All right-minded businesses like to explore engagement opportunities with customers where the chances of getting the returns on their investment in terms of time and effort are the brightest.
Pre-qualifying helps ascertain that a lead is likely to purchase if moved into the sales process.
It ensures that a lead is interested in what the business has to offer and prevents wasted time and resources that could have been better spent to generate revenue.
This is the reason why all loan origination exercises begin with pre-qualifying the leads. Potential borrowers are asked to submit details like employment information, income details, loan repayment history, bank and tax statements to the lenders. The lender then attempts to understand the unique challenges of the borrower and the purpose for which they are raising the loan.
The detailed documents submitted allow the executive to estimate the chances of loan repayment in the future. It is only after ascertaining that a borrower will be able to repay the loan efficiently, that he is approved for loan disbursement.
Pre-qualification benefits lenders as it uses individual credit data to match potential customers to the right loan products. This allows direct sales teams to tailor their pitch to engage prospects.
The good ‘ol Feet-on-Street (FOS) approach or relationship based selling allows sales executives to propose the best solutions for the needs of the borrower, enhancing the overall profitability of the business.
Limitations of the Feet-on-Street approach in Getting Pre-Qualified Leads into the Lending Lifecycle
We are in the middle of a massive boom in the credit markets. The demand for credit has shot to the roof in recent times. Consequently, financial lending companies are faced with demands to process a large number of loan applications on an everyday basis. They find it challenging to keep such large numbers of applicants engaged and close deals at speed due to manual processing approaches they use.
Direct Sales teams at lending companies take time to judge the worthiness of a query. A lot of paperwork and manual verifications are required for ascertaining an applicant’s eligibility for a loan.
Tedious manual data entry processes deviate their focus away from catering to customer’s unique needs. Even in the case of loan rejection, the sales team may not have access to data about the acceptance or rejection of a query.
This limits their understanding of methods to approach a potential lead.
How AI & ML Powered Finezza Software is Replacing the Good ‘ol Feet-on-Street?
We are all witnesses to the rapid digitization wave that has consumed the lending landscape in the country. More and more financial lending institutions are choosing digital systems and loan management software to ease processing and disbursement functions.
Improved web-based functionalities have overpowered face-to-face communication significantly. Across industries and verticals, organisations have started to appreciate the impact of AI & ML on their operations, and lending businesses are no exception.
The unique set of tools included in Finezza optimize the loan origination process helping direct sales team work more efficiently to generate a pipeline of qualified leads for a variety of financial products.
The Mobile Ecosystem
AI is helping financial lending institutions comply with KYC requirements in an improved fashion. There is no need to bear the bulk of the paper load in the form of physical KYC forms. Customers can quickly fill out the forms online and save resources. Thanks to its user-friendly mobile ecosystem explicitly designed for FOS (feet-on-street), Finezza allows users to enter relevant data into the system on their own, saving time that direct sales teams earlier spent in performing data entry operations. The Feet-on-Street app can easily track the application status, calculate EMIs and automate follow ups improving sales volumes and margins for lenders.
Document Recognition & Data Extraction
With Finezza integrated into the lending system, Feet-On-Street agents can upload all the necessary documents in a single go without wasting time uploading them one by one. Powered by AI and ML capabilities, this proprietary software tool sorts the documents to be processed.
Using deep learning algorithms, this tool can identify eight types of documents like Aadhaar, PAN, cancelled cheques, ITR acknowledgement, photographs of the establishment, balance sheet, GST returns among others.
Furthermore, the data extraction feature uses Object Detection techniques. It extracts relevant fields pre-OCR instead of applying OCR to the entire document as done traditionally.
It also crops the image, thus reducing the area of interest to small bits of text.
Functionalities like image recognition and data extraction come tied to some of the decisioning verticals.
FOS can access a particular case and easily explain the reasons, in cases of rejection, to the applicant in a seamless manner. Overall, Finezza promises simpler validation and a richer output by omitting out post-processing headaches.
Intelligent Credit Scoring
Traditional financial lending companies counted solely on a particular credit score to assess the repayment abilities of loan applicants. However, adopting of AI tech has brought along alternate credit scoring methods such as metadata analysis through a smartphone using Machine Learning.
This ensures a superior insight into consumer behaviour and their spending patterns, thereby giving an estimate of the person’s ability to repay the loan. The turnaround time of loan processing is shortened due to quicker decision-making.
Finezza, in particular, uses an AI-enabled credit rating process to assess a loan applicant’s creditworthiness based on real-time inputs from four credit bureaus, Thanks to its KYC documentation & analysis, bank statement analysis and 360° loan eligibility assessment features, it is a one-stop shop for wholesome credit assessment of an applicant.
Centralized Centralized LOS & LMS
Loan Origination & Management Systems have a seamless connection. Finezza makes sure that the data is centrally accessible, thus making it simpler for direct sales team members to know the real-time application status of the borrower. Feet on the street can also be privy to the analysis conducted for each of these applications, and develop a deeper understanding of the kind of clients they need to target.
Conclusion
AI and ML-powered solutions for lending lifecycle management enhance the loan origination process at various levels. Not only does it accelerate the entire process of loan disbursal but also optimizes it, making it free from error. They help lenders with flawless decision-making.
Finezza uses its exclusive AI technology to offer customized analytical solutions. It helps minimize the lead-to-loan TAT and promises better ROIs for lending businesses.
Want to give Finezza a go? Get in touch with us to see what Finezza can do for you!
[…] the simplest of tasks like extracting Address from an Aadhaar Card – it also takes away the focus of Feet-on-street (FOS) reps from doing something much more important like engaging the […]