How banks can jump-start loan automation at minimal cost: Report-as-a-Service (RaaS)
How banks can jump-start loan automation at minimal cost: Report-as-a-Service (RaaS)
Top priority for banks around the world is prioritizing the digital transformation of end-to-end credit journeys, including the customer experience and supporting credit processes. This is because credit is at the heart of most customer relationships, and digitizing it offers significant advantages to banks and customers alike as successful transformations enhance revenue growth and achieve significant cost savings. For traditional banks, the average “time to decision” for small business and corporate lending is between four and five weeks. As financial technology advances, these times will soon seem as unacceptably antiquated as having to go to your branch to withdraw money from your account. A number of banks around the world have fully embraced the digital-lending revolution, some have even brought “time to yes” down to five minutes, and time to cash to less than 24 hours.
In this series, we take a look at how loan processing automation can impact banks today and explore ways that it can be started at minimal cost.
Faster credit decisions, improved customer experience
One large European bank increased win rates by a third and average margins by over 50 percent as a result of slashing its time to yes on small and medium enterprise (SME) lending from 20 days to less than ten minutes, far outpacing the competition.
Digitization is becoming the norm for retail credit processes but this doesn’t apply to commercial lending. Even as personal-loan applications can now be submitted with a few swipes on a mobile phone, and time to cash can be as short as a few minutes, many SME business loans still use manual and paper-based loan approval procedures that now seem out of step with a digitized world. As a result, they have slower decision times than what many customers want, and an internal data management problem that creates more work for bankers and causes opacity for both management and external examiners alike.
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Because commercial loans can range in size and complexity, manual underwriting methods using spreadsheets are still used to underwrite credit for businesses. Mortgage lending is more complex due to regulatory constraints, yet banks in many developed markets have managed to digitize large parts of the mortgage journey. Banks can consider utilizing Report-as-a-Service (RaaS) that allows for a simple reporting solution to this part of the lending requirement. Credit risk reports relevant to business outcomes delivered at faster turnarounds enable loan officers to focus on relationship building, improving the customer experience and allow for greater cross-selling opportunities.
Lower cost and an improved secure risk profile
With traditional manual, paper-based loan underwriting methods, lenders often struggle to see what exposures are in the portfolio and to see how these exposures change over time. All lenders have policy-based risk appetite tolerances and most set appropriate risk-based portfolio limits to guide their loan officers.
Do you want to find out how to leverage machine learning to improve your bank's risk assessment of commercial loans? Schedule a call with us here.
A powerful rationale for automating the loan process via RaaS rests with the improved data integrity, data lineage, and overall lowering of cost. In traditional systems, data integrity is compromised when several diverse systems are used to store the same data. The amount of keying and rekeying is multiplied and data is stored in sub-optimal systems. When conditions such as this exist, lenders spend considerable time and resources reconciling their portfolio data before they can usefully analyze it. Several weeks can elapse before an accurate financial picture emerges.
The benefit to the accurate measurement of a loan portfolio in terms of capital usage must not be underestimated. Overstating risk weighted assets on your balance sheet has a substantial direct cost to it. RaaS allows banks to automate a key stage of the loan origination process which helps ensure that risk data is subject to robust governance and control. Further, automating to deliver key business insights through a powerful financial reporting tool can add significant value as well.
Source: moodysanalytics.com