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AML and KYC: A Differential Perspective

Data from the United Nations estimates money laundered annually worldwide, is between 2-5% of global GDP (between $800 billion to $2 trillion!!). This is leaving aside penalties financial institutions may incur due to non-compliance to regulatory requirements. Understanding nuances of AML and KYC becomes critical for fraud and risk mitigation from financial, regulatory and operational perspectives.

Whether you are a Fintech, bank, BNPL, card issuer, payment processor or marketplace, implementing an effective AML and KYC program has become essential. Regardless of your role in the transaction lifecycle, institutions need to implement effective KYC and AML tools.

Let’s dive in to gain clarity on how stronger KYC processes can reduce risks, but will not suffice to prevent AML. AML is a set of processes dedicated to tackle money laundering and inappropriate usage of the money. KYC is a part of an AML program that helps in customer identification to incorporate processes preventing money laundering and verification for better AML solutions.

  • KYC refers to the process of acquiring relevant and validated information about your customer from credible sources to serve as your reference point to assess credibility of transacting or lending to a potential customer

  • AML on the other hand has far more regulatory & compliance driven. AML serves as an umbrella term for regulated procedures and mechanisms that financial institutions must implement to fight money laundering and terrorism financing to comply with regulatory requirement (which otherwise leads to penalties).

AML and KYC have critical differences in terms of the Process, Objectives and Parameters:

  • Process: AML deals with activities or processes related to monitoring of suspicious transactions. KYC on the other hand has to do with validated and authentic customer by obtaining personal details and verifying them.

  • Objectives: AML serves to prevent money laundering, fraud and suspicious transfer of funds to potential criminal entities. While KYC provides a key check towards allowance of an entity to engage for onboarding/transaction/lending on a business platform.

  • Parameters: AML comprises risk assessment, transaction monitoring, stoppage and reporting of suspicious activities. KYC encompasses customer identity verification, risk identification, and risk management.

Mitigation of risks with alternate datasets

As much as new forms of risks and frauds have plagued the payments and lending ecosystem, technology has also evolved providing risk mitigation measures and approaches that did not exist before. Today with the sharp spike in digital transactions, payment providers have access to a lot more than basic KYC details in forms of alternate datasets across pre-transaction, transaction and post transaction phases which add significant insights to assist risk mitigation.

Datasets around device, IP, browser fingerprints, geolocation and keystroke dynamics can be well leveraged to address challenges related to synthetic identity, suspicious transfers and laundering as a whole. The diversity and magnitude of such parameters make it impossible to adopt traditional rule-based approaches to mitigate new age frauds and machine learning algorithms help in identifying evolving fraud patters to secure new-age payments and lending.

Drona Pay helps financial institutions with a modern risk management platform to leverage a range of alternate data sets and machine learning models that tackle AML patterns in a real-time environment, to accelerate growth.


Effective KYC is an integral part of risk management including but not limited to AML. Rule based approaches maybe necessary but no more sufficient to stay relevant in the digital economy. Financial institutions need to add actionable insights from alternative datasets and leverage machine learnings models as effective ammunition against money laundering to stay relevant- its real, its critical, and the time is now!

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