Solving Anti-Money Laundering (AML) and Know Your Customers (KYC) Challenges For a Leading Remittance Company

Notes on KYC and AML

Know Your Customers (KYC) has become an arduous concern for most financial institutions. KYC and its cousin anti-money laundering (AML) have been refined over the years. In its simplest form, KYC mandates the financial institutions verify customers are who they say they are. However, regulations have not been prescriptive in how, and with what, institutions should evaluate customers. The result is considerable expense for the institution for the technology and human resources to stay ahead of regulators and out of the headlines. Indeed, HyperAspect estimates that financial institutions will spend US$8 billion on financial crime management in 2021.

Artificial intelligence (AI) and machine learning (ML) are becoming increasingly important to KYC efficacy and customer experience, and savvy KYC providers have already incorporated AI/ML into their solutions and road map. Advanced analytics in KYC that incorporate AI/ML significantly improve the KYC screening process, resulting in potentially better outcome prediction accuracy.

Challenges

Our customer is an online remittance company providing international money transfer services to individuals who send money to beneficiaries in over 190 countries. The remittance options include cash pick up, home delivery, bank transfer, mobile airtime top-up and mobile wallets. The company was dissatisfied with their global data solutions provider and needed to find a more reliable solution for AML and KYC compliance. Their data provider’s API was often down, and the compliance team was never given advanced warning, leading to high levels of AML and KYC risks. As a result, our customer was forced to bypass the system and run thousands of manual checks, resulting in significant payment delays and customer dissatisfaction.

Solution

Our client engaged HyperAspect’s Cloud platform to help develop a decision support system that allows any medical professional to quickly see all documents important to the procedure and automatically highlight important sections within the document.

The approach involved creating a decision support system that fully integrates with the existing pre-approval workflow, funnels all document submissions into a centralized system, and appliesdifferent approaches from natural language processing to understand the document and text context. 

After the contextualizing phase, the system uses a series of AI comparison techniques to understand exactly which pieces of the unstructured text is relevant to the claim procedure and visualizes key information.

Results

The client benefited using our custom KYC and AML solution that was tailored to the company’s specific needs and regulatory requirements. The following results were achieved within first six months after the solution was implemented:

⦁ automated screening and monitoring against real-time global data of companies and individuals that is consolidated into separate user-friendly risk profiles
⦁ customer’s compliance team got access at an individual user level to the case management tool on the platform that allows for keeping a detailed audit log that can serve as an evidence to regulators
⦁ 250% improvement in risk management through alert and false positive reduction

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