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Novel Patterns Wins 'Best Agentic AI Application' at ET Enterprise AI Awards 2026 for Bringing Governed AI Reasoning to LendingRecognition highlights DecisionOS’s approach to agentic AI in lending-where AI reasons across financial evidence and policy while keeping consequential decisions explainable, auditable and human-controlled | ||
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Bengaluru, Karnataka, India Novel Patterns, an AI-native financial intelligence company built for financial institutions, has won the ‘Best Agentic AI Application’ award at the 2nd edition of the ET Enterprise AI Awards 2026.
Ashutosh Singh, CFO & Head of Products, Novel Patterns, receives the ‘Best Agentic AI Application’ award at the ET Enterprise AI Awards 2026
The recognition acknowledges Novel Patterns’ application of agentic AI to complex lending decisions through DecisionOS, its decision intelligence Platform for financial institutions. DecisionOS connects financial evidence, policy, reasoning and workflow to help AI move beyond task automation and participate intelligently across the lending lifecycle. Novel Patterns’ solutions are currently live with 140+ financial institutions across India, Africa and Southeast Asia.
Ashwani Arora, CEO, Novel Patterns, said, “Banks and NBFCs don’t adopt AI simply because it is fast. They adopt it when it can improve decision capacity while remaining accurate, explainable and defensible in front of a regulator, an auditor and a credit committee. We built DecisionOS around a simple discipline: AI reasons on evidence, operates within policy, and every output carries a traceable record of how it got there.”
DecisionOS: Intelligence Across the Lending Lifecycle
And many more intelligence capabilities across the financial lifecycle.
Together, these capabilities connect customer context, financial evidence, policy, reasoning and workflow into a common decision fabric.
Built for Financial Intelligence - Not Generic AI The intelligence behind DecisionOS is purpose-built for financial decision-making. The platform is designed around a multi-layer trust architecture incorporating source-grounded processing, policy and rule validation, cross-document reconciliation, confidence scoring and human-in-the-loop review for exceptions.
It analyses more than 400 financial and behavioural indicators and bring more than 1,000 behavioural risk signals into credit assessment. Proprietary financial ontologies provide the domain context required to interpret relationships across different sources of financial information.
DecisionOS combines this intelligence with policy and workflow, helping institutions understand what the evidence means, which policy applies, why a recommendation was generated and what needs to happen next.
From AI Automation to Decision Intelligence For Novel Patterns, the award is a milestone in a larger ambition: to build a connected intelligence layer for financial decision-making.
The objective is not to replace human judgement, but to let AI handle more of the complexity while people retain authority where judgement matters - with consequential decisions remaining explainable and auditable.
Intelligence that reasons. Decisions that remain human. Outcomes that can be trusted.
About Novel Patterns Novel Patterns is an AI-native financial intelligence company building intelligent decision infrastructure for financial institutions. Its platforms combine financial domain intelligence, AI reasoning, decision orchestration and governance across lending and investment management. Novel Patterns’ solutions are used by 140+ financial institutions across India, Africa and Southeast Asia. |
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