Technology driven fight against financial crime

05 April, 2022

Over the last few years, PwC has had the privilege to work with multiple clients to deploy various technologies to prevent financial crime, such as machine learning models and cloud-based solutions.

PwC had observed that properly deployed technology can reduce the overall cost of compliance by as much as 30 - 50%1 by reducing the handling time and increasing the quality (thus reducing reworks).

In this article we would like to outline some interesting use cases, primarily in the context of Know Your Customer (KYC) and Transaction Monitoring (TM), although they may be applicable to any regulatory compliance process.

1. Flexible workflow

The heart of successful regulatory operations involving highly complex processes, is a reliant and flexible workflow. Tools with the ability to support a range of financial crime areas including KYC, TM alert review, data enrichment or data remediation, lay a solid foundation to build advanced and efficient processes. Flexibility to align with already existing systems is essential.

2. Reporting services

Well-designed reporting is crucial for effective project management and key performance indicators (KPI) monitoring. Building automated and useful reporting is best achieved when designed and delivered together with a workflow solution.

Reporting services provide live, interactive data visuals with the ability to drill down into details. They can be accessed anytime from web or mobile devices enabling real-time decision making and empowering both tactical and strategic solutions.

More advanced compliance departments may use data for advanced analytics and intelligence.

3. Data driven Business & Process intelligence 

Data collected during KYC/AML processes can be an input for further business intelligence tools, enabling the calculation of efficiency KPIs, fine tuning capacity, the measurement of processing time for individual tasks or visualisation of the whole process to identify inefficiencies and bottle necks. 

Additionally, Machine Learning can be deployed for ongoing monitoring of changes to customer Anti-Money Laundering (AML) profiles and trigger appropriate follow up actions.

4. Smart forms and client portal

Smart forms can be the backbone of an effective process by integrating multiple automations and serving as an interface for the user to easily access them. 

These forms can be integrated with client portals to enable an efficient exchange of data and documents with the clients in a more secure and structured manner. 

5. TM Scenarios

For TM scenarios PwC sees a big opportunity in supplementing a rule-based approach with advanced data analytics tools. Fueled with AI and machine learning algorithms, these tools can analyse multiple sources of information about the customer and their transactions. This can enable the automated disposition of false positive alerts while also identifying true suspicious activities which are not captured by simple rules.

6. Knowledge sharing

Efficient knowledge management is often neglected in regulatory compliance processes. Many organizations underestimate the operational difficulties caused by increasing scale, complexity and pace of change of procedures and processes.

There are three layers of an effective KM system:

  • A well-structured knowledge platform that includes all key documents and proper tagging

  • An intelligent search engine that displays the most relevant results. Many organizations are taking one step further and experimenting with intelligent chatbots/ virtual assistants.

  • A ticketing system in which users can submit queries to a senior specialist in instances where they cannot find the response themselves. All replies are stored for future reference, which may reduce the number of similar queries in the future and enhances standardization

7. Data gathering and data extraction solutions

By leveraging machine learning, biometrics, and AI capabilities, identity verification can be automated to enhance efficiency and accuracy for customer onboarding and authentication processes. Use of automated identity verification for onboarding and outreach for retail clients has become a market standard. 

Regulatory compliance processes require usage of many external and internal sources. There is a large volume of data and information on the market and that data needs to be extracted, standardized, verified and prioritized. Applying smart and automated data sourcing is necessary to set up an effective remediation process.

8. Automated Screening

Adverse media and/ or sanctions/ Politically Exposed Person screening are time consuming and error-prone tasks. Majority hits may be false positives. Artificial Intelligence (AI), Machine Learning and Cognitive Analytics enable streamlining screening against negative news, PEP status or sanctions, with either automated dispositioning or routing the hit for a manual review and highlighting key information to support the human decision-making process. These technologies may also facilitate a more thorough due diligence by expanding the depth and breadth of sources being used.

9. Quality reporting and predictive sampling

Comprehensive and granular quality measurement and reporting (based upon quality checks) allows for monitoring and prompt action to be taken to avoid regulatory fails or time-consuming reworks post completion. Reliable, quality data lays the foundation for predictive sampling, where AI/ machine learning algorithms are used to introduce a targeted, risk-based approach to quality checks. 

10. Risk rating modeling

Machine Learning and advanced technologies can be leveraged to derive AML Customer Risk Ratings using the data gathered during KYC processes. The advanced capabilities serve as the backbone of these models and allow for more accurate AML ratings. These can serve as the basis for identifying high risk customers and the ongoing monitoring processes to mitigate AML risk.

Additionally, automation of time-consuming configuration and calculation processes of risk rating models may allow AML Compliance Officers to focus their attention on the interpretation of results and engagement in risk mitigating activities. This, in turn, supports agile and in-depth verification of internal AML standards implementation through the customer risk lens.  Implementation of such tools can also bring significant time savings on the compliance side.

The group of solutions outlined above is just a sample of what PwC sees being used by automation frontrunners.  They can be further supplemented and enable concepts such as straight-through processing (STP) and Perpetual Know Your Customer (PKYC).

1 - PwC analysis

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