I was part of the Evolve Bank & Trust data breach which affected me as a Wise customer.
Every data breach is regrettable, but this one, involving a regulated financial institution, is even more concerning.
I've written a post about what steps I will be taking, and everyone should consider, to protect themselves against cybercriminals and financial fraud.
Let me know if you have any suggestions of what else customers could be doing to prevent fraud.
https://isitbankholiday.com/14-june-2024
Hi all, made a tiny website in Jekyll that tells you if the current date is a bank holiday in England and Wales.It leverages the Gov UK Bank Holidays API (https://www.api.gov.uk/gds/bank-holidays/), runs a script once a day and creates the static files for each day available in the API (see https://isitbankholiday.com/sitemap.xml).The site is then deployed to Cloudflare Pages, where a CF Pages...
The average response time for this endpoint is ~200ms, and we guarantee this latency for up to 100 requests per minute.
In production we currently handle ~1 million transactions a day with no problem.
Does this answer your question?
Yes, we match the raw string to a merchant with extra static fields (URL, icon, logo, Merchant Category Code).
In our mind, merchant enrichment unlocks many possibilities. The most obvious one is to have a nice and modern bank transaction feed. But our customers also use us to lock company cards to particular merchants, group by merchants to see where people are spending the most, and more. Would love to hear if you had other "step 2"s in mind!
Our new approach consists of using custom Natural Language Processing and Named Entity Recognition models to predict a) what substring of a bank transaction string represents a merchant e.g. "FACEBK" and b) which canonical merchant e.g. "Facebook" this substring corresponds to in our merchant DB.
The toughest steps were to manually label thousands of bank transactions very carefully to use as training data, and to deploy the models in a production env where we need API response times to be under 200ms (usually what's required in order to incorporate this API in a payment auth flow).
We always optimize for accuracy (>99% currently), because we never want to return an incorrect merchant, but with this new approach our coverage is now at 80% of all bank transactions we see through our system.
We would love any feedback and comments, and also happy to answer any questions about the product or how we productionized it!