Bank becomes a future-ready profitable lender
To better serve and retain its loyal customers, a bank transformed lending practices—saving $20M and avoiding $2B in exposure.
The hardest part about applying for a business loan is the waiting. The longer and more manual that process is, the more costly and resource-intensive it becomes for the lender.
That’s why one of the largest consumer and commercial banking groups in North America decided to upgrade its commercial lending business processes.
The bank’s leaders believed that with faster, more efficient underwriting and approval processes they could generate enough savings to fund new loans for existing customers at a record pace. For example, the bank’s average end-to-end turnaround time for commercial loans was 53 days—well below top quartile performance.
To better serve its largest customers, the bank also needed to provide a more personal customer experience. A key element of its strategy would involve bringing in new digital capabilities that would connect and harmonize its many lending processes while driving better experiences and continuous innovation.
Making its lending process faster and easier would be critical for the bank to survive and keep its loyal customers.
Working with Accenture, the bank developed a flexible roadmap for its lending transformation. To create an intelligent banking operating model, the team used SynOps, a cloud-enabled platform that orchestrates the optimal combination of technology and human ingenuity. The new model introduced new ways of working. It also provided access to data and insights that could improve the speed and quality of decisions.
Importantly, the new operating model included a new cloud-based commercial lending solution that brought together the bank’s core processes on a single platform and made data available in one central place. SynOps identified transactional tasks that could be performed by more than 60 automation bots, eliminating many of the bank’s point solutions and manual-based processes. This freed up the bank’s lending experts to spend more time interacting with customers.
New analytics measure the strength and profitability of the bank’s loan portfolio, prioritize forecast volumes and boost customer retention by predicting loan pre-closure propensity.
A new AI-based intelligent spreading solution powered by machine learning and optical character recognition gathers documentation and digitizes processes to speed up credit decisions.
A quality control framework improves controls and compliance by helping the bank fulfill requirements for quality assurance demands.
Increase in commercial lending productivity and 26% drop in approval times (from 53 to 39 days).
3X faster processing of loans under US$350,000.
in bottom-line savings.
In addition, predictive analytics helped the bank identify pre-closure loan exposure of US$2 billion. With these types of time and cost savings, relationship managers can deliver better customer experiences and retain the most valuable customers.
The new quality control framework has also enhanced the bank’s controls and compliance by improving business outcomes and insights. Compliance adherence climbed from 93% to 100%. And increased visibility of process gaps and bottlenecks helped the team address more than 99% of the bank’s compliance-fulfillment backlog.
In the future, as the organization continues to lend money more efficiently and in ways that leave customers happier, its technology transformation will produce even more savings and even better customer and employee experiences. Those are benefits it can take to the bank.