FinServ AML (The Next Generation AML Solution)

Financial Institutions worldwide are at risk of get exposed to illicit, fraudulent and terrorist financing activities. In today’s world, money launders are using various hi-tech and advanced methods to launder the money; with this financial institutions are not in position to track such activities using their traditional manual process and are looking forward to advanced automated monitoring systems.

In today’s AML market, most of the vendor products being First generation solutions that can track the money laundering activities only based on static defined rules. Today financial institutions are badly looking for products that can, not only track the network of illicit transactions but also help banks in identifying the customer’s fraudulent behavior patterns using self learning algorithms.

With FinServ AML being the Next generation solution, institutions are insulated from being a victim of current or future emerging patterns of money laundering and terrorist financing. FinServ facilities institutions with automating of activities, starting from tracking, detecting and investigating to documenting and reporting the potential fraudulent activities.

FinServ AML facilitates institutions with:

  • Customer Identification Process
  • Profiling the customers into various Peer Groups based on the Industry, Income stream, source of funds, geography etc.,
  • Performing of Customer Due Diligence
  • Identifying the High risk customers and perform Enhanced Due Diligence
  • Adaptive learning of customer/peer group behaviors
  • Advanced neural algorithms
  • Configurable case management modules to track the generated red flags
  • Compliance reporting

FinServ AML framework integrates itself into the Institution’s business processes and controls, enabling the institution to use the integrated customer data to monitor the money laundering activities in a cost-efficient and scientific way. By deploying the FinServ AML, Banks can dramatically reduce the cost and effort involved in Customer Data Integration, Monitoring, Investigating, Documenting and Regulatory reporting of suspicious transactions.

With FinServ AML, Institutions can perform:

Customer Data Integration:

Integrate and improve the quality of the customer data by aggregating, normalizing and cleansing the customer data from desperate systems.

Customer Risk Management:

Know Your Customer (KYC)

The inadequacy or absence of KYC standards can subject Financial Institutions to serious customer and counterparty risks, especially reputational, operational, legal and concentration risks. It is worth noting that all these risks are interrelated.

With its KYC module FinServ, brings all the Verification and Investigation efforts that involved many manual processes into a single integrated environment, there by reducing risk exposure, due to delays in the verification and investigation process.

FinServ manages these risks using multi prong approach of Customer Profiling, Customer Identification, Due Diligence, and Enhanced Due Diligence.

Customer Profiling

System provides the capabilities to classify the customer into risk/behavioral profiles based on nature of business, accounts/ products, geographic location, customer type, source of funds, occupation, etc.,

This classification enables in fine grained definitions of the rules for Risk rating, Due Diligence checks and Transactions monitoring.

Customer Identification and Due Diligence

Using its customer due diligence module, system helps the bank to protect itself from being used to launder money or to support terrorist financing by its customers.

As part of the customer due diligence process, system performs following operations:

  • Customer Identification
  • Customer Due Diligence (CDD) checking
  • Enhanced Due Diligence

Customer Identification: system identifies the customer and substantiates his/her identity by using dependable, self-determining source documents, data or information, by accessing or interfacing with various public record databases (like OFAC, FinCen etc.,),

Customer Due Diligence Checks: As part of the customer due diligence checks, checklist for various information that need to be collected from the customer can be configured in the system. Checklist can be configured based on different peer groups/profiles. For example, a ‘salaried employed’ profile can have a different checklist from that of a ‘corporate a/c’ profile. This checklist will be verified against the data provided by the customer during opening of the account.

Concentrated Due diligence for high risk customers: Banks need to affect improved due diligence measures based on the risk assessment, thereby necessitating concentrated due diligence for higher risk customers, particularly those for whom the sources of funds are not obvious such as non-resident customers, high net worth individuals, trust and charities, companies with close family shareholding or beneficial ownership, firms with sleeping partners, politically exposed person of foreign origin, non face to face customers, those with dubious reputation as per available public information.

Customer identification is done either by Documentary or Non-documentary verification in the system.

Documentary verification includes customary forms of identifications like

  • Valid driver’s license
  • Passport etc.,

Non-documentary verification includes any other form of information other than relying on customary forms of information.

Transaction Risk Assessment

FinServ identifies and filters all the customer transactions that pose greater risk for potential money laundering activities.

Finserv monitors every single transaction and discovering all unusual behavior and separating out those transactions that are determined to represent a true risk for Institution.

Using its Intelligent Neural Network engine identifies and adapts itself to new emerging money laundering techniques and schemas

Transaction monitoring

Transaction monitoring enables banks to be vigilant for any significant, unexpected and unexplained change in the behavior of an account or inconsistencies in amount, origin, destination, or type with a customer’s known legitimate activities. This inconsistency in the pattern of transactions is measured against the stated original purpose of the accounts.

The inconsistency in the account behavior includes (but not limited to)

  • Recurring transactions
  • Sudden activity into a Dormant account
  • Rapid Fund movement in and out of an account
  • Wire transfers to bank secrecy haven countries
  • Incoming and/Outgoing wire transfers
  • Frequent wire transfer with no apparent business reason
  • High volume of wire transfers with low account balances

Adaptive threshold analysis

This allows detecting of transactions violating regulatory reporting limits. System has capability to monitor the cash or non-cash transactions of any threshold limits notified by regulatory authority.

System provides options to allocate different lower limits for individual accounts with higher risk perception. The monitoring periodicity can be defined on day-to-day to any other period of transactions to meet the requirement of regulatory authority.

Pattern recognition

To unearth known money laundering patterns and scenarios with neural network scoring engine. System allows the users to identify different scenarios and build the rules to track the possible money laundering.

Different scenarios that can be tracked include (but not limited to):

  • Structured or recurring, non reportable transactions
  • Even Dollar amount transactions
  • Customer maintaining multiple accounts and transferring money among the accounts and using one account as a master account from which wire/funds transfer originates or into which wire/funds transfer are received
  • Customer regularly depositing or withdrawing large amounts by a wire transfer to, from, or through countries that are known sources of narcotics or where Bank secrecy laws facilitate laundering money.
  • Remittances received from financial haven countries and particularly if there is no apparent business reason for such transfers and is not consistent with the customer’s business or history.
  • Sending or receiving frequent or large volumes of wire transfers to and from offshore institutions.
  • Transactions which are not consistent with the customers business or income level

Behavioral Analysis

This allows the system to detect transactions not conforming to customer's expected account usage. This functionality manages the complex behavior that is commonly associated with the money laundering schemes.

Using this, system detects the wrongdoing by finding the suspicious patterns of behavior that may be hidden behind large volumes of financial data. It analyzes the customer behavior based on amount of transactions, frequency of transactions, and number of transactions.

It uses advanced Neural network detection technique like inconsistent with past behaviors, link analysis, money laundering topologies like structuring, frequent wire transfer etc.

Using its Group pattern technique it compares the behavior of same peer groups and identifies the suspicious customer transactions that does not go hand in hand with the peer group transactions

Case Management

System provides a comprehensive Case management system for suspicious transactions or persons in a paperless environment, through a step-by-step workflow with built-in checkpoints and support for multiple authorization levels

Highlights of this module includes (but not limited to):

  • System comes with dynamic workflow that allows the administrators to define the step by step process to be followed for investigation process.
  • Provides option for the Bank to disallow deletion of cases regardless of status and to allow case re-opening and re-assignment based on workflow rules
  • Provides facility to set deadlines to cases. Email notifications/reminders based on set number of days from an event may be sent to specific persons. Accountabilities can be established through date-time stamp on all actions taken
  • Dashboard to allow the compliance officer to monitor progress at every stage of case and allocate or re-allocate resources to manage workload
  • At the end of the investigation, system generates a case investigation report to be submitted to the regulatory authority.
  • Provides a complete case history including but not limited to detailed log of all alerts and transactional data, actions taken, maker-checker-authorizer details and reports filed

Regulatory Requirements

  • Suspicious Activity Report (SAR)
  • Currency Transaction Report (CTR)
  • Non-Currency Transaction Report (NCTR)
  • Currency or Monetary Instrument Report (CMIR)
  • Foreign Bank/ Security Account Report (FBAR)
  • IRS Form 8300 Report