{
  "docId": "019dd923-5de0-76bd-a169-3232a0a05dd2",
  "docSlug": "ed72ee2d6510b5ed",
  "documentTitle": "AI/ML use in Risk Management and Compliance PwC Actuarial, Risk & Quants",
  "authorId": "PwC",
  "authorName": "Institute of International Finance",
  "documentKindSlug": "consulting-deck",
  "documentKindLabel": "Consulting deck",
  "sourceTypeSlug": "strategy_consulting",
  "sourceTypeLabel": "Strategy consulting",
  "presentationDate": null,
  "orientation": "portrait",
  "aspectRatio": 0.771,
  "pageNumber": 3,
  "pageCount": 8,
  "prevPage": 2,
  "nextPage": 4,
  "slideType": "appendix_methodology",
  "function": "present_framework",
  "density": "balanced",
  "nDataPoints": 0,
  "notes": "The slide is a page from a journal article, containing a table classifying ML methods.",
  "elementsJson": [
    "paragraph",
    "data_table",
    "footnote"
  ],
  "metadataConfidence": 0.95,
  "imagePath": null,
  "slideHref": "/slides/019dd923-5de0-76bd-a169-3232a0a05dd2/3",
  "deckHref": "/decks/019dd923-5de0-76bd-a169-3232a0a05dd2",
  "deckJsonHref": "/decks/019dd923-5de0-76bd-a169-3232a0a05dd2.json",
  "deckAnchorHref": "/decks/019dd923-5de0-76bd-a169-3232a0a05dd2#slide-3",
  "components": [
    {
      "bbox": {
        "h": 0.125,
        "w": 0.355,
        "x": 0.133,
        "y": 0.223
      },
      "kind": "paragraph",
      "text": "The machine learning spectrum comprises many different analytical methods, whose applicability varies with the types of statistical problem one might want to address.",
      "attrs": null,
      "subkind": "paragraph",
      "toolName": null,
      "toolSlug": null,
      "confidence": null,
      "componentId": "cf011d30-a767-4277-9488-531057a32e04",
      "frameworkName": null,
      "frameworkSlug": null
    },
    {
      "bbox": {
        "h": 0.085,
        "w": 0.355,
        "x": 0.513,
        "y": 0.765
      },
      "kind": "source-note",
      "text": "5 PLS is used to find the fundamental relations between two matrices through linear regression. 6 LASSO stands for least absolute shrinkage and selection operator...",
      "attrs": null,
      "subkind": null,
      "toolName": null,
      "toolSlug": null,
      "confidence": null,
      "componentId": "7def610c-79b7-48fa-b50d-5ed0bedc0a5a",
      "frameworkName": null,
      "frameworkSlug": null
    },
    {
      "bbox": {
        "h": 0.45,
        "w": 0.355,
        "x": 0.513,
        "y": 0.223
      },
      "kind": "table",
      "text": "Table 1 - Overview of machine learning methods",
      "attrs": null,
      "subkind": "data",
      "toolName": null,
      "toolSlug": null,
      "confidence": null,
      "componentId": "a3290a35-c4c6-49fc-85e0-e038c234328a",
      "frameworkName": null,
      "frameworkSlug": null
    },
    {
      "bbox": {
        "h": 0.015,
        "w": 0.235,
        "x": 0.133,
        "y": 0.208
      },
      "kind": "title",
      "text": "Machine learning methods",
      "attrs": null,
      "subkind": "headline",
      "toolName": null,
      "toolSlug": null,
      "confidence": null,
      "componentId": "458aea64-766d-49c8-9d42-95acd29aa190",
      "frameworkName": null,
      "frameworkSlug": null
    }
  ],
  "metrics": [],
  "tools": [
    {
      "name": "Table data",
      "slug": "table-data",
      "agent": null,
      "layer": "slide",
      "matchId": "a0293de0-268c-4789-b829-a6cc177e58fd",
      "evidence": "This slide contains a table titled 'Table 1 - Overview of machine learning methods'.",
      "confidence": 0.7
    }
  ],
  "frameworks": [
    {
      "name": "matrix-nxn",
      "slug": null,
      "matchId": "29f0d568-1f15-4b39-aba7-52ada3a39483",
      "evidence": "The table classifies machine learning methods across two dimensions: Problem type (rows) and Linearity (columns).",
      "confidence": 0.9
    }
  ],
  "arcBeats": [
    {
      "to": 6,
      "from": 3,
      "beatId": "17dca3c3-2dc7-49c5-9944-173b72592055",
      "arcName": "The Sparkline",
      "arcSlug": "sparkline",
      "beatName": "What Could Be",
      "beatSlug": "sparkline-what-could-be-2",
      "evidence": "The description of machine learning methods implies a discussion of potential applications.",
      "position": 1,
      "confidence": 0.8,
      "parentBeatName": "Turn",
      "parentBeatSlug": "turn"
    }
  ],
  "loops": [
    {
      "to": 6,
      "from": 2,
      "name": "Golden Circle",
      "slug": "11-golden-circle",
      "bestFor": "Visionary leadership, brand positioning, mission statements",
      "matchId": "9c3ec2cd-b1e2-45a4-bcee-88541722f204",
      "evidence": "The introduction and method descriptions imply a Golden Circle structure.",
      "position": 0,
      "objective": "Why AI/ML is useful in risk management and compliance",
      "structure": "The Why (Belief) -> The How (Process) -> The What (Result)",
      "confidence": 0.7,
      "description": "Invert the typical pitch by starting with why you exist, rather than what you do"
    }
  ],
  "imagePathAlt": null,
  "thumbSrc": null,
  "thumbSrcAlt": null,
  "locked": true
}