CASE STUDY

How we helped a leading mortgage servicer reduce losses with a loan resolution model? 

Sep 28, 2022

Highlights of the Case Study: 

Particulars Description 
Client A US-based non-bank mortgage and loan servicing company struggled with high provisioning, rising bad debts, and multiple loan defaults. 
Business Challenge Our client wanted to run structured queries to access all kinds of loan-related data, asset values, and its borrowers’ profit statements to enable tailor-made loan resolutions. 
Impact Quantzig’s AI-powered loan resolution model segregated the client’s customer base into high, medium, and low categories. The solution created custom loan resolution plans for the client’s customers in each category. 

Game-Changing Solutions for the Mortgage Servicing Industry   

The mortgage servicing industry has been witnessing two significant risks: valuation and business risks. The valuation risk is driven by default risk and integrated risk. In contrast, the business risk comprises legal and compliance risks and negatively impacts the business’s reputation. A group of competent analysts assessed and calculated these risks using a paper-based conventional approach. Acting as a bridge between the lender and borrower can be a high-risk proposition, especially when there is the possibility of defaulting on the loan repayment. In such cases, a sound loan resolution model with a sufficient margin of error can come in handy to loan servicing firms to maintain and manage timely loan resolution.   

Quantzig’s AI-powered loan resolution model enables mortgage servicers to streamline loan servicing flows, automate the risk identification and analysis, and improve the balance sheets. This will also help to reduce provisioning and writing-off of bad debts.    

The Challenges of the Client 

A US-based non-bank mortgage and loan servicing company struggled with high provisioning, rising bad debts, and multiple loan defaults. The client already had a risk and compliance department doing the pre-check before providing loans to its customers. Yet, the client’s default rate was rising, negatively affecting its balance sheet and income statements. This resulted in loss accumulation in the books and led to operational difficulties such as cash crunch and swaying of market confidence.   

The client wanted to run structured queries to access all kinds of loan-related data, conduct a valuation of assets, and get insights into profit statements to gauge the borrowers’ credit standing. This would help them create tailor-made loan resolution plans for specific borrowers. The client thus approached Quantzig to seek our expertise in developing an AI-powered loan resolution model.  

Through Quantzig’s data-first approach, our client wanted to implement a loan resolution model to mitigate loan defaults.

Quantzig’s Loan Resolution Model for Mortgage Servicing Industry 

Quantzig’s data analytics team used several inputs such as the borrowers’ credit standing, the quantum of loans taken, annual installments, and income stream to categorize different borrowers. Our advanced data analytics technologies assessed the short-term and long-term irregularity in mortgage servicing and the possibility of defaulting on the entire loan amount, leaving the client high and dry.   

We then prepared a dashboard that took inputs from our AI-powered loan resolution model and segregated the client base into high, medium, and low categories. Different solutions and packages were created for diverse clients; for example, clients with derived probabilities of 10% or less of defaulting within the next 12 months were offered a special package with no penalties for three months.  Similarly, for borrowers with more than a 10% probability of skipping the installments or defaulting on the loan, a restructuring plan with revised EMIs was created. The customer was put on vigilance until the credit history improved.    

Impact Analysis of Quantzig’s AI-Powered Loan Resolution Model 

Quantzig’s – Interactive Borrower’s Credit Standing Dashboard enabled the client to scan the borrower’s capacity to service the mortgage on time. It also allowed our client to assess and pre-empt the probability of default on the loan repayment and take suitable pre-emptive measures to mitigate defaulting of loans. This helped to improve the lender-borrower relationship and maintain healthy operating margins. As a result of the partnership, the client’s loan default rate dropped significantly. It also helped to reduce provisioning and writing-off of bad debts, leading to a healthier bottom line for our client.    

Loan Resolution Model

Key Outcomes 

Quantzig’s advanced data analytics solution provided the client with complete visibility of the borrower’s financial situation. This helped to create an AI-powered loan resolution model that enabled the categorization of customers based on their credit history. This model can be used to devise tailor-made solutions for each set of customers. The client could thus restructure the loan with revised terms and interest based on the risk category. This helped the client ensure loan repayment and reduced the need for provisioning and writing off bad debts. It also helped to improve the bottom line of all the stakeholders involved.   

Broad Perspective on Advanced Data Analytics Solutions in the BFSI Sector 

Analytics solutions based on the borrower’s data can be utilized by firms in the BFSI sector to judiciously offer loans while having a data-backed score on the repayment and default probability of the borrower. Real-time data can be used to monitor the loan type, quantity, and amounts, and accordingly, a recovery resolution plan can be worked out. A customized data-backed plan would be designed to cater to the borrower’s financial situation and ensure minimal chances of debt defaulting and timely repayment of loans. 

Clear visibility of the prospective borrower’s financials would enable BFSIs to decide whether or not to disburse loans to candidates with adverse credit scores. They can set an optimal margin for such clients to improve their portfolio and thus provide them with an opportunity to strengthen their credit standings and reapply for loans. Quantzig’s AI-Powered Loan Resolution Model can help banking and financial institutions develop customer-centric plans which will emerge as a win-win solution for all the stakeholders involved. 

Key Takeaways 

Our AI-powered loan resolution model enabled the client to get the following insights:  

  • Identify the probability of default in payments based on the previous mortgage servicing history  
  • Categorize clients based on the risk involved – elevated risk clients, moderate risk clients, and healthy clients 
  • Significantly reduce the loan default rate  
  • Minimize provisioning and writing-off of bad debts 
  • Ensure a healthier bottom line for the client 

Request a Demo of this Case Study.

Related Articles:

Big Data Transportation Analytic Solutions Optimized Route Planning for a Banking Client

How Churn Analytics in Banking Helped Identify the Attrition Risks of its Customers?

How Healthcare Data Analytics Enabled Client to Deliver Personalized Plans for its Customers?

Recent Case Studies

Use Cases of Big Data Analytics in Telecom Industry 

Use Cases of Big Data Analytics in Telecom Industry 

Overview of the Telecom Industry:  If you’re ever worked in the telecom industry then you already know the role the telecom companies are playing in facilitating the transfer of information and communication across the globe. While focusing on the role of big...

read more

Industries

Our advanced analytics expertise spans across industries, sectors, and functions, which enables us to deliver robust, agile solutions to all our clients. These are our core competencies, formed through years of experience.

Insights

Our free resources shed light on our extensive expertise and equip you with information to accelerate decision-making, growth, and innovation.

Talk to us
Talk to us