Automation has become the latest trend in the lending industry with the promise to streamline the loan lifecycle, improve employee productivity, and make customers happy. With banks and NBFCs dealing with an ever-expanding universe of applications and tools, the need of the hour is a single straight-through-processing platform to automate and transform the complete lending process.
Gone are the days when bank employees needed to manually compare data across multiple spreadsheets and documents to verify loan information or spot missing/ incorrect information. Straight-through processing, especially when combined with AI and ML, takes the manual work out of lending processes, helps personalise customer interactions, and can shape the lending industry well into the future. Lending firms can reduce the overall loan processing time – almost by 80% – with minimal human intervention.
What is straight-through processing?
Straight-through processing, or STP, is the automation of the entire lending lifecycle from application to disbursement. This automation makes it easier for employees to process a greater number of loans and do so faster, freeing up highly skilled banking staff to focus on more complex cases. With STP, lending firms get end-to-end digital transactions, from data capture at the point of application right through to fulfilment and settlement of the loan.
How straight-through processing helps lending firms
Slow lending processes mean delayed approvals, high cost to serve, and the bank’s inability to meet customer expectations for accelerated and frictionless experiences. Many lending firms continue to use manual and paper-based loan procedures that slowdown decision times, increase workload, and impact transparency for employees and customers. STP ensures data integrity, improves regulatory compliance, identifies anomalies in credit data, and alerts lenders to potential fraud or poor data. Let’s look at different stages of the lending lifecycle to understand STP’s impact.
From data storage, lineage, retrieval, and portfolio insights, using spreadsheets to underwrite credit is error-prone and cumbersome. STP maintains data uniformity, eliminates duplicate data, and saves time for the lending firm and its customers. Firms can increase the quality of the loan portfolio and deliver customer satisfaction. They can leverage APIs to facilitate onboarding of prospect and customer data directly on the loan origination platform. Based on the data received, lenders can pick the loan applications that can be processed from those that need more documentation.
Several types of advanced loan origination software are already in play, helping lenders streamline processes and give their analysts more time to complete risk assessment. This involves forecasting models, ratio analysis, data interpretation, and measuring the financial risk of the borrower and their repayment ability. With STP, customer management and credit analysis tools can be combined for compounded benefits.
Presentation & Decisioning
With accurate and near real-time data and higher efficiency, STP helps reduce decisioning time. Lenders can get a better idea of their lending appetite based on financial statements, ratio analysis, performing projected scenarios, and undertaking a risk rating, They no longer need to collate separate, yet related, pieces of information. They can use the data and pre-configured document templates already stored in the lending platform to conduct their analysis.
After loan origination, lenders need to manage the asset and monitor risks. However, this proves to be a challenge for banks due to the absence of a standardized process to collect financial data and track customers efficiently, especially with reliance on manual tools. STP maintains sanctity of data and assuring all stakeholders that correct information is being collected.
With traditional manual, paper-based underwriting, lending firms can encounter blind spots related to risks and exposures. The situation is made complex with varying risk appetites and dynamic risk-based portfolio limits. But designing rules for portfolio limits can be quite a task. With automation in the loan origination stage, risk data can be better managed and applied.
The future of loan processing
The lending landscape is definitely changing, spurred on by the emergence of increasingly sophisticated tools and software. Traditional lenders are adopting automation in their lending lifecycle, as they recognise the need to be more efficient, productive, and responsive, with higher levels of service.
Straight-through processing in lending is highlighting the value of credit data, helping lenders improve risk assessment, regulatory compliance, and cost containment. Combined with the adoption of open banking, STP will enable enhanced levels of compliant automation and personalisation in lending. However, the challenge for lending firms will be to bridge the gap between their existing systems and platforms and the future-fit customer centric systems and features they have now.