Embedded lending has altered the very gateways to credit, and its global market could swell to $7.2 trillion by 2030. But with every new customer and transaction, the pressure on compliance grows. Traditional compliance systems still cast a wide net, with as many as 95% of AML alerts turning out to be false positives. This may result in delays, frustrated customers, and extra operational strain.
It’s not just AML checks slowing things down. Research from Tink shows 32% of lenders see manual income verification as their biggest bottleneck in risk decisioning, while a quarter say document validation is their single highest cost. These inefficiencies chip away at the seamless experience that embedded lending promises.
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Yet, a robust orchestration layer with a best-of-breed approach can offer a solution. It can reduce false positives and seamlessly connect all risk and compliance checks to improve the borrower experience. The payoff is faster decisions, fewer customer drop-offs, and an uninterrupted lending experience. Let’s take a closer look at the bottlenecks and what orchestration looks like in practice.
AML false positives—The hidden bottleneck
False positives are a normal part of the AML risk assessment process. Many institutions err on the side of caution with strict AML filters, even if it means delaying legitimate borrowers. But with false positives reaching unprecedented highs, the system is eroding embedded lending’s promise of speed and friction-free experiences.
But what actually triggers these alerts? A false positive happens when the lender’s system’s criteria are too sensitive or broad, as they rely on rules-based monitoring with predefined thresholds and static patterns. Deloitte shares some of the common challenges in AML, leading to false positives:
“Many scenarios/rules are implemented because they are available in a vendor solution but without a solid foundation in an AML risk assessment, leading to under-monitoring in some areas and over-monitoring in others.”
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By GlobalData“Modern AML TM solutions offer a myriad of adjustable parameters, and without a systematic approach the complexity can be overwhelming, as a result of which firms use factory settings which are usually not optimal for their specific circumstances.”
Since 2015, Europe’s AML framework (AMLD4) has mandated a risk-based approach, requiring institutions to tailor monitoring to their specific risks rather than relying on fixed rules. But its effectiveness depends on how this approach is implemented.
Furthermore, AML systems weren’t built with today’s instant embedded lending experience in mind. For example, a small business owner applies for an equipment loan of £1,000 through an online store while traveling. Even with the applicant’s strong account history and risk profile, the loan is flagged due to a rule analysing transaction amount, unusual IP, and location. Without real-time context—like consistent past usage or multi-party authorisation—the transaction stalls for manual AML review.
False positives within the KYC process can cause a delay while compliance teams review the loan application manually. Data from PYMNTS found that 64% of consumers want instant lending payouts due to financial need, and over one in four said they need funds in 30 minutes or less. A pause in this process and/or within the process of transaction monitoring is more likely to cause a customer to abandon their purchase, looking for an alternative lender and merchant. This causes a lender to miss out on interest, revenue and a potential new-to-bank customer, and the retailer to lose a high-margin sale as well as customer satisfaction.
Quick KYC and AML decisioning is a key part of the embedded lending compliance process, and regulators are only tightening their grip. Yet, there is a solution: an integrated orchestration layer that builds smarter, faster compliance directly into the customer experience.
The role of orchestration in fixing AML friction
Effective AML hinges on piecing together up-to-date data from a web of internal and external sources. A best-of-breed orchestration layer serves as the bridge between core bank internal systems and specialised third-party tools for AML, KYC, ID verification, and fraud detection. This not only streamlines operations but also creates a single, cohesive compliance environment, dramatically reducing the risk of costly gaps, overlaps or errors.
Modern orchestration layers typically include:
- Money laundering risk scoring modules that are built-in or integrated engines that calculate real-time risk using contextual data, including transaction type, location, behaviour, and device.
- API connectivity to multiple vendors. The orchestration layer enables plug-and-play connections to KYC, sanctions screening, document verification, fraud detection, open banking and more.
- Complete audit trails for compliance. The orchestration layer automatically logs every decision, rule path, and outcome, which is critical for regulatory reviews and model governance.
Ultimately, the flexibility of the orchestration layer comes down to the lender’s risk appetite. With a risk-based AML approach, the lender defines how much risk they are willing to accept, and those preferences determine the thresholds and parameters within the KYC process and within the transaction monitoring system used to monitor individual or sets of transactions. This means lenders retain control to balance effective fraud detection with minimising false positives.
Leading institutions are already deploying AI-driven AML platforms that analyze over 800,000 transactions per second with 92.3% accuracy. This has led to U.S. banks reporting that AI has reduced false fraud alerts by up to 80%.
The purpose and outcome of proper and tailored tools within the orchestration layer is to turn fragmented systems into a unified decision engine, balancing speed with traceability and enabling faster, more confident approvals.
Beyond AML: Building a fully-orchestrated digital lending stack
KYC and transaction monitoring are the most compliance-heavy components of digital lending, but orchestration is far from a one-trick pony. An effective orchestration layer doesn’t just streamline AML checks; it stitches together all the critical services required to deliver a seamless, compliant lending and customer onboarding experience.
This includes KYC processes for verifying borrower identities at onboarding and during the customer relationship. These identity checks are complemented by open banking integrations that access real-time financial data. This enhances affordability checks and speeds up approvals, enabling document-free verification by using a customer’s bank records. Income and employment verification APIs also support eligibility assessments, providing a full financial picture.
Fraud detection tools use that data to find synthetic identities, account takeovers, and application anomalies, with orchestration bringing together multiple solutions into a single customer view. This unified approach allows compliance and fraud teams to work from one source of truth, and with that, increase the quality and speed of the decisions.
The major benefit of a well-built and implemented orchestration layer is that it gives lenders speed and agility. With flexible APIs and plug-and-play technology, lenders can launch new products and features at speed. They can also quickly customise solutions for different markets and compliance rules, staying nimble without a drawn-out development process. That flexibility lets lenders constantly refine the customer experience. Also, by tapping into best-of-breed services, these platforms take a lot of pressure off the IT team, saving resources.
An orchestration layer acts as the “glue” of embedded lending, integrating various compliance and risk tools. By reducing AML false positives through smarter, context-aware decisioning, it ensures faster approvals and the frictionless lending experience that today’s customers demand.
Yaacov Martin is CEO of Jifiti
