Broadpath
PRACTICAL SOLUTIONS
entities and learn from their associated behavior. An AI-based AML solution can automate the transactional analysis of correspondent banking relationships to find anomalous behaviors and The reliance on TMS is presenting significant risk to financial institutions. An identify the end clients unacceptable number of illicit transactions, or causing those anomalies. false negatives, are not flagged by today’s TMS. It is estimated thatsolution 50 percent of An AI-enhanced financial crimes in the banking system pass can also account for seathrough TMS unnoticed. In addition, it is sonality,by mergers and acquiunderstood anti-money laundering (AML) compliance practitioners sitions, randomness andthat other approximately 95 percent of the alerts genlegitimate erated by TMS arevariances false positives. to find the illegitimate that Unlike TMS, artificialanomalies intelligence-based sys- are pretems can detect patterns of behavior, anasenting significant risks to financial lyze the intent of those patterns and expose institutions. anomalous activities. For example, transactions that do not follow the usual frequency Entity resolution Entity resolution andforthe investigation of and the investigation of and directional patterns expected a given entity relationships are integral to curbing type of account may not be flagged by a entity relationships are integral curbing theto de-risking cycle. The ability to estabTMS, but would be identified with an effeclish behavioral histories related to the the derisking cycle. The ability to establish tive AI solution. An AI solution can learn the volume of transactions and their amounts, behavioral related baseline of normal histories reported payroll account to the volume expected volume of transactions and activity and thus identify any irregularities of transactions and their amounts, expectamounts, current and ongoing ultimate Human decision-making is still in payroll transactions as potentially fictibeneficial owner data, andtution. any/all adverse With data AI, time-coned and volume transactions a keyanalytics element to and AML compliance tious worthy ofof further investigation. and amounts, media related to the entity in question, is suming and costly correspondent bank and current and ongoing ultimate the beneficial On the front line against money laundering key to ensuring accurate corresponAI can radically improve are AML compliance professionals tasked pseudo-customer investigations can become dentmedia banking risk management and know owner data, and any/all adverse correspondent banking with identifying suspicious activities. The your customer’s customer.automated, providing investigators with the related to the entity in question, is the average compliance professional works Advanced data analytics and AI technoloExpanding the same data most points toessential an entieight to 10 alerts each day. To make a decidata. gies canto help financial institutions manage key ensuring accurate correspondent ty’s related parties (customers) provides a sion on each case, the professional is correspondent banking more effectively. An banking risk management andholistic know your risk picture for compliance and required to review multiple and disparate Advancements in data analytics and AI can important function of an AI solution is its investigative teams within a bank or covbank systems, including KYC and customer customer’s customer. ability to monitor customers’ relationships enable compliance teams and AML asinvestiinformation program databases, well as ered financial institution. With data analytto other customers and entities and learn cross-reference TMS for related flags and ics and AI, time-consuming and costly gators to fulfill their regulatory obligations from their associated behavior. AI-based Expanding the sameAndata points to an entity’s turning to external sources of data. The correspondent bank and pseudo-customer AML solution can automate the transacwithautomated, precision,application improve SAR reporting and of AI can significantly enhance investigations can become related parties (customers) provides a holistic tional analysis of correspondent banking the capabilities of human compliance pro- of providing investigators ultimately with the mostprevent unnecessary derisking risk picture foranomalous compliance relationships to find behaviorsand investigative fessionals by eliminating tedious, time-conessential data. and identify the end a clients causing those banking customers. tasks involving massive amounts of teams within bank or covered financial insti- correspondentsuming Advancements in data analytics and AI can anomalies. An AI-enhanced solution can data. enable compliance teams and AML investialso account for seasonality, mergers and gators to fulfill their regulatory obligations acquisitions, randomness and other legitiwith precision, improve SAR reporting and mate variances to find the illegitimate David McLaughlin, CEO, QuantaVerse, QUANTAVERSE ISSUU FLIP BOOK 13 ultimately prevent unnecessary de-risking anomalies that are presenting significant Wayne, PA, USA, dmclaughlin@ of correspondent banking customers. risks to financial institutions. quantaverse.net