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Home Credit China Cuts Risk by 25 Percent on Thin File Loans

FICO

Home Credit , a global non-bank consumer lender, has successfully reduced its credit risk while maintaining loan volumes and keeping approval rates steady by incorporating the FICO® Score X Data to optimize its loan process in China. They are one of our most sophisticated clients in terms of advanced analytics.”.

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Lendingkart Lends Credit Risk Tech To FI

PYMNTS

16) said Lendingkart will offer its credit risk assessment technology to banks and other alt-lenders starting in 2017. “We plan to offer our analytics technology to other NBFCs [non-banking financial companies] and financial institutions sometime in 2017,” the executive said in an interview with Livemint.

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Merchant-facing regulation: What merchants need to know in 2025

The Payments Association

The FCA’s final guidance, issued in April 2025, outlines “reasonable procedures,” including fraud risk assessments, internal controls, staff training, and governance oversight. Next steps/action required: Conduct a comprehensive fraud risk assessment across all channels and partners.

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Understanding Risk Management Strategies as a PayFac

Stax

PayFacs handle risk assessment, underwriting, settling of funds, compliance, and chargebacks which exposes them to greater potential risks. Major risk factors for PayFacs include fraudulent transactions, merchant credit risk, regulatory compliance, and operational risks.

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Proactive Credit Management in a Fluid Tariff Environment

Trade Credit & Liquidity Management

(Photo by Christine Roy on Unsplash ) This is reflected in reports from major banks like Wells Fargo and JPMorgan Chase, which have not observed companies making large withdrawals from credit lines—a sharp contrast to the early days of the Covid-19 crisis, when businesses rushed to secure cash.

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Filtering customers in the lending process with automation

Nanonets

Traditional underwriting processes may not assess creditworthiness accurately for a borrower who derives income from non-traditional sources. Filtering customers based on income and savings, in addition to credit scores, can be a stronger predictor of mortgage risk. Verify KYC/AML based on geography.

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Case Study: J.P. Morgan integrates Slope’s AI-powered platform to offer instant B2B financing at point of sale

Tearsheet

Morgan’s financial strength and Slope’s innovative approach to credit risk assessment and monitoring. All of these features are powered by our AI-driven underwriting and risk-scoring infrastructure, which is built in-house from the ground up. The partnership brings together J.P. By combining J.P.

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