Categories: News

Arya’s Cred AI Advances Credit Underwriting Toward Context-Driven Intelligence

MUMBAI, India and NEW YORK, Feb. 25, 2026 /PRNewswire/ — Underwriting teams have already automated much of the operational grunt work. This progress, though, has largely come from rule-based systems handling repetitive tasks. Underwriters still spend most of their time understanding transaction patterns, and the bank and financial statement analyzers available to them only categorize transactions, not contextualize them.

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This is the gap Cred AI, Arya.ai’s statement analysis platform is built to close. To make better credit risk assessments, underwriters need to know what transactions mean, and not merely what category they fall into. Statements carry significant evidentiary weight: pay stubs can be modified and invoices inflated, but financial behavior, as reflected in bank statements, is far harder to manipulate.

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In corporate underwriting, the same problem takes a different form. Financial statements are often treated as static outputs (ratios computed, numbers compared, exceptions flagged) without interpreting what those numbers represent operationally. Cred AI addresses both dimensions: behavioral context in retail underwriting and operating reality in corporate underwriting.

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Automation accelerates analysis, but it often flattens meaning.

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Automation helped underwriting move faster, but it didn’t help it think better,” said Deekshith Marla, Founder of Arya.ai. “Underwriting is fundamentally a behavioral problem. If you don’t understand why money moves the way it does, or why financial statements change the way they do, no amount of categorization will lead to better credit decisions.”

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Cred AI is designed to help teams make smarter underwriting decisions. It moves underwriting beyond automation by enabling contextual understanding across transactions. This allows underwriters to interpret behavior in retail cases and operating reality in corporate cases.

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Key Differentiators: Cred AI

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  1. Treats statements not as flat records, but as behavioral and operational timelines
  2. Connects signals across time, distinguishing genuine income from artificial inflows
  3. Identifies patterns that showcase financial health and operating quality
  4. Preserves relationships between financial events that traditional analysis discards

Most importantly, Cred AI is powered by Weave, Arya.ai’s orchestration platform. This feature allows teams to interact with statements conversationally. “Teams can ask Cred AI questions such as ‘Forecast the next three months’ cash balance’ and get instant insights. We’ve seen teams catch falsified revenue using citable answers,” said Ritesh Shetty, Product Head, Cred AI.

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Cred AI has already delivered excellent results. In the UK, an SMB-focused lender achieved a 300% increase in underwriting productivity by using Cred AI.

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True productivity gains come when underwriters trust what they’re seeing,” Marla added. “Context removes friction from decision-making. When interpretation is clear, speed follows naturally.”

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As financial institutions continue to invest in AI-driven underwriting, the next phase of innovation will not be defined solely by automation. It will be defined by systems that restore context—systems that understand financial behavior for retail underwriting and financial reality for corporate underwriting.

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Learn more about Cred AI: Statement Analysis for Smarter Underwriting.

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About Arya.ai

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Arya.ai is an Enterprise AI solutions provider helping organizations unlock the power of AI. Under the leadership of its founder, Deekshith Marla, the company bridges the gap between advanced technology and real-world challenges. Its offerings empower enterprises to integrate, manage, and scale AI across functions.

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Photo: https://mma.prnewswire.com/media/2919985/Arya_Cred_AI.jpg
Logo: https://mma.prnewswire.com/media/2620540/5312999/Arya_ai_Logo.jpg 

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View original content:https://www.prnewswire.co.uk/news-releases/aryas-cred-ai-advances-credit-underwriting-toward-context-driven-intelligence-302696806.html

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