https://ryanorban.com/categories/banking/Recent content in Banking on Ryan OrbanHugoen-usme@ryanorban.com (Ryan Orban)me@ryanorban.com (Ryan Orban)Ryan OrbanFri, 01 Apr 2022 00:00:00 +0000https://ryanorban.com/notes/ntropy-transaction-categorization/Fri, 01 Apr 2022 00:00:00 +0000me@ryanorban.com (Ryan Orban)https://ryanorban.com/notes/ntropy-transaction-categorization/<h3 id="summary" class="scroll-mt-8 group"> Summary <a href="#summary" class="no-underline hidden opacity-50 hover:opacity-100 !text-inherit group-hover:inline-block" aria-hidden="true" title="Link to this heading" tabindex="-1"> <svg xmlns="http://www.w3.org/2000/svg" width="16" height="16" fill="none" stroke="currentColor" stroke-linecap="round" stroke-linejoin="round" stroke-width="2" class="lucide lucide-link w-4 h-4 block" viewBox="0 0 24 24" > <path d="M10 13a5 5 0 0 0 7.54.54l3-3a5 5 0 0 0-7.07-7.07l-1.72 1.71" /> <path d="M14 11a5 5 0 0 0-7.54-.54l-3 3a5 5 0 0 0 7.07 7.07l1.71-1.71" /> </svg> </a> </h3> <p>Ntropy is a fintech API for cleaning and enriching raw banking transaction data. The core problem: raw bank transaction strings are a mess — &ldquo;SQ *COFFEE SHOP 12345 PORTLAND OR&rdquo; means something to a human but is opaque to any system trying to categorize spending or identify merchants. Ntropy&rsquo;s ML pipeline normalizes these strings into structured data: canonical merchant name, category, subcategory, merchant logo, website, and enriched metadata. This is the missing data layer between raw bank feeds (via Plaid or direct connections) and financial applications that need to understand what users are spending.</p>