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# A leading US lender turns static dashboards into conversational analytics for risk & origination
**URL:** https://www.sigmoid.com/case-studies/a-leading-us-lender-turns-static-dashboards-into-conversational-analytics-for-risk-origination/
Date: 2026-09-26
Author: Joha Momin
Post Type: page
Summary: AI on BI · Risk & Origination · Personal Loans Interactive Case Study A leading US lender turns static dashboards into conversational...Read More...
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AI on BI · Risk & Origination · Personal Loans
Interactive Case Study
# A leading US lender turns static dashboards into conversational analytics **for risk & origination**
A leading US consumer lender's **risk and loan origination teams** manage a large personal-loan portfolio spanning a wide range of borrower risk profiles. Their reporting, however, ran on static, template-bound dashboards that could show what was happening but not why. Sigmoid layered **conversational analytics** on top with an **AI-on-BI** solution built on Snowflake Cortex and Claude, so analysts can now **talk to the data**: ask a question in plain English and get granular, root-cause answers on the fly. What once took a 2–3 week reporting cycle now takes minutes.
The Insight Gap
Before conversational BI
Questions the dashboard couldn't answer
Why did December FPD jump to 1.96%?No drill-down
Is it a risk-segment mix shift?Needs a new view
Filter to Direct Auto & SDL UnsecuredFile a ticket
2–3 wks
Each root-cause analysis meant a request to the BI team, and a **2–3 week wait**
### Business Scenario
### For risk & loan origination teams, every deep-dive was a **2–3 week reporting cycle**
On a fast-moving personal-loan book, analysts could see a number move but couldn't interrogate it. Any new view (a segment breakdown, a product cut, a fresh filter) had to be pre-built by the development team, so finding the underlying cause of a risk or origination issue meant filing a request and waiting in the reporting backlog. With no standardized semantic layer, definitions drifted across reports, and teams were left identifying risk trends slowly and inconsistently, with root-cause analysis effectively out of reach.
### Key Challenges Addressed
C1
Static dashboards limited drill-down into specific problem areas, stalling root-cause analysis on risk and origination.
C2
Interactive dashboards were confined to templates the development team had pre-built; anything new required engineering and a wait.
C3
No standardized semantic layer meant definitions drifted, leaving reporting inconsistent across risk & origination use cases.
One Risk Question: Before vs After
From a 2–3 week cycle to a single conversation
Before
Ticketed reporting cycle: 2–3 weeks
01
Spot the spike
→
02
File a ticket
→
03
Wait in backlog
→
04
Review new view
Every follow-up restarts the loop; root-cause analysis drags on for weeks.
After
Conversational analytics: minutes
01
Ask in plain English
→
02
Cortex Agent routes
→
03
Answer + RCA + actions
Root-cause analysis in minutes, so analysts talk to the data
### AI on BI · Sigmoid's Solution
Sigmoid layered **conversational analytics** directly on the risk & origination BI stack. A curated knowledge layer captures metadata, joins, filters and FAQs; reusable semantic views turn raw loan, bureau and portfolio data into business concepts; and a **Cortex Agent** (the routing brain) sends each plain-English question to the right analyst, returning consistent charts through a Python replication layer and a Streamlit app. The result is faster insights generation: analysts **talk to the data** and get granular, root-cause answers without leaving the dashboard. Because processing runs through Snowflake Cortex, portfolio data stays inside the client's own environment, and every answer is backed by the SQL and semantic view it came from.
High-Level Solution Architecture
Foundation: runs under every layer
Knowledge &
Semantic Layer
Snowflake Cortex
Claude Sonnet
Streamlit
Python Chart Replication
Data Sources
Inbound
Loan Origination
Credit Bureau
Portfolio Data
Formats
Base tables & schema
Semantic Layer
Knowledge
Metadata, Joins, Filters, FAQs
Views
Aggregated view
Base + Account-level views
Cortex Agent
Routing brain
Intent detection
Routes to
Executive · aggregated
Detail · granular
Streamlit App
Executive path
Trends, KPIs & consistent charts
Detail path
RCA, SQL & deep dives
Users
Risk · Origination · Strategy
Data & AI stack
Powered by
Snowflake Cortex
Claude Sonnet
Semantic Views
Streamlit + Python
### Key Solution Capabilities
#### Analysts talk to the data
Risk & origination teams ask questions in plain English and the dashboard responds with the exact cut they need, even when it isn't on the current chart.
#### Find the underlying cause
Dual-analyst routing sends each question to the right analyst, so teams can find the underlying cause of any risk or loan-origination issue in minutes, not weeks.
#### Identify risk trends faster & better
A governed knowledge & semantic layer keeps every metric consistent, helping teams identify risk trends faster and better across the personal-loan book.
### Conversational Analytics, Live
This is how **analysts now talk to the data**. The dashboard shows the standard risk & origination cuts, but when the answer isn't on the chart, they just ask. The Cortex Agent routes the question and the dashboard responds dynamically with granular, root-cause detail. **Try a question ↓**
Application Distribution
Loan Distribution
PTR
Risk Performance
Delinquencies by MOB
Dimensions
Risk Level
Customer Type
Vantage Bucket
Density
Top 10 State
Product Type
Customer X Product
Report Level
Year-Month ▾
Year
20252026
Month
JanDec
Origination Mix by Risk Segment
Booking share by risk level · Oct–Dec 2025
Stack
Group
Customer Type
FCNCPC
Risk Level
1.S2.P3.A4.B5.C-En/anull
**Not seeing the cut you need?** Ask the dashboard, in plain English.
Ask about risk trends, segments, products, or run a root-cause analysis…
↑
### Business Impact
100×
Faster Root-Cause Analysis
From 2–3 weeks → minutes
What once took risk & loan origination teams a **2–3 week reporting cycle** now takes **minutes**, through plain conversation with the AI agent. Analysts talk to the data, find the underlying cause of any risk or origination issue, and identify risk trends faster and better.
### 80%
#### Faster Insights Generation
Real-time, prompt-driven analytics and RCA replace the reporting backlog across the personal-loan book.
### Scalable
#### Reusable Reporting Framework
A standardized charting framework extends across future personal-loan use cases without rebuilding for each report.
### Self-Serve
#### Conversational Analytics
Risk & origination teams talk to the data in plain English and get granular, root-cause answers on the fly: no SQL, no BI ticket, no wait.
### About Sigmoid
Sigmoid helps companies modernize data, transform business processes, and make better decisions using AI, to gain competitive advantage. Enterprises are able to unlock new revenue opportunities and improve operational efficiency by partnering with Sigmoid to build bespoke GenAI and agentic AI solutions powered by strong data foundations and contextual knowledge.
[www.sigmoid.com](http://www.sigmoid.com)
### Let's Get Started
Bring conversational analytics to your risk & origination dashboards: AI on BI, with root-cause analysis in minutes instead of weeks.
[Contact Us](mailto:[email protected])
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