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Banking Expert

banking-expert

Expert-level banking systems, core banking, regulations, and banking technology

SKILL.md

Full skill instructions

Banking Expert

Expert guidance for banking systems, core banking platforms, regulatory compliance, and banking technology.

Core Concepts

Banking Systems

  • Core banking systems (CBS)
  • Account management
  • Transaction processing
  • Payment systems (ACH, SWIFT, SEPA)
  • Loan management
  • Risk management systems

Regulations

  • Basel III/​IV capital requirements
  • Know Your Customer (KYC)
  • Anti-Money Laundering (AML)
  • GDPR for banking
  • PSD2 (Payment Services Directive)
  • Dodd-Frank Act

Key Technologies

  • Real-time payment processing
  • Mobile banking
  • Open banking APIs
  • Digital wallets
  • Blockchain in banking
  • AI for fraud detection

Account Management

from decimal import Decimal
from datetime import datetime
from enum import Enum

class AccountType(Enum):
    CHECKING = "checking"
    SAVINGS = "savings"
    CREDIT = "credit"
    LOAN = "loan"

class Account:
    def __init__(self, account_number: str, account_type: AccountType,
                 customer_id: str, balance: Decimal = Decimal('0')):
        self.account_number = account_number
        self.type = account_type
        self.customer_id = customer_id
        self.balance = balance
        self.status = "ACTIVE"
        self.created_at = datetime.now()

    def deposit(self, amount: Decimal) -> dict:
        """Deposit funds with validation"""
        if amount <= 0:
            raise ValueError("Amount must be positive")

        self.balance += amount

        return {
            "transaction_id": self.generate_transaction_id(),
            "type": "DEPOSIT",
            "amount": amount,
            "balance": self.balance,
            "timestamp": datetime.now()
        }

    def withdraw(self, amount: Decimal) -> dict:
        """Withdraw funds with balance check"""
        if amount <= 0:
            raise ValueError("Amount must be positive")

        if self.balance < amount:
            raise ValueError("Insufficient funds")

        self.balance -= amount

        return {
            "transaction_id": self.generate_transaction_id(),
            "type": "WITHDRAWAL",
            "amount": amount,
            "balance": self.balance,
            "timestamp": datetime.now()
        }

    def transfer(self, to_account: 'Account', amount: Decimal) -> dict:
        """Transfer funds between accounts"""
        # Withdraw from source
        withdrawal = self.withdraw(amount)

        try:
            # Deposit to destination
            deposit = to_account.deposit(amount)

            return {
                "transaction_id": self.generate_transaction_id(),
                "type": "TRANSFER",
                "from_account": self.account_number,
                "to_account": to_account.account_number,
                "amount": amount,
                "timestamp": datetime.now()
            }
        except Exception as e:
            # Rollback on failure
            self.deposit(amount)
            raise e

KYC/​AML Compliance

class KYCService:
    def verify_customer(self, customer_data: dict) -> dict:
        """Perform KYC verification"""
        verification_results = {
            "identity_verified": False,
            "address_verified": False,
            "sanctions_clear": False,
            "pep_check_clear": False,
            "risk_level": "HIGH"
        }

        # Identity verification
        verification_results["identity_verified"] = self.verify_identity(
            customer_data["id_document"]
        )

        # Address verification
        verification_results["address_verified"] = self.verify_address(
            customer_data["proof_of_address"]
        )

        # Sanctions screening
        verification_results["sanctions_clear"] = self.screen_sanctions(
            customer_data["name"],
            customer_data["date_of_birth"]
        )

        # PEP (Politically Exposed Person) check
        verification_results["pep_check_clear"] = self.check_pep(
            customer_data["name"]
        )

        # Calculate risk level
        verification_results["risk_level"] = self.calculate_risk_level(
            verification_results
        )

        return verification_results

class AMLMonitoring:
    def monitor_transaction(self, transaction: dict) -> dict:
        """Monitor transaction for suspicious activity"""
        flags = []

        # Large transaction
        if transaction["amount"] > 10000:
            flags.append("LARGE_TRANSACTION")

        # Rapid succession of transactions
        if self.check_velocity(transaction["account_id"]):
            flags.append("HIGH_VELOCITY")

        # Unusual pattern
        if self.check_pattern(transaction):
            flags.append("UNUSUAL_PATTERN")

        # International transfer to high-risk country
        if transaction.get("international") and \
           self.is_high_risk_country(transaction.get("destination")):
            flags.append("HIGH_RISK_COUNTRY")

        if flags:
            self.file_suspicious_activity_report(transaction, flags)

        return {
            "flagged": len(flags) > 0,
            "flags": flags,
            "risk_score": self.calculate_aml_risk_score(flags)
        }

Payment Processing

class PaymentProcessor:
    def process_ach_payment(self, payment: dict) -> dict:
        """Process ACH payment"""
        # Validate routing and account numbers
        if not self.validate_routing_number(payment["routing_number"]):
            raise ValueError("Invalid routing number")

        # Create ACH file
        ach_batch = self.create_ach_batch([payment])

        # Submit to ACH network
        submission_result = self.submit_to_ach_network(ach_batch)

        return {
            "payment_id": payment["id"],
            "status": "PENDING",
            "expected_settlement": self.calculate_settlement_date(),
            "trace_number": submission_result["trace_number"]
        }

    def process_wire_transfer(self, wire: dict) -> dict:
        """Process SWIFT wire transfer"""
        # Generate SWIFT message
        swift_message = self.create_swift_mt103(wire)

        # Send via SWIFT network
        result = self.send_swift_message(swift_message)

        return {
            "wire_id": wire["id"],
            "status": "SENT",
            "swift_reference": result["reference"],
            "fee": self.calculate_wire_fee(wire["amount"])
        }

Interest Calculation

class InterestCalculator:
    @staticmethod
    def calculate_simple_interest(principal: Decimal, rate: Decimal,
                                  days: int) -> Decimal:
        """Calculate simple interest"""
        return principal * rate * days / 365

    @staticmethod
    def calculate_compound_interest(principal: Decimal, annual_rate: Decimal,
                                   years: int, compounds_per_year: int = 12) -> Decimal:
        """Calculate compound interest"""
        rate_per_period = annual_rate / compounds_per_year
        num_periods = years * compounds_per_year

        return principal * ((1 + rate_per_period) ** num_periods - 1)

    @staticmethod
    def calculate_loan_payment(principal: Decimal, annual_rate: Decimal,
                              months: int) -> Decimal:
        """Calculate monthly loan payment"""
        monthly_rate = annual_rate / 12

        payment = principal * (monthly_rate * (1 + monthly_rate) ** months) / \
                  ((1 + monthly_rate) ** months - 1)

        return payment.quantize(Decimal('0.01'))

Best Practices

  • Implement two-factor authentication
  • Use encryption for sensitive data (at rest and in transit)
  • Maintain complete audit trails
  • Implement real-time fraud detection
  • Ensure ACID compliance for transactions
  • Regular security audits and penetration testing
  • Implement rate limiting on APIs
  • Use tokenization for sensitive data
  • Maintain disaster recovery and business continuity plans
  • Regular regulatory compliance reviews

Anti-Patterns

❌ Storing sensitive data unencrypted ❌ No transaction logging/​audit trail ❌ Synchronous payment processing ❌ Ignoring regulatory compliance ❌ No fraud detection mechanisms ❌ Using floats for money calculations ❌ No backup and recovery procedures

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