Fighting fraud: How to enhance financial crime prevention without breaking the bank

Financial crime is on the rise, and it is costing billions. New research shows UK financial services organisations are collectively spending £34.2 billion each year on financial crime compliance, up 19% since 2020.

In response, new reforms are being introduced by regulators working to shift the dial on the fight against financial crime. Just last year, the UK published its Economic Crime Plan 2 (ECP2), which commits the Government to a number of measures, including reducing money laundering, sanctions evasion and fraud. Europe is also introducing stricter regulations. In May this year, the EU Parliament introduced new regulations to combat money laundering and terrorist financing.

What does all this mean for banks?

While tighter regulatory controls are needed, it means the pressure on banks is intensifying. To protect customers and mitigate commercial risks in today’s landscape, banks need to be able to identify and prevent illicit activity faster.

The problem is that financial crime is constantly evolving. Criminals are increasingly sophisticated with their attacks, and regulators are imposing tougher penalties on banks and financial institutions for non-compliance and due diligence failings.

The rapid adoption of instant payments and emergence of new technologies like generative artificial intelligence (Gen AI) further raises the stakes. It means that new ways must be found to stay one step ahead of the criminals – and the regulators – by enhancing existing anti-financial crime capabilities, and future-proofing systems to react and respond to future, unforeseen threats.

Why a new approach is needed

For the most part, fraud and financial crime systems have not been built with future events in mind. The have mainly evolved reactively over the years, with piecemeal changes implemented to stay compliant and deal with specific fraud vectors and crime scenarios.

As a result, many banks are burdened by anti-financial crime systems that are extremely fragmented. This siloed approach is creating significant inefficiencies. In most cases, fraud and financial crime systems are implemented at a divisional or channel level rather than an enterprise level, meaning multiple applications are providing similar or even duplicated capabilities to support processes like onboarding, customer identification and validation.

It also makes it difficult to gain a 360° view of customer profiles, thereby limiting the ability to effectively enforce customer-level risk policies and increasing the risk that fraud and financial crime will go undetected. Clearly a new approach is needed.

How can enterprise level services transform anti-financial crime capabilities?

To protect customers, as well as their own bottom line and reputation, banks need to make appropriate use of cutting-edge technologies to continually develop their anti-financial crime capabilities.

Achieving this flexibility requires a shift away from siloed systems towards enterprise-level services that combine advanced analytics and machine-learning algorithms. This involves developing a set of common fraud and financial crime services that can be consumed across the bank. The services should use and propagate a consolidated, domain-specific data set, making data readily available across other systems and teams.

Through this consolidated approach, banks can streamline fraud and financial crime operations, improving efficiency, performance, and responsiveness. It also makes it possible to optimise the use of data, moving further towards real-time data-driven architectures that increase responsiveness and remove dependencies on batch processing cycles and periodic reviews.

Data sharing and data-driven architecture

Moving away from data silos and creating enterprise repositories enriched with data from external sources (both government and commercial agencies) will provide stakeholders with ready access to a trusted source of data with well-defined lineage, spanning the fraud and financial crime domains.

Data and new technologies are key to the transition, and the recommended architectural improvements position banks to take advantage. For example, opportunities are available to leverage the growth in Gen AI and data science capabilities, through the development of machine learning fraud detection models, which reduce the reliance on 3rd party-developed models (often expensive and sub-optimal) and enable improved screening results: fewer false positives and less customer friction.

The benefits of an end-to-end architecture

To enable financial crime processes and services to continually assess risks and respond faster to changes happening across the bank, solutions must be designed and developed across organisational boundaries, using standard patterns and shared technologies, as part of a common, integrated, architectural approach.

Banks can then use the increased responsiveness to drive operational efficiencies and cost savings. It also enables the elusive 360° view of customers, facilitating data sharing across systems to realise synergies across financial crime and fraud operational teams.

By adopting this holistic approach – encompassing people, technology and processes – banks can unlock the true effectiveness of fraud, Know Your Customer (KYC), anti-money laundering (AML) and sanctions systems. For larger banks, it could also open up new revenue streams, by making it possible to package and offer financial crime and fraud services to corporate customers and agency banks through the use of open and secure APIs.

The adoption of an event-driven model

Moving away from a diarised schedule of batch processing to a more responsive event-driven model enables financial crime processes and services to detect, assess and respond to both transactions and customer changes in a more real-time manner (and be more proactive) to prevent financial crime and fraud before they occur.

This requires the organisation to adopt specific architecture, processes, services and technologies appropriate for handling events as and when they occur and build more insightful customer profiles. This in turn can be used to understand the customer journey better and adapt where necessary, leading to an improvement in performance analytics of financial crime indicators.

Application consolidation and common IT architecture

Often banks have implemented fraud and financial crime systems at a divisional rather than  enterprise-level, providing similar or even duplicated capabilities to support processes such as onboarding, customer identification, validation, payment request and payment fulfilment.

Furthermore, when we consider various product and core banking systems, we see that banks implement different solutions to provide the same fraud screening capability across a number of products, e.g. credit cards, debit cards and online payments. The picture can be further complicated where larger institutions offer correspondent and agency bank services.

The aim is to develop a set of common fraud and financial crime services that can be consumed across the enterprise and which use and propagate a consolidated, domain-specific data set, making consistent data readily available through governed data products and APIs.

Ensuring transformation happens safely

While the benefits are compelling, a large-scale transformation does not come without challenges. The risks associated with transforming business-critical solutions are significant and must be carefully managed.

Icon Solutions has delivered anti-financial crime solutions for some of the world’s largest financial organisations. This means we are uniquely positioned to help banks architect, develop and deploy new services safely.

Whether you need help with your technology strategy / roadmap, architecture delivery, or both, get in touch to see how we can help accelerate the transformation of your anti-financial crime capabilities.