operations but also on their accuracy and, ultimately, their outcomes. Nevertheless, AI-driven platforms offer a solution to streamline the KYC (Know Your Customer) processes for companies operating in the BFSI sector.
The adoption of intelligent data extraction engines like OCR, coupled with AI-enabled auto-population of KYC forms, ensures expeditious customer onboarding. In unison, these technologies simplify the landscape of regulatory compliance, eradicate human errors, automate repetitive tasks, and contribute to substantial time and cost savings.
- Enhanced credit risk assessment: Financial institutions extend loans contingent on the creditworthiness of potential borrowers, which is traditionally gauged through their credit score. Nonetheless, a substantial segment of applicants often faces loan rejections due to their feeble credit histories. In this context, artificial intelligence platforms possess the capability to identify risk profiles and assess an individual’s repayment potential using criteria beyond their credit score. These platforms can generate a comprehensive credit assessment for a customer based on their online transactions and activities.
AI-powered lending technologies meticulously scrutinize all pertinent document information, align it with the loan prerequisites, and provide valuable insights that empower lenders to make more judicious decisions concerning a borrower’s creditworthiness. Following these AI-driven processes, if the borrower proves to be creditworthy, lenders can expedite the disbursement of funds.
- Reduced lending cycles: The conventional procedures for loan approval and fund disbursement were laborious and resource-intensive. Every aspect of the process relied on manual intervention, often stretching the timeline for final approval and disbursement to several days or even weeks. This prolonged turnaround time frequently resulted in missed opportunities within the market for companies. Nevertheless, the integration of AI technology presents an opportunity for lenders to dramatically reduce loan processing time.
All stages of loan processing entail a substantial volume of repetitive tasks that consume extensive time. AI in loan processing mitigates the overall time dedicated to these mundane processes by facilitating automation throughout the lending cycle. Consequently, the adoption of AI empowers lenders to optimize their operations and significantly compress the lending cycle timeline.
- Controlling fraudulent activity: Artificial intelligence offers a potent tool for the detection and mitigation of fraudulent activities within the realm of loans. AI-powered solutions excel in swiftly and accurately scrutinizing vast datasets, equipping lenders with the capability to discern anomalous patterns indicative of potential fraud. For instance, AI algorithms can identify suspicious behaviors, such as repeated loan applications from the same individual or IP address.
AI-driven solutions assist lenders in pinpointing prospective borrowers who exhibit characteristics suggestive of loan default, achieved through an in-depth analysis of their credit history and other pertinent financial data. Moreover, AI-based systems can be deployed to real-time monitoring of existing loans, vigilantly watching for signs of fraud or delinquency. Leveraging the capabilities of AI, lenders can enhance their ability to effectively identify and thwart fraudulent loan activity, all while ensuring that those in genuine need of credit can still access it.
Catalysts for AI innovations in the BFSI sector
- The surge in Big Data: The banking industry has undergone a significant transformation owing to the explosion in availability of data. Changing customer expectations have led to more digital interactions with banks. In addition to traditional structured data like transactional records, organizations now amass substantial volumes of unstructured data from customer service, social media platforms, emails, text and voice messages, images, and videos. Leveraging this wealth of big data, lenders are increasingly capable of delivering highly personalized services. They use a comprehensive view of the customer’s interactions with the brand, encompassing personal information, transaction history, and social media engagement, to make informed decisions.
- Advancements in infrastructure and cloud technology: The proliferation of cloud technology, coupled with the availability of powerful computing resources and infrastructure, enables swift and cost-effective processing of large datasets, enhancing scalability and efficiency. This favorable environment has rendered banks more poised than ever to harness the potential of AI.
- Regulatory imperatives: Banks operate under strict regulatory norms, necessitating the timely and accurate submission of reports to meet their regulatory obligations. The process of regulatory compliance involves gathering data from diverse sources and systems. AI-driven solutions offer an avenue to address some of the challenges in today’s financial systems by automating data collection processes, enhancing decision-making speed and quality, and fortifying the organization’s readiness to fulfill regulatory compliance obligations. The continued evolution of AI promises to revolutionize both the front and back-office operations of financial institutions. This transformation will also necessitate adjustments to longstanding regulations and significant changes to the structure of global financial markets. This shift presents an opportunity for compliance teams to strategically invest in new technologies to position banks for a more future-ready state.
- Intense competition: Banks are engaged in perpetual competition with industry peers and, more recently, with FinTech companies to deliver top-notch services to their clientele. Technology has emerged as a key differentiator in this landscape as organizations leverage cutting-edge technologies to harness their vast pool of data. Consequently, banks are increasingly using AI powered tools to optimize existing service offerings, introduce new products to the market, and provide customers with more personalized experiences.
AI in digital lending: A boon for MSMEs in India and expanded credit access
Fintech companies have emerged as transformative forces in the micro-credit landscape of the country. Empowered by cutting-edge technologies such as Artificial Intelligence (AI), Machine Learning (ML), and Big Data, these fintech firms are orchestrating a substantial evolution in micro-lending practices. At the core of this transformation lies the concept of a data-driven digital footprint, where modern fintech models are constructing a resilient digital lending ecosystem to bridge the credit gap for micro-entrepreneurs. Various studies indicate that the microfinance sector in India has the potential to grow at a CAGR of 40% by 2025.
User-generated data is being collated from numerous sources, including bank accounts, e-shopping patterns, GST returns, lifestyle indicators like ride-sharing usage and entertainment preferences, and various mobile applications used in daily life. Whenever a micro-entrepreneur engages in a digital transaction, be it a sale or a purchase, a trace of that transaction is meticulously recorded. For instance, invoice data from digital purchases is swiftly uploaded to the GST portal for tax reporting. As consumers and small businesses increasingly embrace digital transactions, their digital footprints expand, yielding copious data that can be analyzed to discern patterns and glean actionable insights. AI plays a pivotal role in this process, adeptly handling complex and unstructured data to construct innovative workflows and inform decision-making with efficiency.
The prevailing trend in expanding credit access to the vast and underserved segments of society is characterized by digitization and automation, along with cooperative ventures between credit bureaus and diverse fintech companies. Through collaborative models that boast scalability and accessibility, digital lending is undergoing a transformative evolution that is being driven by technology and supported by data, reaching even the most marginalized people. Fintech companies are dedicated to reshaping microfinance landscape, ensuring that both urban and rural MSMEs enjoy unfettered access to credit, thereby contributing to India’s aspiration of becoming an inclusive nation.
Technology and its continued impact on the digital lending industry
The significance of artificial intelligence in the BFSI sector and online lending is huge. It possesses the capability to enhance consumer experiences through the simplification of KYC procedures, accelerate loan processes by significantly reducing turn-around time (TAT), and enhance the overall safety and ease of lending for financial institutions. A survey conducted by IIFL FinTech forecasts that the digital lending market in India will reach an astonishing USD 515 billion by the end of 2023. Consequently, the market’s prospects appear highly favorable in the foreseeable future.
Describing the transformative impact of artificial intelligence on the banking and online lending sectors is not an exaggeration, and this influence is set to persist as additional application areas for adoption emerge. AI has not only streamlined loan procedures but has also elevated customer experiences, rendering the lending process more secure and user-friendly for financial institutions while granting banks a competitive edge. As the usage of AI is slated to surge in the forthcoming years, it is certain that digital lending will firmly establish itself as a fundamental component of the financial landscape, playing a pivotal role in streamlining loan processes and enhancing the overall customer experience.