Consumers, all around the world, are now borrowing more than ever. The need for a better lifestyle, meet the luxury aspirations, and improve quality of life – has motivated consumers to borrow readily. This has evidently given rise to the need for faster, effective and secure credit scoring. AI-based algorithms are the perfect answer to fraud risks, and the need for delivering a  better borrowing experience. 

Since all borrowers cannot behave and think the same way – their creditworthiness cannot be determined with a fixed set of parameters. Your scoring system has to be widespread and must consider a 360-degree data collection and analysis. 

#1 Telecom Score 

Telecom data has good correlation with credit risk estimation of possible default in the future it must include the features of: 

• Subscription (profile, duration, products, bundling)
• Usage (call pattern, mobile device, P2P/micro payments, device installment)
• Billing (prepaid top-up pattern, VAS services, top-up credit, postpaid overdue, suspension & recovery)
• Other (location, overseas roaming, VOC pattern, financial app downloads)

#2 Social Score 

Data available through smart phones based on browsing history and personality analysis help in determining social score. This can take into account: 

• Demographics Data
•  Content Data
•  Network Data
•  SMS Messages

#3 Financial Score 

Some of the factors affecting credit include late payments, oldest accounts, credit usage, hard enquiries, total balance and available credit

• Wallet or Mobile Money
•  Banks/MFI
•  Credit Bureau

#4 Transaction Score 

Transaction Score is calculated based on purchases made on different channels

• E-commerce
•  Purchase History
•  POS Transactions
•  Merchant Payments

#5 KYC Score 

Score that is calculated based on how well the customer can be identified and verified

• Field Verification and Validation
•  Face Match & Liveness Detection

#6 Info Score 

What do you own and how much you earn governs your Info Score which is calculated based on your earnings and utility expenses

• Utilities Data usage– Energy, Gas
• Asset Data – Ownership, Rental
• Employment – Income / Salary

If the lending system takes into account these prominent scoring metrics, they are covered against the risks of frauds upto a high extent. Effective credit scoring can help safeguard against impersonation frauds, instant validation, false salary validation, instant data extraction, etc. 

All these metrics together reflect the score in the form of credit score cards. A higher credit score means a lower risk of default. Applicants with a good payback history are often likely to have a good credit score. 

It is Recommended for Applicants to Keep A Track of Their Credit Record

Credit scores and reports can be easily calculated for individuals. Keeping a good record of the credit score helps boost the confidence of the applicant. This can easily be compared with the instant and automated credit report card generated by AI-powered solutions. These can be mapped for a smooth transition and approvals for loan origination. 

Automated Credit scoring systems are fast empowering banks, telecoms, Wallet service providers, and consumer lenders towards instant and accurate credit scoring and faster than ever loan processing.