Orchestrating Loan Management Systems and Lifecycle Workflows

The economic climate of the past few years has put increasing pressure on the lending industry. With heightened interest rates aimed at curbing inflation, financial institutions have less margin for error. They must innovate if they want to accelerate the loan cycle without increasing risks.

But these organizations are at a technical disadvantage. Most loan management solutions leave a lot to be desired. Brittle, inflexible systems act as roadblocks to agility, yet replacing legacy systems is costly.

Financial services organizations don’t have to resign themselves to this status quo. With the right automation and process orchestration tools, you can streamline your loan management systems without having to rip and replace. This post will discuss some of the current limitations of loan management software, benefits of automation, and tips for optimizing your loan management system workflows.

[Curious how emerging technologies like AI will affect the broader financial services market? Find out with the The AI Handbook for Financial Services Leaders.]

Financial services organizations are heavily burdened by legacy software. Many loan management systems use outdated technology. This often leaves loan management divisions missing out on critical efficiencies brought about by newer technologies like artificial intelligence or RPA. 

Beyond that, financial services organizations often use a patchwork of systems to accomplish daily operations. This leads to a heavy IT maintenance and security workload. Plus, the disjointed nature of these systems creates silos that make data less readily accessible to decision-makers. This slows the loan approval process and increases the chance of human error. Unfortunately, replacing these systems can be costly (and in some cases, nearly impossible due to data retention compliance issues).

Loan management is replete with repetitive tasks. Often, employees must manually enter data to document things like personal and financial information in various systems. Beyond that, employees are often asked to spend additional time setting up payment schedules and processing payments in the loan servicing departments. These monotonous tasks are ripe for automation.

As mentioned before, organizations have little margin for error around loan risks. Tightened monetary policies have made it even more important than ever to reduce investment risk. But currently, most organizations have to manually locate information like credit histories, background check results, and bank statements. This further delays loan processing, reducing customer satisfaction and tying up human resources from higher value work. Plus, manual processes increase the possibility of human error, which can be extremely costly.

Each of the previous points add to wait times for all different types of loans. For many, these loans are critical to their financial or personal goals, whether they're looking for auto loans, mortgages, or small business loans. Unfortunately, this can make the process extremely painful, leading to low customer satisfaction. If your competition can speed up the lending process and boost customer experience, then you may start to lose ground in the market.

Financial services organizations shoulder a heavy compliance burden. And regulations change frequently. Guidelines get updated, new laws get passed, and auditors renew focus on specific areas. Because loan management systems are often inflexible without a lot of customization, this can make keeping up with compliance more challenging and costly than necessary.

Financial organizations don’t have to remain stuck with these problems. A good AI process platform can allow you to connect disparate systems and introduce new technology without retiring your old software (or adding heavily to IT maintenance workload). Process automation enables you to orchestrate processes, pass work between digital workers and humans as needed, and rapidly adapt to new changes. 

How does it work? Let’s look at an example of a customer filling out a loan application:

• The customer enters information into a form. The form was created using AI in just a few seconds (and tweaked using low-code).

• The customer uploads important supporting documents. Using AI document processing, the system automatically classifies critical documents according to type (financial statements, application forms, etc.). From there, the solution extracts critical information from the documents to use in the verification process.

• The system runs automated verification checks against external databases. This can be done via API connections or even robotic process automation (RPA) bots entering information automatically.

• Once this information has been verified and collected, it gets routed to a separate team to make a final decision. The system can even automatically draft an email using generative AI, then allow a customer service representative to review it before sending.

Now that you know how automation works, how can it help your organization?

• Improved efficiency: Efficiency is the most immediate benefit of automation. From data entry to compliance checks, automation ensures faster decision-making, loan approvals, and customer communications. 

• Reduced errors and delays: Human-run processes are prone to errors. Offloading repetitive tasks to automation technologies leads to fewer mistakes like typos or review oversights. This can both speed up the process and further reduce costly rework.

• Greater agility: These platforms enhance operational flexibility by automating repetitive tasks, freeing up staff for higher value work. This can both increase productivity and unleash innovation. Additionally, the use of low-code technologies enables development teams to change applications and workflows to meet changing market conditions or new compliance requirements. 

• Better customer experience: With faster processing times, fewer errors, and greater agility, customers get a much smoother loan approval process. Plus, automation can allow for greater transparency. For example, automating status updates to customers allows them to gain greater insight into the loan process, instilling confidence and trust.

The answer to these issues lies in AI process platforms. These platforms enable you to layer new capabilities on top of your existing technology without having to undertake costly, complex rip-and-replace projects. 

Beyond this, data fabric technology solves the disjointed data silo challenge. Using data fabric, organizations can create a 360-degree view of their enterprise data in a unified data model. Plus, data fabric keeps information synced across data sources—combined with RPA, that includes data sources that don’t have API capabilities. The result? Easier access to enterprise data without having to migrate data or add significantly to your maintenance workload.

A good AI process platform will include low-code development capabilities. Low-code development can be up to 90% faster than traditional, high-code software development. By creating new applications fast, you can quickly roll out the latest technologies for greater efficiency, boosting your competitive edge. Plus, as compliance regulations evolve, you can respond in kind (and often faster than your competition).

Automation brings enormous benefits to loan management. From boosting operational efficiency to minimizing risk to improving customer satisfaction, automation can be key for improving your competitive advantage. With the right process automation platform in place, you’ll have the flexibility to meet the pressures of the moment by speeding up loan decisions and minimizing risk at the same time. 

Of course, no automation conversation would be complete without discussing the huge impact of artificial intelligence. Find out how AI will affect lending with this American Banker whitepaper, Decoding the Future of Lending: AI’s Capability to Transform the Landscape.