TO REDUCE CREDIT RISK, TAKE ADVANTAGE OF THE LATEST LENDING INNOVATIONS

TO REDUCE CREDIT RISK, TAKE ADVANTAGE OF THE LATEST LENDING INNOVATIONS

The defi Team Automation, Compliance, defi INSIGHT, Fraud, Instant Integrations, New Customers, Technology

TO REDUCE CREDIT RISK, TAKE ADVANTAGE OF THE LATEST LENDING INNOVATIONS

All lenders seek to reduce credit risk within their portfolios. While some still use manual risk assessment tools, portfolio management spreadsheets, and even good old-fashioned intuition to guide decision-making, savvy lenders are looking to technology and automation as a solution. These days, consumer lenders have begun to adopt cloud-based lending software to assess risk. Such cutting-edge solutions have made mitigating risk more reliable while also increasing efficiency.

With a wide range of risk assessment, management, and mitigation capabilities, lending software allows consumer lenders to easily identify potential risks to make well-informed decisions. Whether looking for new lending software or simply wanting to manage risk more effectively, there are a few important risk reduction capabilities lenders should consider.

How Lenders Can Reduce Credit Risk 

A number of obstacles present themselves when looking at ways to reduce credit risk. First, the risk environment is constantly changing. Fraudsters seek to come up with new schemes to avoid detection. Compliance regulations frequently change as well, so lenders must keep abreast of these new rules in order to manage the risk to their portfolios.

Additionally, lenders today offer a greater and more varied range of loans, making managing risk more complex. Having a diverse portfolio opens many new lending opportunities, but it also increases the risk for the lender. To deal with these greater risks, lenders require a system that allows them to identify individual risk factors for each type of loan and applicant while carefully managing this risk throughout the loan’s lifecycle. 

Upgrading to a cloud-based software platform that can manage many different types of loans will help lenders reduce credit risk. In particular, three capabilities within modern lending software helps lenders more effectively reduce risk, which include: 

  1. Fraud analytics helps detect and mitigate fraudulent activity while assisting with predictions of future fraudulent behavior.
  2. Automated verification services largely eliminate human error while streamlining the application process.
  3. Machine learning algorithms that automate the application process provide greater accuracy and speed.

Let’s take a closer look at how each of these three capabilities help reduce credit risk. 

Innovations in Fraud Analytics 

There are numerous forms that fraud takes in the loan application process, including:  

  • Income: Applicants sometimes create fake pay stubs that appear very realistic. This allows them to be approved for loans for which they’re not qualified, based on their actual income. 
  • Employment: Employment history can also be altered, with phone numbers tied to fictitious employers or references. Sometimes fraudsters even use phony email addresses and dummy websites. 
  • Collateral inflation: Another method of fraud involves inflating the value of a vehicle or other collateral used to achieve more favorable loan terms. While shrewd lenders usually spot this, such situations sometimes get overlooked when this involves a manual process.
  • Identity: Identity theft is another big problem for the consumer lending industry. While an applicant might look legitimate based on the data entered and documents provided, this type of fraud can be difficult to catch. This is largely due to the fact scammers are increasingly employing technology to counter lenders’ techniques for spotting this.  

With this vast potential for fraud these days, often supported by their own technology, lenders need to utilize the most current approaches to stay ahead of the fraudsters. To reduce credit risk, cloud-based lending software should integrate easily with multiple third-party providers whose operations are supported by fraud analytics. With this capability built into their systems, lenders can more easily identify such scams during the application process.  

Rather than relying on loan officers to guess whether an application is genuine, fraud analytics providers collect and mine data to identify hidden patterns that indicate possible fraud. For example, innovative fraud detection software helps identify patterns in fake phone numbers, automatically flagging these in future applications. This allows a lenders’ personnel to identify fraudsters, even if they’ve never seen a specific scam before. By keeping a detailed record of all known factors related to these attempts at fraud, loan officers can more easily identify suspicious information or activity within an application.

Cutting-Edge Verification Services Help Lenders Reduce Risk 

Fraud analytics and verification services go hand in hand to reduce credit risk. The best lending solutions will have: 

  • Synthetic identity detection capabilities that compare personal information provided on the application to reliable credit databases.
  • Cloud-based resources that allow lenders to store and access vast amounts of information to make better lending decisions.  
  • Income verification from secure and confidential sources.
  • Alternative credit data and trended credit data filters that give lenders a clearer picture as to how risky an application actually is, going beyond traditional credit scores, income reports, or employment history to increase the difficulty of faking this data.
  • The ability to verify and refute employment history. 
  • Accurate collateral valuations that are history-adjusted, with vehicle valuations also integrated with Black Book and Kelley Blue Book. 

To reduce credit risk, lenders can’t simply take applicants at their word. Advanced verification services like these help lenders separate honest borrowers from potential fraudsters

Using Machine Learning to Automate and Manage Portfolios 

Reducing credit risk involves more than just detecting fraud and verifying information, however. It also requires that lenders manage their applications and portfolios effectively. For example, if an account is delinquent, lenders must take immediate action to prevent the loan from defaulting. Automation and machine learning enables lenders to take these necessary steps more quickly and efficiently. 

Risk management automation works by: 

  • Assessing how risky it would be to lend to a specific applicant, which then allows lenders to eliminate the introduction of high-risk borrowers into their loan portfolios.
  • Structuring loans based on past and projected risk management data.  
  • Prioritizing applications with lower risk and high return potential.
  • Automatically approving very low-risk applicants. 
  • Sending mid-range-scoring applicants to loan officers for manual assessment when approval or denial isn’t straightforward. 
  • Automating the delinquency recovery and collections process to reduce financial risk. 
  • Using machine learning algorithms to identify patterns and create new decision rules based on these trends. 

Not only does this improve the efficiency of lenders’ loan approval, origination, and management processes, but it also gives loan officers more time to focus on tasks that require a personal touch. 

Is Your Risk Management System as Effective as It Could Be? 

One of the most important ways to reduce credit risk is for consumer lenders to leverage the wealth of data sources available to them. This is one place where cloud computing offers a real advantage, as it allows lenders to safely store and retrieve vast amounts of data efficiently. However, collecting, managing, and analyzing this data is a time-consuming process, which is why lenders now need cloud-based software that automates risk management to stay competitive. 

To reduce risk throughout a loan’s lifecycle, the best loan origination systems and loan servicing software use automated decision-making and verification services along with machine learning algorithms and fraud analytics. Having all these capabilities in one platform that’s based in the cloud helps eliminate information silos. Using this interconnected data, consumer lenders can better assess risk and take the most important steps to protect both their business and borrowers from preventable threats and vulnerabilities.

Getting Started

defi SOLUTIONS offers a total solution for a lender’s complete loan or lease lifecycle. Partnering with captives, banks, credit unions, and finance companies, defi’s market-leading solution helps lenders exceed borrower expectations. From digital engagement through the complete lending process, defi sets new standards for flexibility, configurability, and scalability in originations and servicing (by your experts or ours). defi SOLUTIONS has the backing of Warburg Pincus, Bain Capital Ventures, and Fiserv. If you are looking for more information on how to reduce credit risk in your business, please visit www.defisolutions.com

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