Bankloch

" Data is the new gold " is a quote often heard, especially in the financial services industry. This sector deals with enormous amounts of extremely valuable data about their customers and handles purely virtual products or services. Thus, data is an essential part of the financial services business. While the value of data is undeniable, data is not a scarce commodity, unlike "gold." Enormous amounts of data are produced daily. For example, the world created around 118 million petabytes in 2023 and is expected to create 463 million petabytes per day by 2025 (for reference, a single petabyte is one million gigabytes). Although storing and processing these vast amounts of data is complex, the true challenge lies in converting this raw (almost infinite) data into actionable insights. This is where " Big Data Analytics " comes into the picture. Data analytics is no longer a nice-to-have for businesses. With financial services companies becoming primarily digi...

Following our previous blog ' Rethinking AML: A Call for Innovation and Efficiency ' ("https://bankloch.blogspot.com/2024/02/rethinking-aml-call-for-innovation-and.html"), where we navigated the complex world of AML and pinpointed three primary   categories of malicious financial activities : Money laundering : Transforming proceeds from illicit activities into seemingly legitimate funds. Sanction bypassing : Circumventing governmental sanctions. Payment Fraud : Exploiting stolen or fake payment details to illicitly acquire goods or funds. Focusing on Payment Fraud, we discern two principal categories:   insider (internal) fraud , conducted from inside an organization by its own staff, and   external fraud , perpetrated by outsiders like customers or suppliers. This blog delves into   external fraud within the financial sector , particularly the unauthorized extraction of customer funds. This subset of "Payment Fraud" can be further split-up in several types...

Expressions like "Data is the new oil" are already becoming a cliché on social media, but there is still a lot of truth to them. Obviously with customer centricity and hyper-personalization increasing, data gets more and more value. However just like raw oil, data in its raw form has little usage. It needs to be cleaned, filtered, structured, matched and enriched, consent needs to be captured from the data owner (via GDPR compliant opt-in requests) and the data needs to be analysed before it can give its value in the form of new (customer) insights. This is where most companies in the financial services sector are facing issues. While collecting and storing raw data is relatively easy, ensuring high quality data sets (avoiding the "Garbage In – Garbage Out" principle) and converting them into insights is a whole different story. Most financial institutions are facing a lot of data quality issues, i.e.   most  of their data is  mostly  right,  most  of the t...

In the corporate world, the usage of Excel files is still enormous. Many business tools are still running in Excel, often extended with VBA macros and applications. As an Excel fan myself, I can relate to that, as nothing else allows in such a short time to build a powerful and flexible tool, adapted to your specific business needs. However as a software engineer, I also see the issues with these decentrally managed business tools built in Excel. Typically there are 4 main issues with these tools, i.e. The   lack of central storage The   lack of collaboration possibilities   offered by Excel (we all tried to work on a shared workbook, but don’t think anyone was really satisfied with the result) The   lack of versioning The   (non-)functional limitations   of a tool like Excel. Numerous examples exist of an Excel tool growing continuously in complexity and size, until one day it becomes impossible to maintain, it becomes unacceptably slow and/or you reach th...