In the prospecting phase, advanced analytics and artificial intelligence (AI) can be used to quantify the extent to which a prospect is inclined to take a commercial loan. This helps lenders qualify their pipeline, so that their RMs are not chasing the proverbial needle in a haystack. An optimal operating model allows RMs to leverage shared services for non-customer-facing activities.
For credit evaluation, AI that processes unstructured data, analyzes it, and presents it concisely enables lenders to make critical decisions. Automated financial spreading provides fast, accurate inputs to analysis and risk ratings. Front-office underwriters are supported by a global team of credit analysts, who perform support tasks that have not been automated.
In the decision stage, machine learning can help validate decisions against past experience. Intelligent routing can direct work to the right person at the right time in line with credit policies and practices. Post-decision due diligence can be accelerated by using AI and machine learning in the know-your-customer process, and by leveraging computer vision as well as augmented reality for real-estate due diligence.
For booking and funding, Lean Six Sigma processes eliminate non-value-add activities, while robotic process automation can help automate data entry. Finally, for portfolio monitoring, AI-enabled analysis allows lenders to analyze relevant company, market, and industry information in real time.