AI-based loan apps are booming in India, but some borrowers are missing out
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(Reuters) – As the founder of a consumer rights non-profit organization in India, Karnav Shah is used to seeing sharp practices and angry customers. But even he was surprised by the sheer volume of complaints against digital lenders in recent years.
While most of the complaints are about unauthorized lending platforms misusing borrowers’ information or harassing them for missed payments, others relate to high interest rates or loan applications that have been denied for no reason, Shah said.
“These are not traditional banks where you can talk to the manager or complain to the head office. There is no transparency and no one to ask for help, ”said Shah, founder of JivanamAsteya.
“It hurts young people to start their lives – a declined loan can result in poor creditworthiness that will later adversely affect major financial events,” he told the Thomson Reuters Foundation.
Hundreds of mobile credit apps have sprung up in India as smartphone usage increased and the government pushed for digitization in banking, with financial technology (fintech) firms rushing to fill the credit access gap.
Unsecured loan apps, which promise quick loans even without creditworthiness or collateral, are criticized for high loan interest rates, short repayment periods, as well as aggressive exploitation methods and misuse of customer data.
At the same time, the use of algorithms to assess the creditworthiness of first-time borrowers disproportionately excludes women and other traditionally marginalized groups, say analysts.
“Credit scoring systems should reduce the subjectivity of loan approvals by reducing the discretion of a loan officer in making credit decisions,” said Shehnaz Ahmed, fintech director at Vidhi Center for Legal Policy in Delhi.
“However, because alternative credit scoring systems use thousands of data points and complex models, they could potentially be used to disguise discriminatory policies and also perpetuate existing forms of discrimination,” she said.
New to credit
Around 1.7 billion people worldwide do not have a bank account, leaving them vulnerable to loan sharks and being excluded from vital government and social benefits that are increasingly being distributed electronically.
Nearly 80% of Indians have a bank account today, in part because of the government’s financial inclusion policies, but the young and poor often lack the formal credit history that lenders use to assess an applicant’s creditworthiness.
Almost a quarter of credit inquiries each month come from people with no credit history, according to TransUnion CIBIL, a credit score company.
Authorities have encouraged the use of AI to create credit scores for so-called new customers, which account for around 60% of motorcycle loans and more than a third of mortgage loans.
Algorithms help assess the creditworthiness of first-time borrowers by scanning their social media footprint, digital payment details, number of contacts and call behavior.
TransUnion CIBIL recently launched an algorithm that “maps the credit data of similar subjects with a credit history and comparable information,” said Harshala Chandorkar, the company’s chief operating officer.
Women made up about 28% of personal borrowers in India last year, up three percentage points from 2014, and have a slightly higher average CIBIL score than men, she said without answering a question about the risk of algorithm discrimination.
CreditVidya, a credit reporting company, uses an artificial intelligence (AI) -based algorithm that taps “over 10,000 data points” to calculate its scores.
“A clear, unambiguous consent screen that articulates what data will be collected and for what purpose it will be presented to the user to obtain consent,” it said.
EarlySalary, which says its mobile credit app has garnered more than 10 million downloads, uses an algorithm that collects text and browsing history, as well as information from social media platforms like Facebook and LinkedIn.
People who don’t have a significant social media presence could be disadvantaged by such techniques, Ahmed said.
“There is always an element of subjectivity in determining creditworthiness. However, this is compounded with alternative credit scoring models that rely on multiple data points to assess creditworthiness, ”she said.
Personal loan apps in India – which are primarily intermediaries connecting borrowers to lending institutions – now fall into a regulatory gray area.
A draft law discussed by the legislature on the protection of personal data with a long delay would contain conditions for the request and storage of personal data as well as penalties for the misuse of this data.
Authorized credit platforms are advised to collect data and publish detailed terms and conditions with the customer’s consent, said Satyam Kumar, a member of the Fintech Association for Consumer Empowerment (FACE) lobby group.
“Regular audits and internal controls of the lending process are carried out to ensure that no discrimination based on gender or religion is carried out manually or through machine analysis,” he said.
The Indian central bank has announced that it will develop a regulatory framework that “supports innovation while ensuring data security, privacy, confidentiality and consumer protection”.
This will help grow the value of digital lending to $ 1 trillion in 2023, according to the Boston Consulting Group.
Digital lending will still move towards historically privileged groups, with credit rating systems in India also lending to men more often than women, said Tarunima Prabhakar, research fellow at Carnegie India.
If an algorithm were to evaluate creditworthiness based on the number of contacts on a phone, it would likely find men more creditworthy, as Indian men have greater social mobility than women.
Women can face loan refusals or higher interest rates.
“There is almost no transparency on how these values are achieved,” she said.
Digital lenders justify the nondisclosure with competitive advantage, but some clarification needs to be made, including explanations when loans are declined, she added.
“If these platforms make it easier for men, but not women, to start small businesses, it could reduce women’s freedom of choice in an already asymmetrical power dynamic,” said Prabhakar.
“In the absence of strong oversight and a lack of institutions, alternative lending can maintain the same arbitrary lending practices of informal credit markets that they seek to resolve.”
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