Manual research slowed audit planning. A custom AI assistant now automates data analysis, cutting planning time by 65%.
One of Brazil's largest private banks manages a massive volume of sensitive operational data while navigating an increasingly complex regulatory landscape.
Audit planning required many hours of manual research, and the reporting phase was heavily manual and time-consuming. This administrative burden...
“AILA’s proposal was clear: to automate operational or repetitive tasks, allowing auditors to act with analytical depth and focus on the most relevant business risks.”
Full-service commercial bank providing retail, corporate, and investment banking services.
Enterprise software, cloud infrastructure, and consumer electronics platform.
Bradesco's Internal audit assistant is part of this use case:
Related implementations across industries and use cases
Hours searching SharePoint, days waiting for QA, reports rewritten when templates changed. Now two agents answer instantly from live docs.
Review cycles took months, leaving 60% of risks invisible. AURA now monitors every change in real time—analysts approve before action.
700 hours a year on manual JSON deployments across 18 assistants. Automation cut each to minutes.
Review cycles took months, leaving 60% of risks invisible. AURA now monitors every change in real time—analysts approve before action.
Manual sampling struggled with petabytes of data. Now, AI agents analyze entire datasets, freeing auditors for high-risk insights.
Analysts couldn't touch the data—every question funneled through engineers, taking hours or weeks. Now they get answers in seconds.
Finance spent six hours stitching four data sources into fully burdened cost models. Now, they use AI to generate them in minutes.
Routine administrative tasks once tied up human experts for entire days. AI now completes these workflows in just minutes.
Manual spot-checks missed duplicates. AI now audits 100% of spend, catching $20k in errors and reclaiming 160 hours for analysis.
Manual research slowed audit planning. A custom AI assistant now automates data analysis, cutting planning time by 65%.
One of Brazil's largest private banks manages a massive volume of sensitive operational data while navigating an increasingly complex regulatory landscape.
Audit planning required many hours of manual research, and the reporting phase was heavily manual and time-consuming. This administrative burden...
“AILA’s proposal was clear: to automate operational or repetitive tasks, allowing auditors to act with analytical depth and focus on the most relevant business risks.”
Full-service commercial bank providing retail, corporate, and investment banking services.
Enterprise software, cloud infrastructure, and consumer electronics platform.
Bradesco's Internal audit assistant is part of this use case:
Related implementations across industries and use cases
Hours searching SharePoint, days waiting for QA, reports rewritten when templates changed. Now two agents answer instantly from live docs.
Review cycles took months, leaving 60% of risks invisible. AURA now monitors every change in real time—analysts approve before action.
700 hours a year on manual JSON deployments across 18 assistants. Automation cut each to minutes.
Review cycles took months, leaving 60% of risks invisible. AURA now monitors every change in real time—analysts approve before action.
Manual sampling struggled with petabytes of data. Now, AI agents analyze entire datasets, freeing auditors for high-risk insights.
Analysts couldn't touch the data—every question funneled through engineers, taking hours or weeks. Now they get answers in seconds.
Finance spent six hours stitching four data sources into fully burdened cost models. Now, they use AI to generate them in minutes.
Routine administrative tasks once tied up human experts for entire days. AI now completes these workflows in just minutes.
Manual spot-checks missed duplicates. AI now audits 100% of spend, catching $20k in errors and reclaiming 160 hours for analysis.