Intelligent Risk Management
Regnology Unveils AI-Powered Risk Hub Ascend for Proactive Enterprise Risk Management
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Regnology has launched Regnology Risk Hub (RRiH) Ascend, a major upgrade to its risk management platform that brings AI directly into balance sheet and treasury decision-making Montreal Gazette. The product is now fully built into the Ascend cloud platform and uses a new AI layer called RGI — Regnado's Governed Intelligence — to turn complex financial data into plain-language insights for risk officers in real time.
CEO Rob Mackay said the goal is to give banks "a single version of the truth" — letting treasury and risk teams see the impact of market moves on regulatory reports in real time, not weeks later Calgary Sun. The launch also debuts agentic AI, which can autonomously scan for data errors before a reporting deadline closes.
What RGI Actually Does Inside the Platform
RGI ships with three core tools. RGI Explain turns dense risk metrics — things like Liquidity Coverage Ratios or Value at Risk — into natural language summaries. It shows exactly which data points caused a sudden shift in a bank's risk profile Edmonton Sun. RGI Assist acts like a co-pilot. A risk manager can type a plain-English question: "What happens to our funding ratio if the ECB raises rates by 50 basis points?" and get an instant answer.
The third layer is agentic AI — software agents that run on their own. They scan for gaps between a bank's internal ledger and its risk engine, then fix errors before the reporting window closes Toronto Sun. Regnology claims the system can reduce reporting latency — the time between a market event showing up in a regulatory filing — by 90%.
Why Banks Have Needed This for Years
Banks have long run two separate systems: one for internal risk decisions, and one for filing reports to regulators like the ECB or the Bank of England. The problem is "data drift" — the numbers sent to regulators can differ from the numbers the bank's own board uses, because the two systems calculate things differently Sault Star. Basel IV regulations have made this worse by demanding far more detailed data on capital and liquidity.
Regnology calls its fix "Straight-Through Reporting" (STR) — one data pipeline that feeds both internal decisions and external filings at once. Chief Product Officer Maciej Piechocki said the "G" in RGI is the most critical part. "In a regulated environment, black-box AI is a liability," he said. "RGI Explain provides the audit trail that regulators demand" Woodstock Sentinel Review.
Regulators Welcome the Vision but Draw a Red Line
The European Banking Authority has welcomed better data quality but is drawing a firm line on automation. A spokesperson said that "while automation improves efficiency, the final accountability for any regulatory filing remains with the human compliance officer" Sudbury Star. The EU AI Act, which classifies financial AI as high-risk, is also pushing Regnology to keep humans in the loop.
Privacy advocates raise a different concern. Putting sensitive risk data for thousands of banks onto one cloud platform creates a large target. Critics argue that agentic AI adds a new attack surface — agents could, in theory, be manipulated to obscure risk rather than flag it Brantford Expositor. German labor unions have also pushed for "Right to Review" clauses, worried that autonomous agents will shrink compliance departments.
Cost Savings and Competitive Pressure Now Mount
For mid-sized banks, moving to a unified platform like RRiH Ascend could save between $5 million and $12 million a year in legacy software costs and manual auditing Goderich Signal Star. Analysts at Gartner estimate agentic AI could cut manual data reconciliation time by up to 70% at a typical bank. The global RegTech market is projected to reach $20.4 billion by the end of 2026, growing at 18% per year.
The launch puts direct pressure on rivals Wolters Kluwer and Moody's Analytics, who must now speed up their own explainable-AI roadmaps Whitecourt Star. Analysts at Chartis Research say Regnology is effectively "commoditizing" basic reporting and moving the real value to AI-driven risk intelligence — a bet that will take roughly 24 months to prove out with regulators.
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