Digital Loan Processing: What’s New for Banks?

Digital Lending has benefits that are enhanced by a data-first outlook and implementation of modernized systems

For many years now, a number of financial startups have successfully set up neo banks. Where digital banking solutions are a threat to traditional banking, quick digitization safeguards them. The digital experience, low costs on transactions, and built in tools to polish financial habits are addictive to new age consumers.


Banks need to sustain customer-centric digital experiences at a newly-evolved speed and scale. Especially, where artificial intelligence (AI), Blockchain, and Cloud technologies make up a majority of banking infrastructure.


A flexible and scalable platform for digital lending could result in raising loan volumes while reducing operational costs, improving underwriting, and lowering fraud rates too.


What Readies Banks for New Age Digital Lending?


Before bringing Big Data Analytics to the forefront, it is necessary for banks to harness the power of one truly transformative technology – a Data Lake.


Using Data Lakes, Banks edge closer towards automation for loan generation. Banks can highlight common data points such as credit score, household income, and demographics and create in-house data-driven processes for loan sanctioning.


Furthermore, a Data Lake transforms Financial Entities infrastructure to promote automated regulatory reporting, data-first credit monitoring, and predictive analytics for loan defaults.


Benefits of Digital Lending Systems for Banks Today


Loan origination can be automated with digital lending systems, saving valuable time and redirecting human resources from redundant tasks of data entry and verification. Data aggregation can be automated for relationship managers (RMs) to access relevant data and bring risk-monitoring scores at their fingertips.


Data cleansing can be automated with AI-ML-powered systems. Data Synchronization can keep redundant data out of the way. And, data subscriptions can deliver the time-sensitive data to analysts, researchers, and c-suites.


Faster Digital Lending with Online Applications


Online applications are offered by every bank today. It saves time and helps with better decisions. Credit decisions based on borrower's past information is sourced directly from external credit monitoring entities, helping lenders sanction loans quicker and reduce turnaround time.


Automated Data Collection for Pre-qualification


Automation helps in streamlining of disparate system data and provides reliable and consistent dataflow for any stage of the loan origination process Customer management, Credit Analysis, Credit Presentation, Portfolio Risk Management, Covenant Monitoring, Decision, and Approval), accelerates the process, while also offering audit benefits.


Reliable Underwriting with Intelligent Decisioning


Manual credit underwriting processes are being replaced by digital underwriting not only due to optimized access to borrower data. AI/ML-powered intelligent decisioning is a driving factor too. Here, loan origination systems speed up approval processes while providing a quicker and reliable digital lending environment.


Easy Data Integrations using Cloud Technology


Cloud technology is making services available to a wider range of clients, simplifying applications, and improving connectivity between multiple systems and data sources. The benefits of cloud-based loan management data integration are undisputed: quick implementation, lower capital and operational costs, easier data integration, and seamless data delivery to multiple decision-making teams.


Optimized Activity Tracking and Reporting


Once a borrower receives the funds, loan origination ends. However, the next process of credit monitoring requires data and borrower information to be formatted, stored safely, and passed into a synchronized reporting software. In order to achieve this, the tracking and reporting modules should have easy access to lending data.


A loan origination system streamlines data flow of borrower information by easily integrating with data lakes. The information stored by the system can be easily accesses for loan monitoring and research purposes.