{
  "docId": "019dd923-5ca1-7489-b633-746ffdbc9114",
  "docSlug": "6543568fbc47af38",
  "documentTitle": "The age of AI: Banking’s new reality",
  "authorId": "Accenture",
  "authorName": "Accenture",
  "documentKindSlug": "consulting-deck",
  "documentKindLabel": "Consulting deck",
  "sourceTypeSlug": "strategy_consulting",
  "sourceTypeLabel": "Strategy consulting",
  "presentationDate": null,
  "orientation": "landscape",
  "aspectRatio": 1.778,
  "pageNumber": 23,
  "pageCount": 41,
  "prevPage": 22,
  "nextPage": 24,
  "slideType": "initiative_list",
  "function": "plan_implementation",
  "density": "dense",
  "nDataPoints": 0,
  "notes": "The slide uses a purple background typical of high-level strategic consulting decks. The bottom navigation bar indicates this is part of a broader framework of 6 steps.",
  "elementsJson": [
    "headline_text",
    "action_title",
    "subtitle_text",
    "bullet_list"
  ],
  "metadataConfidence": 1,
  "imagePath": null,
  "slideHref": "/slides/019dd923-5ca1-7489-b633-746ffdbc9114/23",
  "deckHref": "/decks/019dd923-5ca1-7489-b633-746ffdbc9114",
  "deckJsonHref": "/decks/019dd923-5ca1-7489-b633-746ffdbc9114.json",
  "deckAnchorHref": "/decks/019dd923-5ca1-7489-b633-746ffdbc9114#slide-23",
  "components": [
    {
      "bbox": null,
      "kind": "callout",
      "text": "Test various architectures to find the best fit for each use case and plan the model's lifecycle from experimentation to scaling and phase-out. This could be achieved through a 'model switchboard' where banks can select a combination of models based on the business context or on factors such as cost or accuracy.",
      "attrs": null,
      "subkind": null,
      "toolName": "Visual emphasis",
      "toolSlug": "visual-emphasis",
      "confidence": null,
      "componentId": "019dd951-9f64-72ba-b40e-4c5b38e392db",
      "frameworkName": null,
      "frameworkSlug": null
    },
    {
      "bbox": {
        "h": 0.3,
        "w": 0.3,
        "x": 0.36,
        "y": 0.25
      },
      "kind": "list",
      "text": "Start moving towards data-as-a-service models. Elevate data governance standards to effectively manage unstructured data. Evolve security protocols to address the complexities that come with diverse data access.",
      "attrs": null,
      "subkind": "bullet",
      "toolName": null,
      "toolSlug": null,
      "confidence": null,
      "componentId": "623f222c-801b-4f55-b4b1-c82f7350b879",
      "frameworkName": null,
      "frameworkSlug": null
    },
    {
      "bbox": {
        "h": 0.3,
        "w": 0.3,
        "x": 0.05,
        "y": 0.25
      },
      "kind": "list",
      "text": "Assess the complete inventory of unstructured data across the organization and analyze how it could help power generative AI. Start to move this data into vector databases and scale them with the precision required for real-time analytics.",
      "attrs": null,
      "subkind": "bullet",
      "toolName": null,
      "toolSlug": null,
      "confidence": null,
      "componentId": "acbb4cf3-84a1-41bd-b513-2551818f0c8e",
      "frameworkName": null,
      "frameworkSlug": null
    },
    {
      "bbox": {
        "h": 0.3,
        "w": 0.3,
        "x": 0.67,
        "y": 0.25
      },
      "kind": "list",
      "text": "Test various architectures to find the best fit for each use case and plan the model's lifecycle from experimentation to scaling and phase-out using a 'model switchboard'.",
      "attrs": null,
      "subkind": "bullet",
      "toolName": null,
      "toolSlug": null,
      "confidence": null,
      "componentId": "ce3faf3a-d706-4b00-a457-adb91e1852fb",
      "frameworkName": null,
      "frameworkSlug": null
    },
    {
      "bbox": {
        "h": 0.05,
        "w": 0.6,
        "x": 0.05,
        "y": 0.08
      },
      "kind": "title",
      "text": "Understand and develop a secure AI-enabled digital core",
      "attrs": null,
      "subkind": "headline",
      "toolName": null,
      "toolSlug": null,
      "confidence": null,
      "componentId": "7f8f5f03-c02f-4cfd-9c51-a5dea6e52caa",
      "frameworkName": null,
      "frameworkSlug": null
    },
    {
      "bbox": {
        "h": 0.04,
        "w": 0.15,
        "x": 0.05,
        "y": 0.18
      },
      "kind": "title",
      "text": "ACTIONS",
      "attrs": null,
      "subkind": "subtitle",
      "toolName": null,
      "toolSlug": null,
      "confidence": null,
      "componentId": "8d5d21e4-864a-40b4-898e-3bbe7250b416",
      "frameworkName": null,
      "frameworkSlug": null
    }
  ],
  "metrics": [],
  "tools": [
    {
      "name": "Chunking",
      "slug": "chunking",
      "agent": "Architect",
      "layer": "loop",
      "matchId": "019dd95a-0f08-73d3-987a-801fec1ca867",
      "evidence": "Bulleted action list breaks digital-core actions into discrete items",
      "confidence": 80
    },
    {
      "name": "Parallel Structure",
      "slug": "parallel-structure",
      "agent": "Architect",
      "layer": "loop",
      "matchId": "019dd95a-0f08-73d3-987a-8743bc0976ec",
      "evidence": "Each bullet starts with imperative verb",
      "confidence": 75
    }
  ],
  "frameworks": [],
  "arcBeats": [
    {
      "to": 34,
      "from": 13,
      "beatId": "019dd95a-0682-776c-8e32-635915b6754b",
      "arcName": "The Consultant's Gambit",
      "arcSlug": "consultants-gambit",
      "beatName": "Evidence & Proof",
      "beatSlug": "consultants-gambit-evidence-proof",
      "evidence": "Each imperative built out with figure, recommendation, named bank case study, and actions",
      "position": 4,
      "confidence": 92,
      "parentBeatName": "Evidence",
      "parentBeatSlug": "evidence"
    },
    {
      "to": 36,
      "from": 13,
      "beatId": "019dd95a-0682-776c-8e32-728a04f7c9a1",
      "arcName": "The Triple Take",
      "arcSlug": "triple-take",
      "beatName": "The Action (Now What)",
      "beatSlug": "triple-take-the-action-now-what",
      "evidence": "Per-imperative actions, case studies and ROI playbook",
      "position": 3,
      "confidence": 65,
      "parentBeatName": "Resolution",
      "parentBeatSlug": "resolution"
    }
  ],
  "loops": [
    {
      "to": 23,
      "from": 19,
      "name": "Zoom In",
      "slug": "06-zoom-in",
      "bestFor": "Technical deep-dives, case studies, detailed analysis",
      "matchId": "019dd95a-07fe-70ce-8d3a-27ce0246ea89",
      "evidence": "Divider -> Figure 3 maturity distribution -> context -> case study -> actions",
      "position": 6,
      "objective": "Prove imperative 2 (Digital core) end-to-end",
      "structure": "The Big Picture -> Key Area of Focus -> Specific Detail -> Implication",
      "confidence": 78,
      "description": "Start broad, then progressively focus on specific details that prove your point"
    }
  ],
  "imagePathAlt": null,
  "thumbSrc": null,
  "thumbSrcAlt": null,
  "locked": true
}