Complaint Management Data Product
Here are a few options, all similar in length and focusing on different aspects: * **Elevating complaints: From reactive fixes to AI-powered insights.** * **Building AI to transform complaints into actionable intelligence.** * **Moving beyond reactive complaints: An AI-driven intelligence platform.** * **Leveraging AI to evolve complaints into a data-rich intelligence asset.** * **Turning complaints: From manual tasks to AI-powered, data-focused solutions.**
The Business Challenge
Here are a few options, all similar in length and capturing the core meaning: **Option 1 (Focus on problems):** The bank's old complaint system was slow, disjointed, and addressed issues after they arose. This resulted in delays, data errors, and delayed detection of compliance problems. **Option 2 (Focus on impact):** Manual and reactive, the bank's complaint process caused operational gridlock, unreliable data, and late identification of potential compliance breaches. **Option 3 (More concise):** A manual, fragmented complaint system created delays, flawed data, and delayed detection of compliance issues for the bank. **Option 4 (Emphasizing automation's absence):** Without automation, the bank's complaint process was slow, disconnected, and only responded after the fact. This hampered efficiency, corrupted data, and delayed discovery of compliance risks.
- Operational Inefficiency: Agents spent valuable minutes manually reviewing and tagging every interaction.
- Inconsistent Classification: Complaint categories varied widely across different teams and regions.
- Limited Regulatory Visibility: Here are a few options for rewriting the line, all similar in length and conveying a similar meaning: * **Fair lending and UDAAP risks surfaced too late.** * **Prompt identification of fair lending/UDAAP risks failed.** * **The detection of risks (fair lending, UDAAP) lagged.** * **Fair lending/UDAAP concerns were recognized belatedly.** * **Risk assessment for lending practices and UDAAP was slow.**
The DataKnobs Solution
DataKnobs built a modular, API-first Complaint Management Data Product. Here are a few options, all similar in length and meaning: * This system elevates complaint handling to a data-driven intelligence tool. * Complaint management evolves, becoming a data intelligence asset. * The system turns complaint workflows into a data intelligence engine. * This solution converts complaint processes into a data intelligence product.
Here are a few options, all roughly the same length as the original: * Driven by advanced AI, it analyzes complaint data to enhance insights for various teams. * Using sophisticated AI, it streams, processes, and enhances complaint data for insights across teams. * Fueled by AI, it transforms complaint data through ingestion, processing, and enrichment, benefitting teams. * Leveraging AI, it continuously ingests, processes, and refines complaint information for key stakeholders.
Interactive AI Architecture
Here are a few options, all similar in length: * **Tap layers to understand their data product role.** * **Explore layer roles by clicking each one.** * **View layer functions by clicking each element.** * **Click layers to reveal their role in the output.**
Data Layer
Core Function: Ingests multi-channel interactions, transcripts, CRM notes.
Role in Data Product: Provides unified, governed data ingestion for all downstream processes.
LLM Layer (Prompt)
Core Function: Classifies, summarizes, and identifies risk from unstructured text.
Role in Data Product: Converts raw text into structured complaint JSON, enabling automated detection.
RAG Layer
Core Function: Retrieves internal policies, procedures, and SOPs for grounding.
Role in Data Product: Ensures all AI-generated outputs are explainable, compliant, and cited.
AI Agent Layer
Core Function: Here are a few options, all similar in length and meaning: * Offers a chat-like way for users to ask about the data. * Enables users to ask questions of the data conversationally. * Gives human users an interactive way to explore the data. * Allows users to explore the data through natural conversations.
Role in Data Product: Delivers contextual insights and recommendations to operations and compliance teams.
Analytics Layer
Core Function: Performs clustering, trend detection, and dashboarding.
Role in Data Product: Feeds continuous insights and emerging themes back into business systems.
Key Capabilities
The data product delivers intelligence across three core areas.
1. Complaint Intelligence
Here are a few options, all roughly the same size and conveying a similar meaning: * **Identifies and summarizes complaints, classifying them from raw text to flag regulatory risks.** * **Processes raw complaint text, automatically classifying and summarizing issues to pinpoint regulatory vulnerabilities.** * **From raw text, this system automatically classifies and summarizes complaints, revealing potential compliance problems.** * **Automatically analyzes raw complaints, classifying and summarizing them to uncover potential regulatory breaches.**
{
"is_complaint": true,
"product": "Mortgage",
"issue_type": "Payment Posting Delay",
"severity": "Medium",
"summary": "Customer reports delayed..."
}Impact: 80% automation in detection, 92% accuracy in classification.
2. Policy-Grounded Reasoning
Here are a few options, all keeping a similar length and conveying the same meaning: * Delivers explainable recommendations via RAG, citing internal policies and procedures. * RAG-powered recommendations offer explanations, backed by internal policy citations. * Provides recommendations with rationale, using RAG and citing internal documents. * Generates explainable recommendations through RAG, referencing internal policy data.
{
"recommended_action": "Reverse late fee...",
"policy_citations": [
"Mortgage Servicing Policy - Sec 3.2",
"CFPB Regulation X - Error Resolution"
]
}Impact: 100% of AI recommendations backed by traceable citations.
3. Interactive AI Agent
Here are a few options, all similar in length and capturing the essence of the original: * **Natural language interface for teams investigating complaints and accessing policies across operations, compliance, and CX.** * **Empowering ops, compliance, and CX with a natural language interface for complaint investigation and policy queries.** * **Investigate complaints and query policies easily: a natural language interface for operations, compliance, and CX professionals.** * **Streamline complaint analysis and policy access: a conversational interface for operations, compliance, and CX.**
Impact: 70% reduction in average investigation time.
See it in action ↓Explore the AI Agent Layer
Here are a few options, all similar in length: * **Based on the study, this mock-up lets you explore AI responses. Click a suggestion.** * **This mock-up, informed by the case study, shows potential AI replies. Select a suggestion.** * **Explore AI answers with this mock-up, derived from the case study. Choose a suggestion.** * **See potential AI replies using this mock-up, based on the case study. Tap a suggestion.**
Compliance AI Agent
Try these examples:
Measurable Business Impact
The data product delivered significant, measurable improvements across the board.
| Metric | Before | After | Improvement |
|---|---|---|---|
| Complaint Classification Time | 3–5 min | <1 min | 80% faster |
| Regulatory Review Cycle | 10 days | 5 days | 50% faster |
| Accuracy (Complaint Detection) | ~70% | 92% | +22 pts |
| Complaint Volume Coverage | 25% | 100% | 4x increase |
| Analyst Productivity | 20 cases/day | 35+ cases/day | +75% |
Here are a few options, all aiming for a similar length and conveying the core meaning: **Option 1 (Concise):** "DataKnobs created more than AI; it's a data product. This core asset provides our teams with real-time customer insights and compliance oversight, central to our CX and risk management." **Option 2 (Emphasis on Impact):** "DataKnobs delivers a transformative data product, not just AI. It gives our teams instant visibility into customer issues and compliance concerns. It's now crucial to our CX and risk infrastructure." **Option 3 (Focus on Functionality):** "DataKnobs' data product offers real-time analysis, going beyond basic AI. It highlights customer pain points and compliance risks, becoming a central data asset for CX and risk operations."