Financial institutions have invested significantly in financial crime prevention technology. Additional ongoing funding is required for the financial crime operations team. However, the amount of incurred costs is not a measure of the bank’s ability to identify the financial crime activities of their clients. Insufficient risk coverage, unmonitored transaction subsets, incorrectly calibrated scenarios, or a high number of false-positive alerts are all indicators that the financial crime technology system has not been set up in an efficient manner. We look in more detail at challenges faced by financial institutions and how Financial Crime Analytics, provided as a Service, can resolve these challenges - not just on a one-off basis, but on an ongoing basis.

Our experience shows that 85% of financial institutions face challenges in making adequate use of financial crime technology tools and in fully leveraging the effectiveness and risk identification benefits these tools offer. Moreover, most institutions underutilise their technology - we often see situations where only 60% or less of available functionalities are utilised thus leading to the valuable time of the AML team being wasted. All these combined - the costs of inefficiency - result in spending rising to 40-50% of the total cost of compliance. Our observations backed by a recent study by Forrester found that 73% of respondents were engaging or were imminently planning to engage external data and analytics support.  Some of the categories which require significant analytics deployments are:

  • Optimisation and maintenance – Our experience shows that 8 out of 10 financial institutions do not perform adequate ongoing financial crime technology optimisation. In many cases, no appropriate quantitative analysis is performed, and annual threshold reviews often take the form of a purely administrative approval of maintaining the same rules and thresholds as in the prior year. Such an approach falls short of regulatory expectations and sets up organisations for potential regulatory enforcement actions. The same lax approach is applied to risk-based segmentation and other aspects of the monitoring environment. Moreover, institutions are unable to leverage the knowledge from past alert investigations to help decrease the number of irrelevant alerts going forward.
  • Risk coverage and emerging threats – In line with a requirement to have a risk-based approach to financial crime prevention and supporting controls, financial institutions need to regularly review the risk coverage provided by the deployed technology tools. This ranges from products and service channels that are being monitored through these automated tools, to the actual typologies and red flags an institution is monitoring against. Without analytics (e.g. Latent Dirichlet Allocation for emerging risks identification), this coverage matches, at best, 60-70% to the institution’s respective risk exposure.
  • Functionality – As the technological capability and functionality of these tools have progressed, many financial institutions have been slow to adequately implement them into practice. This has resulted in tools operating in the same fashion they were introduced many years ago, often without adequate tuning and optimisation considerations.
  • Data quality and availability – With an often-complex set of data processing activities taking place between different internal and external systems, data quality and availability can be sub-optimal to the running of selected rules and scenarios. In prior client work we identified cases where selected material data inputs have not been fed into the AML/sanctions/fraud tool resulting in no monitoring against selected rules without the organisation’s knowledge.

To address these and other related challenges, a combined skill set of AML/fraud subject matter expertise, data science, specific products and scalable technology is required. And Financial Crime Analytics as a Service provides just that!

PwC’s Financial Crime Analytics as a Service

By engaging Financial Crime Analytics as a Service, institutions achieve a tailored and fit-for-purpose approach to their financial crime technology optimisation. Tuning tools and technology in a risk-based, cost-efficient manner requires expert knowledge, relevant software and applied experience; and all of these across financial crime compliance, technology and data analytics, a combination seldomly available within financial institutions. Financial Crime Analytics as a Service delivers continuous system optimisation administered and executed by PwC resulting in a number of client benefits –

  • Worry-free ongoing, long-term managed technology optimisation service
  • Ongoing balancing of a tool’s effectiveness (improving risk coverage) and efficiency (significantly reducing false positives)
  • A structured approach following a defined and tailored methodology aligned with regulatory expectations
  • Continuous access to proprietary applications developed specifically for AML/sanctions/fraud systems and tool optimisation
  • Ongoing monitoring and coverage of the latest AML red flags and financial crime typologies
  • Provision of supportive documentation with all relevant details
  • Implementation support of the configuration changes and associated testing
  • No need for building own dedicated data science team focusing on financial crime
  • Having skilled technology people at hand when performing updates and upgrades of systems or deployment of new detection scenarios and algorithms
  • Ability to deploy AI models for anomaly detection, network analytics and other advanced monitoring approaches extending the reach of traditional rule-based systems

Our Financial Crime Analytics Team  employs purpose-built technology combined with relevant subject-matter knowledge to deliver continuous Financial Crime Analytics as a Service to our clients.

Our clients' recent success stories

Too often we see the same challenges. The same business needs of Compliance teams, the same technology gaps. Financial Crime Analytics, provided as a Service, can resolve these challenges. Not just having a one-off effect, but continuous. Our clients' recent experience speaks for itself:

  • Optimisation of AML transaction monitoring, including new behavioural segmentation model, risk-based thresholds tuning, led to a 50% decrease in the volume of false positives. This resulted in the freeing up of resources to support the introduction of additional monitoring scenarios and other initiatives. The client also decided to retain us for subsequent periodic optimisation of their AML monitoring tool for the next 3 years.
  • A review of a client’s transaction monitoring tool and deployed monitoring scenarios resulted in a recommendation to introduce more than 10 additional scenarios to adequately cover products, customer types and distribution channels. PwC is currently supporting the client in testing the use of NLP technologies for ongoing typologies assessment.
  • Assisted a client to reduce false-positive alerts from their sanctions screening solution by more than 60% during year 1 with ongoing calibration in subsequent years, utilizing PwC’s testing and optimization platform supported by a dedicated data science team.
  • An assessment of a client’s sanction screening solution identified a number of efficiency enhancements allowing for a reduction in the number of false-positive alerts by over 49% in year 1. Supported the client in initial optimisation of their sanction filtering tool in alignment with their risk appetite. Periodic sanction solution optimisation as a service agreed going forward.

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