{"id":30289,"date":"2026-01-20T18:48:50","date_gmt":"2026-01-20T23:48:50","guid":{"rendered":"https:\/\/riscco.com\/?page_id=30289"},"modified":"2026-04-27T17:54:58","modified_gmt":"2026-04-27T22:54:58","slug":"ai","status":"publish","type":"page","link":"https:\/\/riscco.com\/en\/ai\/","title":{"rendered":"AI Services"},"content":{"rendered":"\t\t
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AI FAIRNESS, BIAS & DECISION RISK SERVICES<\/h1>\t\t\t\t<\/div>\n\t\t
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01. AI Training<\/h2>\t\t\t\t<\/div>\n\t\t
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We explain AI<\/span>, GenAI, bias and regulation in simple business language, with real examples from financial institutions and public entities in the region.<\/h3>\t\t\t\t<\/div>\n\t\t
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Your teams will learn to:<\/strong><\/h4>

Understand<\/strong> where AI and scoring models are already influencing decisions<\/p>

Recognize<\/strong> the main risks of unfair, opaque or poorly documented decisions<\/p>

Know<\/strong> what questions to ask vendors and data science teams<\/p>

Connect<\/strong> AI projects with GRC, Internal Audit, HR, Legal and Risk responsibilities<\/p>\t\t\t\t\t\t\t\t<\/div>\n\t\t\t\t

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Delivery formats:<\/strong><\/h4>

Executive briefings<\/strong> for Boards and C-Suite (2-3 hours)<\/p>

Workshops<\/strong> for GRC, Internal Audit, HR, Legal and Risk (half-day or full-day)<\/p>

Custom sessions<\/strong> on “How to Audit AI Projects” for internal audit teams<\/p>\t\t\t\t\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t

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02. Data & Bias Validation
(Pre-Deployment)<\/small><\/h2>\t\t\t\t<\/div>\n\t\t
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Before you put an AI, scoring or decision model into production, we review<\/span> the data, variables and governance that support it. <\/h2>\t\t\t\t<\/div>\n\t\t
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Our goal:<\/strong> help you identify and fix problems before they become compliance issues or public incidents.<\/p>\t\t\t\t\t\t\t\t<\/div>\n\t\t\t\t

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We evaluate:<\/strong><\/h4>

Data quality and coverage:<\/strong> Who is represented? Who is missing or underrepresented?<\/p>

Protected attributes and proxies:<\/strong> Age, gender, location, tenure and variables that may correlate with them<\/p>

Labels and rules:<\/strong> How are “good” and “bad” outcomes defined? Are definitions consistent and defensible?<\/p>

Documentation and controls:<\/strong> Can your process withstand an internal or external audit?<\/p>

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Deliverables:<\/strong><\/h4>

Data & Bias Validation Report<\/strong> with findings, risk ratings and recommendations<\/p>

Evidence package<\/strong> for Internal Audit, Risk, Compliance and regulators<\/p>

Practical remediation roadmap:<\/strong> fix data, adjust variables, strengthen governance<\/p>

We work with your existing data science team and vendors. We do not build the model; we independently validate the data and decision logic.<\/p>\t\t\t\t\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t

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03. AI Forensic Audit
(Post-Deployment)<\/small><\/h2>\t\t\t\t<\/div>\n\t\t
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When AI is questioned, we help you explain<\/span> what happened. <\/h2>\t\t\t\t<\/div>\n\t\t
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If there is a complaint, incident or investigation related to an AI system, scoring model or automated decision tool, we act as an independent forensic expert<\/strong>.<\/p>\t\t\t\t\t\t\t\t<\/div>\n\t\t\t\t

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We help you:<\/strong><\/h4>

Reconstruct<\/strong> how the system made decisions over time<\/p>

Analyze<\/strong> outcomes by group (age, gender, location and other relevant segments)<\/p>

Determine<\/strong> whether issues stem from data, model configuration, thresholds or human overrides<\/p>

Prepare<\/strong> evidence, narratives and visuals for internal review, regulators or court proceedings<\/p>\t\t\t\t\t\t\t\t<\/div>\n\t\t\t\t

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Our forensic advantage:<\/span><\/strong><\/h4>

In our region, judges and prosecutors still rely on the professional judgment of a human expert, not on software alone. We use specialized tools, but our value is:<\/p>

A clear and defensible<\/strong> methodology<\/p>

Proper chain of custody<\/strong> and evidence handling<\/strong><\/p>

Reports and explanations<\/strong> that non-technical decision-makers can understand<\/p>\t\t\t\t\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t

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We manage risk. We audit AI decisions.<\/h4>\t\t\t\t<\/div>\n\t\t\t\t
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  • \n\t\t\t\t\t\t\t\t\t\tWe focus on the risk of unfair, opaque or poorly documented AI-driven decisions
    (hiring, credit, fraud, collections, public services). We do not build AI models or platforms.
    We independently evaluate, challenge and document them.<\/span>\n\t\t\t\t\t\t\t\t\t<\/li>\n\t\t\t\t\t\t<\/ul>\n\t\t\t\t\t\t<\/div>\n\t\t\t\t
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