How can we drive collaboration and reduce financial crime?

With the social and economic consequences of financial crime worsening, the private and public sector need to come together and share data to track and understand financial crime in real time. In our latest research report, Partners Against Crime, we explored how to drive greater private-public sector collaboration and how smarter use of technology should be the driving force behind this change. The right response to the challenge can help build trust in the financial sector and rid societies and global economies of a persistent menace. So how can we get started?

Better use of data

Data is the lynchpin that can draw organisations together. In our recent webinar with UK Finance, just over 45 per cent of the audience agreed that reusing analysis and intelligence from other financial institutions is key to fostering collaboration. Organisations should invest in a central communication hub that enables greater data sharing, allowing them to anonymously compare and match financial crime data in a controlled and auditable environment. Where matches arise, organisations can legally share intelligence with each other. With the right balance between data sharing and data protection, this approach offers the ability to identify repeat offenders, increase asset retrievals and improve prosecution rates.

Overcoming the barriers

Almost half of the webinar audience agreed data sharing standards are a priority to improve collaboration. A flexible financial crime data and information sharing model would allow a collective and proactive response to financial crime, with minimal impact on genuine customers. It would clarify what data can be shared, between whom, and when, as well as completeness requirements and data access rights. These standards would need to meet the needs of the evolving market place, and enforced by a governance body that monitors and acts to ensure compliance. Our regulatory experience tells us this role could eventually fall within the mandate of the UK’s National Economic Crime Centre (NECC), supported by an open and collaborative approach from financial institutions and technology providers.

Deeper analysis of data with more sophisticated technology

Finally, this uniform and automated approach requires advanced analytics capabilities and/or some form of partnership with specialist RegTech (regulatory technology) firms. The results showed that almost 60 per cent of firms are either assessing this possibility or actively engaging with technology providers. The transition to this model requires attention on several fronts:

•         - culture: both private and public sector will need to learn to work with firms that are much smaller yet more proficient in data analytics. As firms iterate new forms of analysis, they should communicate their discoveries through the NECC to reach agreement on the data to be shared and the technology needed to pool and analyse it 

•         - intelligence-driven: the goal should be to shift risk identification from predictive models to forward-looking analytics built on well-founded indicators of crime. This creates the means to spot broader patterns of suspicious behaviour – such as campaigns by criminal networks as opposed to lone fraudsters
   
•         - organisation: building an effective analytics organisation requires deep functional expertise and strategic partnerships. A wider ecosystem of partners can enable access to data and technology, widen talent pools and foster co-developed analytics capabilities.

As money-laundering schemes grow more sophisticated, the public and private sector will have no viable choice other than pooling their data and reaching out to RegTech specialists to create more powerful analytical models. By following the advice above, these firms have an opportunity to upgrade their crime detecting and crime fighting capabilities – strengthening their systems and creating greater public trust in the financial industry.

Click here to read PA Consulting's latest report, 'A Tangled Web: Rethinking the approach to online CSEA'