Financial and alternative financial lending generates economic benefits for an enterprise needing funding to continue its operations or even expand its business. The alternative lending market in the US alone made transactions worth approximately 74 billion USD in 2020. In exchange for managing their risk, lending companies make profits and create shareholder value.
Financing companies, both large and small, often use tools that help them manage the lending process. A more closely suited tool to its business operations processes can help the financier with better underwriting, timely approvals, faster decision making, and fewer unpredicted losses. Financiers are always looking for tools that help them better the quality of their portfolio and deliver exceptional customer satisfaction.
Drawing parallels from other industries, customers today have high expectations. However, financiers today use systems that contain manual processes. This manual intervention often leads to several process bottlenecks, delayed decision making, more wait for the customers, and internal data challenges that prevent them from harvesting insights.
In this post, we see the ways automation can streamline several parts of the loan origination process and help financiers be more agile and customer savvy.
Automating customer data collection
Manual customer data collection can lead to inconsistent data and duplication of efforts while entering it into lending systems. Customer-facing portals can help plug customer data into the financier’s lending systems. In addition, business rules can help automate the next step based on the data entered, differentiating between applications that ready for approval right away and those that need more information and documentation.
More sophisticated lending systems also integrate data from other sources, such as credit systems. This integration is beneficial for more complex commercial borrowing, where financiers need to understand the customer’s existing financial health. These insights can help financiers make better-informed lending decisions that, in turn, create better value for their investors and better manage risks of defaulting.
Automating creditworthiness
Post the customer data collection, the next step is spreading the financial data to estimate the borrowers’ credit worthiness. Today’s loan origination systems can connect to the customer’s accounting and tax systems that facilitate the electronic exchange of data. This exchange does away with the inconsistencies and errors or manual data entry and lets the system pre-screen the customer and provide an in-principal decision in minutes.
Loan processes often need certified financial documents by an accounting body that has verified their authenticity. However, the loan origination system can group a customer under evaluation with a specific set of customers based on their current financial data and assign them a worthiness score.
This data-driven decision-making can help the financier accelerate its decision-making and get a real-time view of its risk exposure. In addition, this rapid initial scoring gives analysts more time to run deeper analyses and uncover any hidden risks or gains in the customer’s business operations.
Automating credit application and decisioning
Once the analysis is complete and a credit appetite is determined, the next step is to present this analysis for credit application and decisioning. For many financiers, this is again a manual exercise. Several pieces of paper must be presented in a specific format extending the approval time.
Several loan origination systems seamlessly integrate with systems or applications that lenders already possess. However, many of them require proper integration to exchange data seamlessly. They can use the data and information stored in the origination system to mirror a lender’s paper-based forms to conduct its decision-making analysis.
While automated decision-making is widespread in the retail credit space, this is still uncommon in commercial borrowing. While commercial lending still contains an element of human judgment, the loan processing can be highly automated. With the proliferation of mobile applications, the time for decision-making reduces further.
Automating monitoring covenants
Once the loan is processed, the asset still needs monitoring. The risk needs monitoring periodically for any covenants and specific conditions. However, monitoring the asset and tracking the covenants can be automated. A system well integrated with third-party data sources, the client’s financial systems, the financier’s CRM, and other relevant 3rd party sources can automate covenant monitoring.
This automation can reduce the total cost of ownership and maintenance of the asset and ensures its future value remains as high as possible. In addition, the automation pushes any red flags to the financier. It can even assess market conditions to determine the impact on an asset’s value in the near term.
Automating risk monitoring
Banks and financial institutions have already taken significant steps in automating risk monitoring. It would be a travesty not to take advantage of this know-how and implement this in lending.
Typically, with manual underwriting processes and paper-based systems, financiers cannot fully understand their risk exposure and how it changes over time. As a result, most underwriting officers follow a rules-based approach to estimating risk.
Automating risk monitoring and exposure also depends on the integrity of data generated over the borrowing process. In a manual process environment, financiers often spend inordinate amounts of time and effort to consolidate this data. In addition, they need to verify its authenticity before assessing their risk exposure. This delay highlights why data integrity in a loan origination system is essential. And how automating data collection at each step is vital in accurately determining risk and its impact.
Final thoughts
While the banking and financial institutions remain pioneers in technology adoption and automation, lending remain laggards in this space. Many financiers usually own a mix of commercial-off-the-shelf (COTS) and custom applications that handle loan origination processes. However, not all of them seamlessly integrate breaking data flow and decisioning process. Moreover, when components change or replace, others may need to be re-written to make them work with newer ones.
Automating loan origination can help financiers seamlessly collect and process customer data across all platforms and devices. These solutions also enable financiers to improve time to value, eliminate bottlenecks that prevent them from chasing stretch goals, and reduce technology costs through each phase of the process.
