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Fraud typologies all financial institutions should know

Abrigo

Can your AML/CFT and fraud staff recognize these fraud typologies? The technology used to perpetrate financial crimes may be changing, but these common fraud typologies aren't going anywhere. This is a nearly 10% increase in complaints received and a 22% increase in losses and thats just fraud that was offically reported.

Fraud 221
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Fraud and AML integration: Is the FRAML approach right for your financial institution?

Abrigo

Evaluating the FRAML approach For years, financial institutions have debated the merits of combining fraud and anti-money laundering (AML) functions into a single department in what's known as a FRAML approach. At its core, FRAML is about taking a more holistic approach to financial crime risk management.

Fraud 195
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Celebrating FinCrime Fighter Day: Honoring the heroes of financial security

Abrigo

Their contributions are massive, and if you’ve ever worked with AML Officers and fraud professionals, you know just how vital they are. Every day, I’m reminded of the critical role the teams at our 2,500 bank and credit union customers play in anti-money laundering (AML), combating the financing of terrorism (CFT), and fraud prevention.

Security 221
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An Introduction: Generative AI Use Cases for the Financial Services Industry

Perficient

Risk Management , Anti-Money Laundering, & Fraud Protection Financial institutions invest heavily in security and risk management, but prevention and recovery progress are delayed by manual reporting and disparate systems.

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Model Risk Management: Regulatory Priorities and Best Practices

Abrigo

Meet Model Risk Management Expectations Updates to the FDIC Risk Management Manual should steer institutions toward a model that manages risk and drives growth. Takeaway 1 Aside from meeting examiner expectations, proper model risk management can protect your institution from unnecessary risk. .

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6 Digital Banking Trends for 2025

Perficient

In 2025, AI will play a pivotal role in customer service, fraud detection, risk management, and personalized financial advice. Additionally, AI-driven algorithms will enhance banks’ ability to detect emerging fraud patterns and mitigate risks more effectively.

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AI Regulations for Financial Services: OCC

Perficient

The economic risks of AI to the financial systems include everything from the potential for consumer and institutional fraud to algorithmic discrimination and AI-enabled cybersecurity risks. Hsu highlighted that each phase requires different risk management strategies and controls.