Executives are rethinking Business Intelligence
Your finance team just spent four weeks preparing a quarterly board report. Your risk officer needs three days to answer a follow-up question from supervisors. Your wealth and commercial bankers are still waiting for IT to add one more visualization to a dashboard before a client meeting.
And while AI tools are becoming more common in financial services institutions, very few deliver answers to executives' desks and frontline teams when they actually need them. AI is often trapped in pilots, specialist teams or one-off channels. The gap that remains is how business leaders and practitioners access governed insights when they need them.
Legacy BI architectures assume teams will anticipate important questions months ahead, building reports and dashboards on a recurring schedule. That model made sense when the operating environment was more stable. It doesn't hold up when rate moves, fraudsters and evolving customer behavior can shift the questions week to week.
Traditional bolt-on "AI for BI" tools summarize dashboards but can't provide visibility across domains, don't share a single set of business definitions with finance and risk and often rely on copied data with a separate governance plane, which can impact accuracy of decisions. For financial services leaders, that's not enough.
Genie is designed to close this gap in an intuitive and meaningful way. It lets CFOs, CROs, business heads and front-line teams interact with their data in plain English so they can move from static, retrospective packs to interactive, auditable answers. All in seconds, instead of weeks.
Genie for financial services
Genie is a conversational analytics assistant powered by Databricks Data Intelligence Platform. Users ask questions in natural language and receive answers as narrative explanations, tables and visualizations, and can ask follow-ups in the same conversation. Genie is included with Databricks SQL, with no separate BI license or bolt-on tool.
Unlike generic chatbots, Genie learns from your institution's governed data and how your organization defines performance, risk and customer behavior. It draws on:
- Metadata and data values in Unity Catalog
- Certified metrics, dimensions and business definitions that reflect how your CFO, CRO and business leaders measure the world
- Query history and existing analytics assets such as dashboards and notebooks, including the questions analysts and quants already ask
- Example questions, instructions and user feedback that refine responses over time
Behind the scenes, specialized agents interpret the questions, identify the relevant data and metrics, generate queries and return with clear explanations and visualizations. When a question is ambiguous, Genie asks for clarification rather than guessing, and it maintains conversational context so users can refine questions naturally.
All interactions occur within a governed environment, creating a single conversational interface for trusted analytics rather than another isolated tool.
Deep integration with Unity Catalog
- Row- and column-level security ensure users only see the data they are authorized to access.
- It uses the same certified metrics and definitions that dashboards and SQL clients use, so "net interest margin," "exposure" or "combined ratio" mean the same thing everywhere.
- It logs every question and answer for audit, giving risk, compliance and internal audit a complete trail of how insights were generated.
Real world use cases across financial services
Banking and payments
Banks are increasingly shifting from volume-driven operations to intelligence-driven decision making. Genie provides executives, finance teams and relationship managers with a conversational layer over enterprise data.
| Use case | User type | Natural language query examples | Benefits |
|---|
| Real-time financial insights (ChatCFO) | Executive and CFO teams | "How did our margin and liquidity profile change last week by business line?" | Finance teams can explore performance instantly and follow the analysis wherever new questions lead. |
| "Show me cohort behavior for deposits opened during the 2025 rate cycle." |
| Customer 360 | Relationship managers, commercial bankers, customer success teams | "Which small business customers in my portfolio show early signs of stress?" | Results include ranked lists, key drivers and suggested next steps, all based on a unified customer view. |
| "Who is most likely to refinance in the next 90 days given current rate scenarios?" |
| Stress testing and scenario exploration | Risk management, treasury and strategic planning teams | "How would a 200 basis point parallel shift affect our commercial real estate exposure by region?" | Genie surfaces results in language suitable for executive and board conversations. |
| "Show me which segments drive the biggest change in expected loss under Scenario 3." |
Asset managers and investment advisors
Asset managers and investment advisors are moving from analytics-driven insight to agent-driven workflows. Genie supports this shift by turning complex, heavily regulated data estates into a conversational surface for desks, research and compliance.
| Use case | User type | Natural language query examples | Benefits |
|---|
| Research copilot | Equity and credit analysts | "How did spreads and volumes move around last quarter's earnings surprise for this peer set?" | Genie assembles relevant datasets, performs the analysis and generates a narrative analysts can refine for formal research. |
| "Summarize the last six quarters of performance for these issuers versus benchmark." |
| Desk and client analytics | Trading desks and sales teams | "Show today's P&L by strategy, broken down by top 10 clients." | Teams receive immediate insights they can further explore or export into desk reviews. |
| "Which clients saw the largest intraday move in VaR?" |
| Surveillance and conduct insights | Compliance, surveillance and audit teams | "Which traders show unusual patterns in intraday position changes and communications over the last month?" | Genie summarizes patterns across trading activity and communications to help teams prioritize investigations while maintaining full auditability. |
Customer Spotlight: Jefferies modernizes equity research with agentic AI
- Challenge: Research teams manually analyze thousands of companies using dozens of internal and external datasets - pulling together a single investment thesis could take days. That's time analysts didn't have when markets moved.
- Solution: With Genie on Databricks, Jefferies analysts query governed internal and third-party data using natural language, without leaving their existing workflows or relying on data engineering.
- Results: Analysts can now answer complex research questions in minutes instead of days or weeks. And spend more time on investment judgment and less on data retrieval — a fundamental shift in how the team operates.
Insurers
Insurers are navigating climate volatility, changing customer expectations and new business models such as usage-based insurance. Genie helps underwriting, claims and distribution leaders make sense of this complexity.
| Use case | User type | Natural language query examples | Benefits |
|---|
| Portfolio and line-of-business performance | Chief Underwriting Officers (CUOs) and risk committees | "How has our combined ratio evolved for coastal property over the past 12 months, by segment and channel?" | Insights can be used directly in portfolio reviews and steering committees. |
| "Where are loss ratios deteriorating fastest once we adjust for exposure growth?" |
| Distribution analytics | Sales and channel leaders | "Which agents and brokers have the highest quote-to-bind ratio for mid-market commercial?" | Leaders can drill into drivers and outliers without waiting for a new analysis cycle. |
| "Where are we seeing the highest lapse rates by product and geography?" |
| Claims analytics | Claims teams and special investigation units | "Where are we seeing the highest claims leakage by product line?" | Genie helps them identify patterns and bottlenecks that feed into process changes, training and fraud controls. |
| "Show claims with similar characteristics to this case and their outcomes." |
Across banking, capital markets and insurance, the pattern is consistent: trusted data becomes directly accessible to the people closest to customers, markets and risk.
Evidence that the pattern works
Financial institutions are already seeing results from Genie.
- Finance teams are reducing reporting cycles from weeks to minutes by querying governed data directly rather than assembling reports manually.
- Global banks that once required days to run large cohort analyses can now complete the same work in minutes and expose the results to hundreds of self-service users.
- Wealth management firms automating 80-90% of annual client review pack preparation are saving thousands of hours each year while maintaining full lineage to source systems.
- Risk and compliance teams are accelerating regulatory reviews from days to roughly an hour - while preserving complete traceability back to underlying data and policy documentation.
These improvements change more than reporting speed. They fundamentally alter the cadence of decision-making across finance, risk and customer operations.
Genie brings three key traits to financial services in a single experience:
- GOVERNED DATA CONTROL: Operate on governed data with a single control plane.
- CONSISTENT BUSINESS LOGIC: Reuse shared business semantics rather than creating new definitions per tool.
- ACCESSIBLE INSIGHTS: Provide natural language access to executives and practitioners - not just specialists.
Customer Spotlight: Magic Orange turns technology spend data into real-time decisions with Genie
- Challenge: Teams managing complex technology portfolios struggled to analyze massive datasets quickly enough to act on them — relying on manual reporting cycles that slowed financial decisions and obscured cost drivers.
- Solution: Magic Orange uses Genie to query terabytes of financial data in natural language - instantly uncovering trends, variances and cost-saving opportunities.
- Results: Teams can now deliver real-time, actionable insights that improve investment decisions while reducing reliance on expensive BI tools and manual analysis, saving hundreds of thousands annually.
Getting started with Genie in financial services
Start from the conversations that matter
Identify recurring questions executives and frontline teams struggle to answer quickly, such as:
- CFO questions about profitability, liquidity and funding costs
- Desk head questions about trading performance and client activity
- Underwriting or claims leadership questions about loss trends and portfolio exposure
These conversations define the first Genie Spaces your organization should build.
Establish trusted business definitions
Next, ensure the metrics that matter most to your institution are defined centrally. Using Unity Catalog Business Semantics, organizations can:
- Standardize calculations for measures such as NIM, ROE, exposure at default and combined ratio
- Certify dimensions executives rely on, such as product lines, regions and risk grades
- Associate those definitions with the datasets Genie can access
This shared semantic layer ensures consistency across dashboards, reports and conversational analytics.
Launch a few high-impact workflows
Rather than experimenting broadly, focus on several lighthouse use cases:
- Banking and payments: CFO performance cockpit, Relationship manager client-insight workspace
- Capital markets: Research copilot for a key asset class, Trading desk analytics workspace
- Insurance: Portfolio performance monitoring for a priority line of business, Claims analytics for leakage and fraud detection
Track improvements in decision speed, user adoption and reductions in ad-hoc reporting requests.
Build governance into the rollout
From day one, treat governance and evaluation as accelerators, not obstacles:
- Reuse existing data access policies so Genie never bypasses entitlements
- Enable logging so risk and audit teams can review usage
- Encourage user feedback to continuously improve responses
Organizations that implement strong evaluation frameworks often move more AI projects into production because they can demonstrate control and transparency.
Scale with business ownership
- As early Genie spaces prove their value, expand to additional domains. Business owners define the questions, decisions and outcomes that matter.
- Data and analytics teams curate the underlying datasets and semantics.
- Risk and compliance teams validate that policies and logging meet their standards.
Together, they transform Genie from a reporting tool into a new way of interacting with enterprise data.
Customer Spotlight: KPMG Reimagines how to engage data using Genie
- Challenge: Finance and analytics teams struggled to access and analyze operational and financial data quickly, relying on multiple dashboards and manual reporting, which slows strategic decision making.
- Solution: KPMG uses Genie to empower finance and analytics teams to easily query data in natural language, exploring actionable insights directly and interactively.
- Results: Teams now deliver accurate, real-time insights that inform budgeting, forecasting and operational decisions - reducing manual reporting and accelerating business actions across the organization.
See how your teams can move faster with Genie
Genie turns governed data into decisions in minutes. Across financial services, teams are reducing reporting cycles, accelerating decisions and unlocking insights from governed data.
Speak with our industry experts to learn how Databricks helps your teams move from dashboards to decisions in minutes.
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