It is becoming increasingly harder to delineate between fraud risk and compliance risk. The speed with which identity fraudsters and money launderers move to exploit gaps within financial crime risk management systems has increased due to the race toward
greater digitalization and increasing service expectations from consumers. And community banks and credit unions are now at even greater risk as fraudsters increasingly target them due to big bank competitors’ continued investments in enterprise risk management
tools and strategies.
Many community-based financial institutions’ risk management tools now consist of a disjointed collection of point solutions and siloed risk management functions. But, as the lines begin to blur between different types of risk, continuing a disjointed approach
to fraud and compliance risk management will inevitably result in missed vulnerabilities to be exploited by malicious actors.
Types of Risk
At a high level, the primary types of risk affecting financial institutions include cyber risk, compliance risk and fraud.
Cyberattacks against financial institutions
jumped 238 percent in 2020 costing the financial sector $5.72 million on average per data breach. Types of cyber risk affecting financial institutions include:
Supply chain attacks
Every financial institution is painfully aware of the resources needed to maintain regulatory compliance. Examples of the types of regulatory compliance financial institutions must manage include:
Fraudsters are continually finding new and creative ways to stay one step ahead of financial institution fraud controls. Types of fraud incurred by financial institutions include:
New account fraud
Account takeover fraud
The Problem with a Siloed Approach to Different Types of Risk
Instead of thinking about various types of risk as standalone (and taking a siloed approach to detection and prevention), what if we considered each type of risk as merely a point on a larger risk continuum and thought about ways to more efficiently—and
effectively—create strategies, build our risk organizations and detect/prevent against threats from all risks? Afterall, a loss that starts as a compliance threat can eventually end up as a fraud threat—risking losses on two fronts: regulatory fines and hard-dollar
losses from fraud.
For example, someone using a synthetic ID to open a new account has bypassed KYC/CDD controls (a compliance threat). Later, after nurturing the banking relationship and opening and maxing out a line of credit, they fall off the radar without paying, leaving
the financial institution with a write-off (a fraud loss). The financial institution faces a two-pronged threat from a single incident.
Financial institutions must reengineer risk management strategies and systems to gain full visibility into operations—detection and prevention systems must be leveraged to full efficiency and risk management teams must be reading off the same page.
Holistic Risk Management Using a Single Platform
The good news is that expensive investments in enterprise fraud and compliance solutions aren’t necessary. While the largest financial institutions may require more sophisticated enterprise systems or a suite of best-in-class point solutions with expensive
custom integrations, most community banks and small to mid-sized credit unions can leverage a single platform to perform both fraud detection and prevention and basic compliance checks at the same time.
Here is the minimum functionality required of a financial crime solution to leverage fraud and compliance risk mitigation from a single solution:
Integration with trusted third-party data intelligence providers so the system works in the background to confirm that all the data input by applicants checks out when compared against publicly available information sourced from a wide range of records and
digital resources before a consumer is onboarded.
The ability to leverage integration to third parties that perform checks against government watch lists and sanction lists for AML compliance.
Automated ongoing transaction monitoring to flag high-risk actions or high-value transactions that may signal money laundering, terrorist or other criminal activity.
Integrated machine learning (ML) to perform large volumes of account opening, application, transaction and payment transaction monitoring in near real-time with the highest degree of accuracy.
A proven track record of delivering highly accurate results to zero-in on suspicious activity while eliminating friction and lost business due to false positives, thereby ensuring a top-notch consumer and employee experience.
The ability to customize and refine risk profiles based on a financial institution’s unique risk tolerance level and operating environment.
A Unified Platform – A Single Solution for Fraud and Compliance Risk Management
Harnessing a turnkey, customizable fraud detection and compliance automation platform checks all the above criteria and more to stop fraud at the source while minimizing friction for legitimate applicants because its ML capabilities help eliminate false-positives—at
a fraction of the cost and time to implement as expensive enterprise solutions.
Already integrated with trusted third-party data intelligence providers and can be deployed out of the box with built-in rules or customized so rules can be added, deleted or adjusted (by business users using drag & drop functionality) based on your institution’s
unique risk profile and tolerances.
Impact top line revenues by eliminating false positives that risk abandonment from legitimate customers or members while achieving a high degree of accuracy in fraud detection.
Protects in real-time across all channels wherever fraudsters attempt to strike: new account applications, loan applications, suspicious activity, credit card transactions and P2P payments.