Challenges FinTech Companies Face With Scam & Fraud Detection Tools
Reviewing Major Concerns
Introduction Because of the uptick in the amount of digital transactions happening on a daily basis, FinTech companies offering their services to business and customers must exercise caution and take steps to prevent scams and fraud. As reviewed. cybercriminals are constantly innovating and looking for new ways to defraud people. Therefore, FinTech companies must walk the extra mile to ensure that the critical information and financial assets of their clients aren’t compromised.
The Problem However, the rigorous implementation of anti-scam practices and adoption of fraud prevention tools bring with them a set of novel challenges that have the potential to hinder business growth. In this presentation, we will review some of them in detail.
1. Constantly Evolving Scam & Fraud Practices This is a difficult subject to nail. Scammers and spammers continuously tweak their methods to ensure that they are not caught. Because of this, FinTech businesses have to allocate a significant percentage of their budget towards fraud prevention and anti-spam practices. This involves embracing machine learning models and AI tools that are by no means cheap. Existing methodologies and tech too, have to be constantly updated to boost cybersecurity of the company as well as its customers. In addition to this, employees have to be trained to keep up. Failure to do so may not only expose them to threats but also cause a huge blow to their reputation, if hackers do end up taking over.
2. Hindrance To Customers Out of the total number of customers availing a FinTech company’s services, only a small chunk of them may have malicious intent. However, every company has to deploy resources and thousands of dollars to keep them at bay.
Here, it is important to note that the anti-spam tools and tech to prevent fake transactions may pose to be elements of frustration for customers who simply want to conduct a particular action quickly. Too many security blocks may result in the user experience getting affected in the long run.
3. Vague Results As reviewed by many FinTech analysts, many fraud prevention tools come with major limitations. For instance, some may not be able to walk personnel through the reasons why a particular usage of a digital wallet is questionable. Similarly, AI tools may not assess issues on a case-by-case basis. Rather, it will deploy algorithms to check whether a particular customer is likely to engage in fraud based on markers that may be outdated or even racially biased.
Solutions ● Embracing AI tools that don’t simply generate results but also include explainability features to demonstrate how it got to a particular conclusion. ● Humans working in tandem with fraud and scam prevention tech.
THANK YOU! Presented & Reviewed By: Vinayak Joshi, Manager, Money 2.0 Conference https://www.money2conf.com/