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Know Your Transactions - KYT

 

  Many of us have heard about KYC (Know Your Customers) while opening bank account, Insurance Policy, Investments and Pension Schemes.  Bank insist on process to know about the customer before onboarding to their systems. KYC is process of a business verifying the identity of its clients and assessing potential risks of illegal intentions for the business relationship.

 

Know Your Transaction(KYT) is more about banks / financial institutions having a complete granular data centric information about the transactions done by the customer. There are major financial transactions happening on customer account to name few

  • Cash Transactions(Domestic)
  • Card Transactions
  • Remittances (Inward & Outward)
  • Cross Border Transactions
  • Trade Finance transactions
  • Bills & LC Transactions.

 

SWIFT” is the major network used by bank globally for transfer of money across banks and financial institutions. As part of swift transaction details, there are various fields captured to name few important fields in MT202 swift message,

  • Sender Reference (20),
  • Value Date, Currency, Amount (32)
  • Ordering Institution (52A)
  • Account with Institution (57A)
  • Beneficiary Institution (58 A)
  • Sender to Receiver Information (72). 

This above-mentioned information are captured as part of swift message. According to swift message types user will capture necessary fields related to financial and non-financial data. These data are mandatory for transaction analysis by the bank.

 

Know your Transactions in detail

As Bank would like to know all details of financial transactions mainly on the counter parties involved, purpose of transactions and transaction originations, as these details will provide the major information about the transaction nature for further analysis.

Bank will create various data models on various parameters such as transaction patterns, transaction codes, country of origination, customer name, originating bank etc. These models will help bank to drill down to find the list of transaction on various parameters provided and find the suspected or fraudulent transactions as part of analysis.

Transaction analyses is performed internally with the bank data for their audit / investigation purpose to find any fraudulent transaction over the network. These report generated can be used as evidence / proof of transaction derived from the data model. It can help bank to make system more secure by updating validation wherever required, reduce fraud and meet compliance & regulatory requirements.

 

Technology used in Know your Transactions

There are emerging technologies used extensively in banks for analyzing KYT.

 

Machine Learning (ML):

ML is a combination of informatics, analytics, and computer science.  Through machine, learning bank can create various models and create output on various parameter such as classification, regression, clustering, dimensionality reduction and others. Bank will create data model, train the system continuously with various parameters as per business requirements, and achieve the desired output over period.

 

Blockchain:

Customer / Transaction data are scattered in various blocks in the blockchain network, to ensure no one is able to manipulate data. Distributed Ledger   technology (DLT) is one of blockchain technology where bank can store the transaction data encoded and distributed database serving as a ledger. As DLT can help bank to utilize each transaction update and verification become possible across the specific blockchain network, depending on its goal and stakeholders. Consensus are obtained while sharing data on the blockchain network.

 

 Conclusion

 End of the Day Banks would like to establish security, accuracy and transparency enhances bank governance and regulatory oversight. This allows bank to focus on core business competencies and generate client satisfaction, while compliance and control for financial crime become a differentiating factor, rather than a costly burden.

 

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This content is provided by an external author without editing by Finextra. It expresses the views and opinions of the author.

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