Institute Insights - Anti-financial crime functions need to embrace a data-centric approach

Anti-financial crime functions face a significant challenge over the coming years: helping to guide their organisations to become both more efficient and effective in tackling financial crime. In order to achieve this, it is critical for data to be a fundamental enabler within the anti-financial crime toolkit. This will require a significant change, or dare I say it, a transformation for many organisations.

There has been a huge amount of change over the last 10 years, including waves of new regulation, increased regulatory scrutiny, constantly evolving financial crime threats and typologies, new technologies and providers, changing customer expectations, and challenging cost environments. Despite all of the effort and money spent, most organisations would still not consider their measures particularly efficient or effective; the primary goal of many is simply to ensure they are adhering to the mandatory requirements. In order to address a growing workload, most have increased the size of their teams – an option that is no longer available to many with renewed scrutiny on the cost base.

Data (and management of data) is critical across every element of the financial crime spectrum: from collection of customer information during onboarding; monitoring the behaviour of your customer throughout the lifecycle; monitoring transactions; managing internal processes; conducting investigations; and providing management information. Data is at the heart of everything. The challenge facing organisations is that data has been an afterthought in the design of the financial crime approach.

To a large extent, most organisations have adopted a process-driven approach, tackling the challenge through the lens of completing discrete tasks - such as client onboarding, KYC, Screening, ID&V, AML monitoring, investigations etc. This aligns with traditional organisational design thinking and leads the organisation to structure themselves in a process-oriented way. The challenge from a financial crime prevention perspective is two-fold: (1) many of the processes, by nature, are not linear so do not always align with this traditional structure; and (2) financial crime prevention is predicated on bringing together multiple data points to see the whole picture in order to make more effective and efficient decisions.

Very few organisations have a high quality, aggregated view of their financial crime data, within a well governed data environment. Even fewer have been able to move past these foundational steps to be able to properly embrace the possibilities of machine learning. We see today that the most advanced organisations have focussed on putting the foundational steps in place, bringing together multiple data sets relating to all facets of financial crime and use analysis techniques (such as machine learning), to review threats and aid with the automation, for example, of the removal of false positives.

Many organisations are thinking carefully about how they can transform their use of data to support more efficient and effective anti-financial crime processes. We recommend some critical steps to support organisations as embark on this type of transformation:

• Define a clear data strategy including an overall vision and plan
• Translate your strategy into specific use cases and prioritise them according to your business goals – aim to take an iterative approach to help deliver quick wins and gain traction
• Establish a clear view of your current state (systems, customer data, operational data etc.)
• Design your future data architecture based on your existing (& planned) business use cases)
• Asses the current skills and capabilities within the organisation and any gaps that will be needed to support the transformation
• Establish robust data governance to support high data quality
• Build a data-centric culture and adapt your organisation structure to enable and embed the change over time

Like any transformation, a number of steps will be required on the way to delivering a vision state and the exact steps required will be highly dependent on factors such as maturity, culture and current state. The important message is to ‘get going’ on this journey, as data is and will be the key to solving both efficiency and effectiveness challenges that face anti-financial crime functions.

Beyond is a specialist consultancy focused on helping Financial Institutions accelerate business, digital & data transformation in areas such as client onboarding, client lifecycle management and financial crime compliance.