Manners used to make a man, now they make a loan. Online trolling on facebook, twitter and pinterest accounts could affect the chances of getting a loan at 9% interest or 30% interest as against the industry rate of 13-17%.

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N-age online lenders and online credit marketplaces like CreditMantri and BankBazaar.com that have found a clientele in the 25-35 age group do their due diligence on borrowers using not just pay slips and bank account statements but also unorthodox metrics like phone location data, SMS Alerts and social media behavior. As a Home Loan Providers in Mumbai, the artificial intelligence software scans through millions of lines of data to give a personality score, which is the measure of borrower’s reliability.

While online marketplaces like CreditMantri and BankBazaar.com act as facilitators for consumers to access bank loans of competitive rates, app-based lenders tie up with an NBFC to provide loans. “We can look at the history of Google Searches entered, the results of Apps, the websites visited, our algorithms run on sentiment analytics. Emotions like anger and people raging on Twitter do get captured,” said Nikhil Sama, CEO of InstaPaisa.

All these questions such as Does a person live beyond his means? Does he drive drunken, gamble or indulge in other high-risk behavior? The algorithms can spot it all. You live in a world of information overload. Your social media footprint can leave an indelible mark on your credit history.

As a Home Loan Providers in Vashi, such analyses have also made it easy to measure the credit worthiness of non-salaried people like lawyers, consultants and real-estate agents who have a large amount of money in their account but do not have a salaried position. The banks are usually wary of lending money to such players.

“While these people have fat bank accounts, they might not necessarily get loans because they are non-salaried. So we look at mobile usage pattern, GPS location and SMS alerts. We can also verify PAN, Aadhaar database, date of birth and use of their registered mobile phone number. We look at traditional data sets before non-traditional metrics,” said Sama.

Online lenders consider an applicant’s Facebook follower and LinkedIn connections. “How many likes or comments you get for what you post, how long you have used this medium; all this information gets fed into our systems add a black box decision algorithm takes a final call on lending. We just want to make sure you are a real person with a credible profile.” said Sami adding.

As a Home Loan Providers in Navi Mumbai, the deep access third parties have to user data certainly seems invasive, but at some point we have all signed away the information while installing apps and subscribing to services. Does it mean some lender could be remotely scanned the contents of your phone – maybe texts from a sweetheart?

“Just like Ola, Uber, Swiggy, other mobile apps request permission before accessing mobile data, we also get the consumer’s permission to access mobile content. Our algorithms don’t read or scan personal messages. The only SMSes that would get picked up are the transaction alerts from banks and e-wallet. Our systems’ artificial intelligence picks up this data, analyses it and then comes to a decision. Data does not get stored with us and is used only to arrive at a decision,” said Sekhar.