With the current volatile geopolitical, social and economic environments, financial service providers and other financial institutions (e.g., casinos) need to pay specific attention to compliance matters, such as the introduction of new sanctions, which can be imposed daily.
Non-compliance with ever-changing rules and regulations can be detrimental to financial institutions from both a reputational risk and a financial risk perspective. Financial institutions need to be able to identify, detect and sometimes prevent bad behaviour, including anti-money-laundering and terrorist financing, across all jurisdictions worldwide. Audits by regulators seek out non-compliance and issue hefty fines.
Sanctions are a widely used tool of foreign policy, and fines from sanction breaches can impact the future operations of the financial institution. This can not only impact profits and erode accumulated reserves and shareholder equity — it can also increase operating costs as the regulators will impose additional monitoring mechanisms on the individual institution.
One of the prerequisites to meeting the obligations of international sanctions is to operate an efficient screening platform with advanced capabilities, such as name-matching algorithms against real-time sanction lists. Robust technology solutions and expert team members are therefore a prerequisite to adhere to compliance rules.
What Is Global Sanction Screening?
Sanction screening is the process of identifying entities or a group of entities against sanction lists and databases provided by local and international regulatory bodies. These lists can change daily and usually have a number of attributes (data points) attached to each of the entities. These attributes can relate to territorial boundaries or jurisdictions, specific currencies and assets. They can also detail partnerships and alliances.
A best practice process of conducting the search to maintain compliance is to have online access to local and global databases to automatically screen prospects, existing customers and related stakeholder databases regularly, including lists of politically exposed persons (PEPs). Advanced analytics, screening results, and existing and newly created global risk data should all lead to the creation of a single risk view with a decision support engine with little or no reduced false-positive results.
This process should be supported by media screening using artificial intelligence technologies, specifically natural language processing algorithms, which help to search text data and audio data for sentiment analysis involving the relevant names and associated words and connotations to generate a productive alert. In theory this sounds straightforward, but there are several variables or attributes attached to the names. This can often create significant obstacles in matching the right entity (prospect or client) to the name of the entity on the sanction list. Different alphabets, sign languages and spellings are just a few variables or attributes to be mentioned.
Why Is It Important for Financial Institutions to React Quickly?
Law makers and regulators can decide to take actions quickly to impose new sanctions and add new entities to the sanction lists in the event of wars or insurgencies. Having an agile process and a compliant screening solution or platform to handle sanction screening will enable financial institutions to quickly react to the new requirements.
What Are the Technology Implications?
The crucial capability for the technology involved in generating productive alerts is to have proper interfaces to several, often disparate, information systems and sanction lists for comparison. Financial institutions also need to be able to update matching algorithms, which can react in at least “near real time” to cross-reference their customers with the sanction list.
Machine-learning algorithms including decision tree, naïve bayes and support vector machine can be used for data classification and to automatise the watch list filtering system; it also enables faster and more accurate outputs than with someone performing the tasks manually.
It’s common that regulatory bodies are not aligned based on jurisdictions. The solution must therefore be able to spot any unalignment between watch lists and proposed alerts.
A major concern is data integrity, as data is often aggregated from multiple, disparate sources. The data and sanction indicators contained in the entity lists must be accurate and reliable. If it is not, the technology needs to provide an alert and decision support.
What Should Financial Institutions do in the Short Term?
Financial institutions should be sufficiently prepared to continue to conduct business under any condition based in part on their risk appetite and risk marketplace programs. This includes being able to scale, pivot or change as rules and regulations change. Financial institutions should therefore take steps to be ready to tackle constantly updated requirements. Financial institutions should:
- Be extra cautious and aware of risks associated with decentralised platforms or distributed ledger technologies (DLTs), which offer new possibilities for anonymity but create identification risks
- Even more actively watch out for patterns previously unseen to detect illegal activities
- Directly liaise with national and international regulators and solution providers to make sure all watch lists are updated
- Review inconsistencies with internal trusted service managers that handle authentication, authorisation and account settlement
- Reassess the importance and weights of various indicators, such as ratings and country assessments
- Create scenarios of capital flows and transfers to model potential new routes of money laundering
- Ensure that transcription of names of entities (both physical and legal) are properly transcribed into the Latin alphabet
If you have any questions, please contact George Briford, or head over to https://www.idc.com/eu and drop your details in the form on the top right.