Transaction signals provide a powerful way to identify potential risk factors in applicants' bank statements and open banking data, helping you make more accurate risk decisions.
In financial risk analysis, transaction signals are key indicators derived from specific behaviors, patterns, or characteristics within a financial transaction. These signals are used to assess the potential risk or trustworthiness of a transaction. They are commonly categorized into risk signals and trust signals:
Risk signals suggest that a transaction may be fraudulent, non-compliant, or otherwise problematic. They often indicate red flags that warrant further investigation.
Trust signals indicate that a transaction is likely legitimate and aligns with expected behaviors or established norms. They help reduce friction in risk assessments and improve the customer experience.
Transaction signals act as early warning indicators, highlighting patterns or activities that warrant closer attention during your risk assessment process. While these signals alone don't definitively indicate fraudulent activity, they become particularly powerful when analyzed alongside other data points in your evaluation process. These are some of the transaction signals available in Inscribe today:
When an applicant's account shows Non-Sufficient Funds (NSF) or overdraft charges, this signal is activated. Regular occurrence of these charges might indicate cash flow challenges or financial management issues.
This sophisticated detection method examines the distribution of leading digits in transaction amounts. When transactions don't follow Benford's Law's expected pattern (where smaller leading digits occur more frequently), it could suggest potential statement manipulation or peculiar spending habits.
Learn more about Benford’s Law.
The signal automatically identifies cryptocurrency trading transactions through advanced categorization of transaction descriptions. This insight helps you understand an applicant's involvement in digital asset markets and associated risks.
Using similar categorization technology, this signal identifies gambling-related transactions, providing visibility into potentially risky financial behavior.
The signal flags loan-related transactions, helping you understand an applicant's existing debt obligations and lending relationships.
For checking accounts with balances of $10,000 or more, the signal flags cases where the average daily balance exceeds 2.5 times the total monthly deposits. This unusual pattern might warrant additional scrutiny.
An unusually high frequency of round-number transactions could indicate document tampering, as authentic bank statements typically show more varied transaction amounts, which is what this signal flags.
By incorporating transaction signals into your risk assessment framework, you can:
Transaction signals represent just one layer of a comprehensive risk assessment strategy. When combined with other verification tools and data points, they provide valuable insights that can help protect your business while making informed risk decisions.
Ready to enhance your risk assessment in onboarding and underwriting? Contact us to learn more about implementing transaction signals in your evaluation process.
Alice Gregson is a Senior Product Manager at Inscribe AI. Previously she worked on account connection and lending products at Bud, an open banking provider based in the UK. Alice has her Bachelors in History from the University of Chicago and currently resides in London, England.
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