5 ways Fintech Startups are Preventing Loan Defaults

By inflooens on January 30, 2021

five ways fintech startups are preventing loan defaults

 

Lending is a risky business. Whether your business is large or small, managing cash flow is a challenging task. When Mortgage lending companies are giving a loan to any customer, they are taking on a huge risk. Even though loan applicants undergo thorough eligibility checks, there is a chance that the lender might not be able to recover the money if the customer faces unemployment and/or loss of income. According to the Mortgage Bankers Association's (MBA) National Delinquency Survey, the delinquency rate for mortgage loans on one-to-four-unit residential properties decreased to a seasonally adjusted rate of 7.65 percent of all loans outstanding at the end of the third quarter of 2020. Nonetheless, the 90-day and over delinquency rate continued to grow and reached its highest level since the second quarter of 2010.

mortgage delinquency rates

Figure 1: Mortgage Delinquency Rates Image Source: https://www.economy.com/economicview/indicator/USA_mbadel/AFAD9D17-EC2C-443D-89D3-EDC09EBFEFA7/United-States-MBA-Delinquency-Rates

Further, due to the current pandemic situation, there is an increase in job losses resulting in reduced revenues. Customers are forced to seek external financial support. This calls for a robust system to achieve timely recovery and avoid delinquencies. At this point, the collection of debt through automation comes into the picture. FinTech startups are leveraging a large amount of available customer data to automate the whole process of Mortgage CRM and Mortgage Origination. Let’s look at the 5 ways in which Fintech startups are proving to be a game-changer for preventing loan defaults.

Machine Learning in Mortgage CRM for Debt Recovery

The process of lending money and recovery of debt has been made easy by Machine Learning (ML). FinTech startups use ML to streamline the process of lending. The credit models used can deal with every stage of lending, for example preparing credit score, credit history, eligibility for loan/ loan amount, risk management, and debt collection. ML also helps to comply with regulatory rules and guiding principles. Therefore, ML is a huge advantage for lenders dealing with the repercussion of loan defaults. At the same time, it is beneficial for customers too, by providing the current tech-savvy customers speedy access to loans with a negligible amount of paperwork. inflooens is the smartest mortgage CRM that uses AI and ML to streamline the mortgage lifecycle.

Bulk Automated Messages to Stay Connected with Customers

Automation can be used to send reminders and messages to borrowers for payment of loan installments. Lenders can opt to include debt amount, date of payment, website link for secure online payment options in the messages. These messages can be sent via text or email depending on the customer’s channel of choice. Automated messages not only help in reducing delinquency rates but also help in improving customer service. Fintech startups are including the feature of automated messaging in mortgage CRM platforms for ease of business. inflooens Mortgage CRM allows automated follow-ups and transparency throughout the mortgage process.

Automated Tools Helps to Analyze Customer Payment Cycles

FinTech startups have developed mortgage CRM platforms that use technology to provide lenders information about the best time to connect with the customers and the most appropriate channels of communication. This makes it easy for lenders to recover debts by contacting customers at the right place and right time. Further, the technology also helps to pin-point irregular payment cycles and identify risky customers. Machine Learning can use advanced algorithms to predict delinquency and help in mitigating lending risk. inflooens provides a reliable and efficient mortgage origination platform that helps in reducing risk and enhancing customer experience.

Customers can select preferred language

Many mortgage lenders operate worldwide or have a varied customer base in their given locations. This can lead to language barriers and difficulty in communication. With Automated Customer Service portals like IVR or applications, Fintech startups are enabling customers to customize their experience. They can select their preferred language which eases the communication process. This in turn makes the collection process smoother and also reduces the cost of following up with the customers over and over again. Nonperforming loans are not only a hassle to deal with, but they are also costly because they need an investment of resources to service without returns.

cost of loan servicing

Image 2: Cost of loan servicing Image Source: https://www.nationalmortgagenews.com/news/fintech-startup-launches-ai-platform-for-mortgage-loss-mitigation

Personalized payments plans

The FinTech startups help the customers build their payment plans. Here, the customers can set their debt payment dates which are, say, within the week of their salary day, without any human intervention. The customers can also opt for lower monthly payments if they happen to lose a job. Since technology is customer-centric, the customers can take control of their finances. Even cases of forbearance and cash-out refinancing are made easier to deal with by FinTech Startups. We have discussed both these topics at length in our previous blogs. inflooens is the best mortgage CRM that provides information at your fingertips and makes the personalization of payment plans faster and simpler.

Conclusion

The FinTech startups are developing automated tools that extract, corroborate, and process all amorphous data and give systematic reports to reduce operating costs, increase accuracy, and reduces default levels in a fully verifiable and transparent way. They provide tools that are proving to be a win-win situation for mortgage lenders as well as borrowers resulting in increased efficiency, enhanced customer experience, reduced loan defaults, and eased debt recovery. The digital debt-recovery solutions are being used to streamline their lending businesses and collection processes.


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