Wibmo has launched an AI platform built to support fraud, anti-money laundering (AML), know your customer (KYC), and dispute-handling teams facing rising volumes of digital payments risk. The company said early tests show the system can cut investigation time by more than 70%, a figure that directly affects how many cases an operations analyst can process in a day.
The platform, called Wibmo Agentic Risk Intelligence Assistant (ARIA), was unveiled at an event in Mumbai titled "Securing Digital Payments: Innovation, Intelligence & Trust." Wibmo's Indonesian entity shared product details through an ACN Newswire release. The company is targeting recommendation accuracy close to 90%.
ARIA gathers signals from transactions, risk models, customer and merchant history, linked transactions, and historical fraud patterns. It automates the data aggregation and analysis work that typically consumes analyst time, then drafts recommendations. Final decisions remain with human teams - the system does not execute production actions on its own.
How the platform structures risk work
Wibmo said the platform produces what it calls "evidence-referenced verdicts" and "transparent, auditable recommendations." It supports standard operating procedure-driven resolutions, communications with customers and merchants, reduction of false alerts, and proactive detection of emerging anomalies. Recommendations flow through existing approval mechanisms, and the system maintains reasoning chains and audit trails.
The company described a unified framework covering fraud, AML, KYC, and disputes - four functions that often operate in separate systems. Wibmo emphasized "replayable audits" and operational provenance for every agent action, positioning ARIA as distinct from fully autonomous AI systems.
"As fraud becomes more sophisticated and regulatory expectations continue to evolve, risk operations teams must manage growing complexity with limited resources," said Shailesh Paul, CEO of Wibmo. "ARIA is designed to help institutions scale intelligently by combining the speed and analytical capabilities of AI with the judgment, oversight, and accountability of human expertise. While AI agents assist with data analysis and recommendations, every critical decision continues to remain firmly under human control."
Industry context and attendance
The Mumbai event drew more than 50 senior leaders from banks, fintechs, payment networks, and technology organizations. Participants included speakers from PayU, NPCI Bharat Billpay, Visa, Mastercard, Flipkart, CSB Bank, Jio Payment Solutions, and Network International. Discussions covered acquiring fraud risk management, authentication technologies, and risk-based decisioning - areas where operations teams are under pressure to move faster without sacrificing accuracy.
For operations professionals in financial institutions, tools that reduce investigation time by over 70% shift the math on staffing and throughput. The work sits at the intersection of AI for Operations and AI for Finance, where the practical question is whether systems like ARIA can handle enough volume to let human analysts focus on edge cases and judgment calls.
Why this matters for operations teams
ARIA targets a specific pain point: the hours analysts spend pulling together data from multiple sources before they can even begin investigating a case. If the 70% reduction holds in production, a team of ten could handle the workload that previously required thirty - or keep the same headcount and clear backlogs that currently sit untouched. The governance controls matter too. In regulated environments, an AI that drafts recommendations but leaves approval chains intact is easier to adopt than one that makes autonomous decisions. Operations leaders evaluating such tools will want to see the audit trails and replayable logs Wibmo described, because those determine whether the system passes a regulatory review.
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