In an era of ever-expanding regulatory frameworks, financial institutions are under constant pressure to comply with stringent anti-fraud regulations. Regulatory Technology (RegTech) has emerged as a game-changer, offering innovative solutions that streamline compliance processes and enhance the effectiveness of fraud prevention measures, reduce risk of human error and enable organisations to better allocate resources.

RegTech tools utilise advanced data analytics, automation and artificial intelligence (AI) to ensure that financial institutions stay ahead of regulatory requirements. These technologies enable real-time monitoring of transactions, automatic generation of compliance reports and proactive identification of potential fraud risks.

One crucial step in detecting, investigating and ultimately preventing fraudulent activity is achieving a single customer view. This is a 360-degree view of the customer, pulling data from multiple sources – eg transaction history, personal information and behavioural data – to provide your organisation with a holistic overview of its customer data. Having this readily available is critical to prevent fraud.

With customer data in one holistic view, fraud management time to resolution accelerates, minimising the risk of data breaches and allowing machine learning to recognise future threats.

Microsoft Dynamics 365’s Customer Engagement platform seamlessly integrates sales, marketing and customer service capabilities to give a full overview of customer activity, preferences and behaviours. Through automated alert flagging using Power Automate, fraud investigators are flagged with any suspicious activity – reducing the risk of human error or manual time delays in fraud responses. This flexible platform allows organisations to integrate it with existing legacy systems as well as enabling third-party integrations to provide full adaptability.

If you would like to learn more about achieving a single customer view, download our free eBook.

Artificial Intelligence (AI) has revolutionised the landscape of fraud prevention, providing institutions with powerful tools to detect and combat increasingly sophisticated fraudulent activities. AI algorithms can analyse vast datasets in real-time, identifying patterns and anomalies that might go unnoticed through traditional methods.

Machine Learning (ML), a subset of AI, enables systems to continuously learn from new data, improving their ability to detect emerging fraud trends. By leveraging AI, financial institutions can implement predictive modelling, anomaly detection and behavioural analytics to stay one step ahead of fraudsters.

Furthermore, AI-powered solutions enhance the accuracy of risk assessments and reduce false positives, enabling institutions to focus their resources on genuine threats. The integration of AI into fraud prevention strategies not only strengthens the defence against existing fraud methods but also ensures adaptability to evolving tactics.

What is unstructured vs structured data?

Unstructured Data: Data in different forms that fall outside of conventional data models or schema. For example, images, audio files and text files.

Structured Data: Data that sits in a standardised, defined format, therefore it is easily searchable and analysable internally for an organisation. For example, Excel files, balance sheets and CRM systems.

Around 80-90% of the world’s data is currently unstructured, from emails, to videos, to social media posts. In the context of Financial Services, unstructured data can hold a wealth of valuable insights on a customer journey – yet it is not readily available to view and analyse to predict behaviours. On top of presenting missed opportunities for personalised communications, this increases the threat of fraudulent activity. A lack of organised data means that data is disparate, hindering the time it takes to resolve fraud cases and preventing a true single customer view.

In 2024, we are looking towards the benefits that AI can bring organisations every day. New AI capabilities within Microsoft’s cutting-edge AI tool, Copilot, mean that AI models are trained to analyse unstructured data types to present greater contextual information. This means pulling in data from emails, individual documents and more to move towards a 360-degree view of the customer. This rapidly increases the rate at which financial institutions can detect fraud.

AI can also be used to transform unstructured to structured data using   data factory, empowering financial institutions with better reporting capabilities and enabling them to use the data in workflow automations.

It is important to note that the emergence of sophisticated AI programs has led to an increase in fraud cases – termed ‘synthetic fraud’ – whereby generative AI has enabled fraudsters to take advantage of identity cloning to con financial institutions and their customers. However, with an effective fraud strategy, airtight multi-factor authentication (MFA) measures and consistent activity monitoring, financial institutions can combat this newfound threat. Let’s find out how…

Financial fraud waits for no one, striking when you least expect it – meaning that it is crucial to always remain vigilant. However, as fraud attempts rise and the Financial Services sector becomes increasingly digital, it can be difficult to respond to growing pressures manually.

Real-time analytics, paired with AI, is an essential tool in detecting and preventing fraud – enabling immediate detection of unusual behaviours and patterns and flagging potential fraud as it happens. AI algorithms within Microsoft Azure employ machine learning to learn from historical data, enhancing predictive capabilities to pre-empt fraudulent activities. Once these activities are spotted, they can automatically be flagged to the correct teams to be actioned using workflow capabilities in Power Automate. From here, these can be visualised within a customer view using PowerBI with powerful graphics and reporting capabilities. By combining the strength of PowerBI, Power Automate and Azure services, your organisation can minimise threats through real-time fraud detection in the Microsoft ecosystem.

In an interconnected digital landscape, financial institutions rely on Application Programming Interfaces (APIs) to facilitate seamless data exchange. Ensuring the security of these APIs is paramount. Employing robust encryption mechanisms for data in transit and at rest adds an extra layer of protection, safeguarding sensitive information from potential breaches.

We’ve only scratched the surface of the factors to consider in fraud prevention – to discover how our Business Applications division, Incremental can support your fraud management and prevention strategy, contact us today. Stay tuned for our final instalment of Fraud24, which explores key considerations in selecting the right digital transformation partner.