The global lending marketplace is growing rapidly, from USD 10.4 trillion in 2023 and is expected to reach USD 21 trillion by 2033. This rapid expansion is fuelled not only by rising demand but also by the growing accessibility of credit through digital lending platforms and online channels.
With more players entering the market and the rising demand, customer expectations regarding speed, transparency, and affordability are climbing sharply. In this environment, it is crucial to reduce loan processing time and lending costs to stay competitive and grow. Infosys BPM offers a range of BPM services tailored for the financial services sector, which can help enterprises achieve streamlined processes to deliver faster approvals, cut operational overheads, and build stronger customer relationships.
challenges in loan processing
Despite the rapid growth of lending, loan processing remains fraught with inefficiencies.
- Manual process and siloed systems: Even today, those following traditional loan management have multiple stages where staff manually check, transfer, or reconcile information. These fragmented systems create duplicated operations, where data is entered and re-entered across siloed platforms, increasing the risk of human error and slowing down workflows.
- Regulatory compliance: Financial institutions operate under strict regulatory norms designed to protect borrowers. Although the regulations are essential, they require repeated checks and duplication of documentation, which drives up compliance costs and extends loan processing time.
- Verification error: Manual verification of credit details and documents can lead to high error rates, requiring repeated checks and corrections. This adds to the delay in loan processing.
- Delayed onboarding and servicing: The loan origination process is usually highly labour-intensive and prone to errors such as incorrect information or missing documentation. These issues may add a full day per loan to review and rectify mistakes, in addition to risking regulatory penalties.
efficiency in loan processing
Processing loans faster and at a lower cost is possible by rethinking loan workflows and embracing digital tools.
reducing loan processing time
- Complete digitisation of loan origination: Moving from manual, paper-based processes to digital loan origination allows customers to speed up documentation online safely and securely, reducing delays caused by physical paperwork. Technology that enables the automated validation of data and e-signatures can minimise loan approval time.
- AI and data-driven decision-making: AI in lending results in faster credit scoring, fraud detection, and risk evaluation. From automated underwriting to real-time risk assessments, AI-powered loan processing can reduce bottlenecks while still ensuring accuracy.
- Integration through APIs: Application Programming Interfaces (APIs) connect lenders directly to third-party services such as credit bureaus, identity verification systems, and payment networks. Integrating APIs in loan processing helps in real-time credit decision-making, eliminating repetitive checks across departments. It provides instant access to borrower data, drastically reducing processing time.
- Automated customer interactions: Virtual assistants and chat-based tools can be the first line of customer interaction to address routine queries, provide instant updates and even offer step-by-step guidance through the process. Agentic AI technology saves staff time and adds transparency to the process, without replacing human interactions in complex cases.
Lowering loan processing costs
- Cloud-based loan management systems: Cloud-based loan management systems enable businesses to reduce IT infrastructure costs, boost scalability and lower maintenance overheads. Cloud-based models also offer the option to pay only for the capacity used, thereby helping to lower loan processing costs.
- Process standardisation: Siloed systems across branches can create duplication of effort and compliance issues. Hence, by standardising workflows and introducing centralised monitoring, lenders can streamline tasks and reduce rework, keeping costs under control while improving audit readiness.
- Predictive analysis for early risk-detection: Defaults and Non-Performing Assets (NPAs) drive up costs in lending. However, predictive analytics embedded in loan processing can identify high-risk borrowers early in the cycle. This enables businesses to take preventive measures early on. AI-led predictive analysis helps reduce long-term losses and stabilises operational costs.
- Ecosystem partnerships: Instead of building every capability in-house, financial institutions can partner with technology providers, data aggregators, and compliance services. This ecosystem partnership model enables shared infrastructure and lowers overheads, particularly for smaller institutions aiming to remain competitive.
Emerging trends in loan processing
Besides the current solutions focusing on digitisation, automation, and process standardisation, new technologies are emerging to transform loan processing even further.
- Blockchain in lending: Blockchain provides a distributed, tamper-proof ledger that improves transparency and reduces reliance on intermediaries. By offering a single source of truth, it eliminates duplicate records and costly reconciliations.
- Smart contracts for faster execution: Smart contracts powered by blockchain technology can ensure transparency through simultaneous execution of the contract for both parties. This enables the fulfilment of the obligations of both the lender and the borrower.
- Agentic AI for real-time decision making: Moving beyond traditional automation, agentic AI can act independently within set boundaries to process tasks such as loan assessments, fraud checks, and borrower communication in real time.
Together, these emerging technologies not only ensure cost and time savings but also provide a more secure, transparent, and customer-centric loan processing experience.
