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Using multi-channel solutions to prevent open finance fraud

We have been applying analytics, artificial intelligence (AI) and machine learning (ML) to fraud prevention solutions for over 20 years. Over this time, the financial services sector has completely transformed, with firms seeking to move away from siloed and disjointed datasets, rapidly digitising and turning to the cloud. 

But how has this impacted their ability to detect, track and prevent fraud? 

The rise of open finance 

Open finance is defined as a data-sharing model that allows users to share their financial data, digitally, with third parties. It’s the next step after open banking, a movement which established the rules that allowed individuals to share their banking information with third parties through Application Programming Interfaces (APIs). 

These data sharing models have provided a safe channel for consumers and businesses to easily share their banking information with other companies – provided there was the necessary consent. Over time, this has helped companies to better understand their customers, and target them with products and services tailored to their specific needs. 

In addition, the benefits of the open finance revolution aren’t confined to the financial services sector. The data can be collated and shared with other digital players such as big-tech companies, fintechs, or gig economy platforms, as well as traditional entities such as fiscal institutions, insurance firms, retailers, and even utility providers. 

More convenience, more risk

However, this added convenience has led to greater risk. Fraudsters will always seek out new ways to exploit private financial information and the rise of open finance brings three key risks:

  • The first is cyber-attacks. An open finance ecosystem may include various players such as data providers, third-party providers, customers, regulators and government agencies. That’s a lot of potential points of failure for data security and fraudsters are adept at targeting the weakest link in a chain.

  • The second risk is social engineering and new scams. As we know, accessing banking information is the holy grail for fraudsters. They are adept at mining every account they infiltrate for personal information as well as currency, reward points or crypto.

In the context of account takeover fraud (ATO), the problem of linked accounts via open finance is evident. Losing control of one account could mean losing much more for customers. Their ID documents or card numbers could end up on the dark web, where they will fuel synthetic identity fraud transactions.

  • The third risk is around customer experience. Firms need to be certain that it is the account holder making a payment, however repeatedly blocking activity or suspending an account may negatively impact customer experience. With analytics intelligence, businesses can build an in-depth understanding of their customers’ behavioural information, transaction history and geolocation, allowing them to easily separate their customer from a fraudster and prevent fraudulent activity. 

Detecting, preventing and managing fraud

For banks, deploying software that can effectively ​​detect, prevent and manage fraud across the enterprise in real-time and from a single platform, is essential. 

There are three core priorities that banks need to balance: 

  • Customer service

  • Reducing fraud rates

  • Minimising operational overheads.

Balancing these three priorities requires analytics-driven tools and technologies. Fraud managers are very much aware of the need to balance fraud losses with customer experience and operational overheads. Business managers and marketing teams, on the other hand, often underestimate or fail to appreciate the fraud risks and can get wrapped up in the excitement of a new product or service launch. As products are rushed to market, it’s tempting to remove or down-scope some of the fraud controls. 

It’s essential to foster a collaborative working relationship with teams across the business, implementing fraud controls that fit with the organisation’s overall IT architecture and strategy. 

Through the deployment of our fraud management software, businesses can effectively stay on top of the ever-changing and evolving tactics used by fraudsters. At the same time, customer data will not be compromised, nor will their overall experience. 

 

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This post is from a series of posts in the group:

Artificial Intelligence and Financial Services

Artificial Intelligence and Financial Services


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