Fintel AnalyticsNeobank Analytics: Build the Data Stack That Scales in 2026
Most neobanks scale their product long before they scale their data. Here's how to build the analytics stack that actually supports growth, profitability, and investor scrutiny.
Fintel Analytics blog
Data & AI Insights
Expert perspectives on data analytics, AI agents, internal tools, and business intelligence from the Fintel Analytics team.
26 of 206 posts
Investor Due Diligence Analytics: Build a Data Stack That Survives the Process
When investors open your data room, what they find — or fail to find — can make or break your round. Here is how to build an analytics stack that holds up under scrutiny.
Why Your Data Stack Breaks Under VC Due Diligence (And How to Fix It Before Your Series A)
Most early-stage data stacks look fine until a VC opens a data room request. Here's what breaks, why it costs founders term sheets, and how to fix it.
Settlement Timing Analytics: Fix Your Post-Trade Data Stack
Settlement timing analytics tell you exactly where your post-trade process breaks down — before regulators or counterparties do. Here is how to build the data stack that survives T+1.
BaaS Analytics: Build the Data Stack Behind Embedded Banking
Most BaaS-powered products ship fast but build no analytics layer. Here's how to fix that — and what it costs you if you don't.
Acquirer Analytics: Build the Data Stack That Wins in 2026
Most acquirers are flying blind on the metrics that matter most. Here is how to build the internal analytics stack that turns transaction data into competitive edge.
Stablecoin Payments Analytics: Build the Data Stack That Works
Stablecoin payment volumes are exploding — but the data infrastructure most fintechs are running is not built for on-chain flows. Here is how to fix that.
PSP Data Analytics: Build Intelligence Into Your Payment Stack
Most fintechs track whether payments succeed or fail — but few build analytics that reveal why. This guide shows how to unlock real intelligence from your PSP data layer.
Virtual IBAN Analytics: Fix Broken vIBAN Data in 2026
Virtual IBANs promise automated reconciliation — but the data stack behind them is usually broken. Here is how to fix it before it costs you.
Crypto Exchange Analytics: Build the Data Stack That Scales
Most crypto exchanges generate enormous volumes of data but operate with surprisingly immature internal analytics. Here's how to fix that — from fee revenue modelling to liquidity dashboards.
Partner Revenue Analytics for Fintech: Build Real Visibility
Fintech platforms with partner ecosystems rarely have clean visibility into how revenue is split, earned, and reconciled. Here is how to fix that with a proper data stack.
FX Exposure Analytics for Fintech: Stop Flying Blind on Currency Risk
Most fintech startups have no real-time visibility into their FX exposure — only spreadsheets and gut feel. Here's how to fix that before it costs you.
Intraday Liquidity Analytics for Fintech: Build Real Visibility
Most fintech treasury teams are managing intraday liquidity from delayed reports and spreadsheets. Here is how to build the data stack that gives you real-time visibility — and why it matters more than ever in 2026.
Loan Portfolio Analytics for Fintech Lenders: Build It Right in 2026
Most fintech lenders drown in loan data but lack a single trusted view of portfolio performance. Here's how to build the analytics stack that actually works.
Network Token Analytics: Fix Your Payment Performance Data
Network tokens promise higher auth rates and lower fraud — but most fintechs can't measure whether they're delivering. Here's how to build the analytics layer that proves it.
Revenue-Based Financing Analytics: Build the Data Stack That Scales
Revenue-based financing is growing fast — but most RBF platforms are flying blind on portfolio risk, repayment performance, and unit economics. Here is how to fix that.
Credit Risk Analytics for Fintech Lenders: Build It Right in 2026
Most fintech lenders don't have a modelling problem — they have a data infrastructure problem. Here's how to build the analytics stack that credit risk decisions actually depend on.
Usage-Based Billing Analytics: Fix Your Revenue Data in 2026
Usage-based billing creates complex revenue data that breaks most standard analytics stacks. Here is how to build the data layer that actually works.
Dispute Operations Analytics for Fintech: Build It Right in 2026
Most fintech dispute teams are drowning in volume with no analytics stack to manage it. Here is how to build one that actually works.
Fintech Burn Rate Analytics: Build Real Visibility in 2026
Most fintechs track burn rate in a spreadsheet — until it breaks. Here's how to build a real analytics stack that gives finance and leadership actual visibility.
Multi-Currency Analytics: Fix Broken Financials in 2026
Multi-currency analytics is one of the most underengineered problems in fintech data stacks. This guide shows how to fix it before it costs you real money.
Card Programme Analytics: Build Intelligence Into Your Issuing Stack
Most fintech card issuers are flying blind. They know their card is live — but they don't know why authorisation rates dropped, which spend categories drive interchange, or which cardholders are drifting to a competitor.
Payment Gateway Routing Analytics: Fix Your Routing Blind Spots
Most fintechs run multi-gateway stacks but have no analytics layer to tell them whether their routing logic is working. Here's how to fix that.
Chargeback Dispute Analytics: Stop Flying Blind on Losses
Chargebacks are no longer just a cost of doing business — they are a data problem. Here is how to build the analytics stack that turns dispute losses into managed, measurable outcomes.
Authorization Rate Analytics: Fix Declining Payments in 2026
Poor authorization rates silently drain revenue from payment businesses. This guide shows exactly how to build the analytics stack to diagnose, monitor, and fix them.
Embedded Finance Analytics: Build Intelligence Into Your Platform
Embedding financial products into your platform is one thing. Measuring whether they're working — and why — is another problem entirely. Here's how to build the analytics stack your embedded finance operation actually needs.