{"id":34608,"date":"2020-02-17T16:09:02","date_gmt":"2020-02-17T16:09:02","guid":{"rendered":"https:\/\/www.sisinternational.com\/?page_id=34608"},"modified":"2026-05-05T16:57:25","modified_gmt":"2026-05-05T20:57:25","slug":"%d9%85%d9%83%d8%a7%d9%81%d8%ad%d8%a9-%d8%ba%d8%b3%d9%8a%d9%84-%d8%a7%d9%84%d8%a3%d9%85%d9%88%d8%a7%d9%84-aml-%d8%a3%d8%a8%d8%ad%d8%a7%d8%ab-%d8%a7%d9%84%d8%b3%d9%88%d9%82","status":"publish","type":"page","link":"https:\/\/www.sisinternational.com\/ar\/%d8%ad%d9%84%d9%88%d9%84\/%d8%a3%d8%a8%d8%ad%d8%a7%d8%ab-%d8%a7%d8%b3%d8%aa%d8%b4%d8%a7%d8%b1%d8%a7%d8%aa-%d8%a7%d8%b3%d8%aa%d8%b1%d8%a7%d8%aa%d9%8a%d8%ac%d9%8a%d8%a9-%d8%a7%d9%84%d8%aa%d9%83%d9%86%d9%88%d9%84%d9%88%d8%ac\/%d9%85%d9%83%d8%a7%d9%81%d8%ad%d8%a9-%d8%ba%d8%b3%d9%8a%d9%84-%d8%a7%d9%84%d8%a3%d9%85%d9%88%d8%a7%d9%84-aml-%d8%a3%d8%a8%d8%ad%d8%a7%d8%ab-%d8%a7%d9%84%d8%b3%d9%88%d9%82\/","title":{"rendered":"Anti Money Laundering AML Market Research | SIS"},"content":{"rendered":"
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Anti Money Laundering Market Research<\/h1>\n
\"SIS<\/figure>\n
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\u062d\u0644\u0648\u0644 \u0644\u0645\u0633\u0627\u0639\u062f\u0629 \u0627\u0644\u0634\u0631\u0643\u0627\u062a \u0639\u0644\u0649 \u0645\u0643\u0627\u0641\u062d\u0629 \u063a\u0633\u064a\u0644 \u0627\u0644\u0623\u0645\u0648\u0627\u0644 \u0648\u062a\u0639\u0632\u064a\u0632 \u0627\u0644\u0627\u0645\u062a\u062b\u0627\u0644<\/span><\/h2>\n

What is Money Laundering? Money laundering is the process of legitimizing the proceeds of crime. It involves introducing the money into the legal financial system. The cash is then circulated into different accounts to create\u00a0confusion. Finally, the launderer integrates the funds into the financial system. Such money often encourages acts of terrorism and drug trafficking.<\/span><\/p>\n<\/div>\n

Anti Money Laundering AML Market Research: How Leading Financial Institutions Build Compliance Advantage<\/h1>\n

Anti Money Laundering AML Market Research has shifted from a compliance checkbox to a strategic input for institutions competing on speed, trust, and capital efficiency. The banks and payment firms pulling ahead treat AML intelligence as a sensing function, not a reporting function. They use primary research to understand how typologies evolve inside specific corridors, how regulators interpret ambiguous guidance, and how competitors are pricing the cost of compliance into product economics.<\/p>\n

The opportunity is concrete. Institutions that map AML risk with the same rigor they apply to credit risk lower false positive rates, reduce investigator headcount per alert, and approve more good customers. The differentiator is no longer the rulebook. It is the quality of the intelligence behind it.<\/p>\n

Why Anti Money Laundering AML Market Research Now Drives Commercial Strategy<\/h2>\n

Three forces have moved AML from the back office to the boardroom. ISO 20022 migration is exposing payment data fields that legacy transaction monitoring systems were never built to read. Account-to-account payments and stablecoin settlement are compressing the time window in which suspicious activity can be detected. Open banking adoption is creating new typologies around mule networks operating through aggregator APIs.<\/p>\n

Each of these shifts changes the economics of compliance. A correspondent bank that misreads the typology mix in a cross-border corridor will overspend on monitoring while still missing the activity that triggers enforcement. A neobank that underestimates synthetic identity risk in onboarding will see card-not-present fraud bleed into AML caseloads downstream. Primary research closes the gap between what the rulebook anticipates and what the market is actually doing.<\/p>\n

What Leading Firms Learn from Structured AML Intelligence<\/h2>\n

The strongest AML programs treat intelligence gathering as a continuous function across four layers: regulatory interpretation, typology evolution, peer benchmarking, and customer segment risk profiling. Each layer requires a different research method.<\/p>\n

Regulatory interpretation is built through expert interviews with former examiners, outside counsel, and FinCEN-adjacent practitioners. The written guidance from FATF, OFAC, and the EU AMLA tells a bank what is required. Practitioner interviews tell a bank how examiners are actually scoring it. The gap between the two is where consent orders are written.<\/p>\n

Typology evolution requires field intelligence from fraud and AML operators inside payment processors, gaming operators, and money service businesses. In structured expert interviews conducted by SIS International with senior fraud and payment risk leaders across iGaming operators in the UK, Malta, Gibraltar, and Ontario, practitioners consistently described AML typologies migrating faster than vendor rule libraries could be updated, with mule activity moving from card rails to instant payment rails within a single quarter.<\/span> That kind of pattern is invisible in published reports.<\/p>\n

How Primary Research Reduces False Positives and Investigator Cost<\/h2>\n

The single largest operating cost in an AML program is alert disposition. Most tier-one banks run false positive rates above 95 percent on transaction monitoring. The institutions that have driven that number down did not buy a better engine. They invested in segment-level behavioral baselines built from primary research with their own customer base.<\/p>\n

The mechanism is straightforward. Generic typology rules treat a small business importer the same as a freelance consultant the same as a remittance sender. Behavioral baselines built from voice-of-customer interviews and transaction pattern segmentation produce risk thresholds that match how each segment actually moves money. SIS International’s proprietary research with US-to-Mexico remittance senders using Western Union, Remitly, and similar services indicates that legitimate sender behavior clusters around predictable wage-cycle patterns, payment-method preferences tied to recipient banking access, and corridor-specific amount bands. Monitoring rules calibrated to those clusters cut alert volume materially without weakening detection.<\/span><\/p>\n

The same logic applies to KYC refresh cycles, sanctions screening tuning, and adverse media filtering. Each is a tuning problem, and tuning requires evidence about actual customer behavior, not assumptions.<\/p>\n

Where Competitive Intelligence Changes AML Vendor Selection<\/h2>\n
\"SIS<\/figure>\n

The AML technology market has consolidated into four categories: transaction monitoring platforms, perpetual KYC providers, sanctions and adverse media screening, and case management. Vendors including NICE Actimize, SAS, Oracle Financial Services, ComplyAdvantage, and Quantexa each position against different parts of the stack. Procurement teams that evaluate them on feature matrices alone routinely overpay.<\/p>\n

The institutions extracting the most value run win\/loss analysis and reference-customer interviews before they issue an RFP. They learn which vendors actually scale at the transaction volumes they project, which graph analytics implementations survive a regulatory exam, and which perpetual KYC claims hold up when applied to commercial banking books versus retail. That intelligence reframes the negotiation.<\/p>\n

The Four-Layer AML Intelligence Model<\/h3>\n
\n\n\n\n\n\n\n\n\n
Intelligence Layer<\/th>\nPrimary Method<\/th>\nDecision It Informs<\/th>\n<\/tr>\n<\/thead>\n
Regulatory interpretation<\/td>\nFormer-examiner and counsel interviews<\/td>\nPolicy calibration, exam readiness<\/td>\n<\/tr>\n
Typology evolution<\/td>\nFraud and AML operator interviews<\/td>\nRule library updates, model retuning<\/td>\n<\/tr>\n
Peer benchmarking<\/td>\nAnonymous practitioner panels<\/td>\nHeadcount, budget, vendor stack<\/td>\n<\/tr>\n
Customer segment behavior<\/td>\nVOC and transaction segmentation<\/td>\nThreshold tuning, false positive reduction<\/td>\n<\/tr>\n<\/tbody>\n<\/table>\n<\/figure>\n

Source: SIS International Research<\/em><\/p>\n

How Geographic Specificity Separates Strong Programs from Weak Ones<\/h2>\n
\"SIS<\/figure>\n

AML risk is local even when the institution is global. A trade finance book exposed to Gulf re-export corridors carries different typologies than one weighted toward Latin American agricultural commodities. A correspondent banking relationship with a West African bank requires different enhanced due diligence than one with a Baltic counterpart. Generic country risk scores from third-party data providers compress this variation into a single number that hides what matters.<\/p>\n

SIS International has conducted financial services research across more than 135 countries, including expert interviews with compliance officers, regulators, and operators in jurisdictions where written guidance lags practice by years. The patterns that emerge from that work consistently show that the highest-risk corridors are not the ones flagged by standard country risk indices. They are the ones where regulatory capacity, banking concentration, and informal value transfer systems intersect in ways that public data does not capture.<\/p>\n

Building the Internal Case for AML Research Investment<\/h2>\n
\"SIS<\/figure>\n

Finance committees fund AML technology readily. They fund AML intelligence reluctantly. The argument that moves them is the cost-of-error calculation. A single consent order from a major regulator carries direct penalties, lookback costs, monitor fees, and a multi-year drag on growth initiatives that require regulatory non-objection. Set against that, the cost of structured primary research across regulatory interpretation, typology evolution, and customer segmentation is rounding error.<\/p>\n

The institutions that have made this case successfully frame AML research as inputs to three measurable outcomes: reduction in alert-to-SAR ratio, reduction in onboarding abandonment among low-risk customers, and acceleration of new product approvals through compliance review. Each is quantifiable. Each is defensible. Each turns Anti Money Laundering AML Market Research from an expense line into a return calculation.<\/p>\n

What This Means for the Next Planning Cycle<\/h2>\n
\"SIS<\/figure>\n

The competitive frontier in financial services compliance is moving from rule coverage to intelligence quality. Institutions that build a continuous primary research function around AML, integrated with second-line risk and first-line product teams, will price risk more accurately, onboard more good customers, and absorb regulatory change with less disruption. Those that continue to rely on vendor-supplied typology libraries and published guidance will find their cost-to-serve rising while their detection effectiveness flattens. The gap will compound.<\/p>\n

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Related SIS Resources<\/h3>\n