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Use Case: Corporate Guarantee Fraud

Globally, the majority of commercial banks’ profits come from corporate loans. The banks use collateral to counter the risk of a potentially bad loan, and it’s called: corporate guarantee. When an entity (a corporate or a person, say, A) applies for a loan from the bank, the bank requires another entity (usually another corporate, say, B) to financially guarantee that if the original entity A fails to pay the loan back, party B will pay the loan off on A’s behalf.

A commercial bank usually deals with hundreds of thousands of, if not millions of, corporates and corporate loans. The front-office staff (sales reps) issue many loans on daily basis, and the back-office staff work on identifying potential risks associated with each corporate guarantee. This process has been traditionally laborsome and time-consuming.

There are a few typical types of frauds, intentionally or unintentionally, associated with a guarantee.

  • The simplest form of fraud:  A ⇋ B, A guarantees B and B guarantees A, this is in direct violation of any bank’s loan issuance prerequisite.
  • Forming of chain or ring guarantee:  A→B→C→D→E→A, this is slightly harder to detect, as you have to dig all the way to E, then to find that E’s guarantee for A violates the bank’s rule.
  • Forming of more complicated topologies that violate bank’s rules. For instance, an entity may be involved in many loans thus forming a forest of guarantee chains.

The immediate below diagram shows that the red-dot corporate entity guarantees 4 other corporates, forming 3 loan-guarantee triangles (Note: the triangle is the simplest form of a “guarantee ring”) and 1 loan-guarantee quadrilateral (4 parties involved).

Guarantee Rings – 4 Triangles of Corp Loan Guarantee

List Mode of Corporate Loan Guarantee Chain Detected -3 triangles & 1 quadrilateral

The above example is a zoomed-in investigation of a particular corporate, oftentimes, you would run through all or a large chunk of loan data in a batch processing fashion to understand how many violations are out there. This process can be very time-consuming given a large number of entities involved (oftentimes in the range of or exceeding millions). This is where real-time fraud detection boosted by real-time graph computing does the magic.

The below diagram shows in a 3D panoramic view the status of the bank’s current corporate loans. All loan-guarantee chains, rings and obfuscated topological structures are visualized for easy comprehension with minimal cognitive load.

Bank Loan Guarantee – A Panoramic and Holistic View

Note in the above diagram, the centrally-positioned structure involves ~100 corporates, a structure like this is very hard, if not impossible, to sort out manually, and not uncommon in real-world business practices, and may hide illegitimate guarantees that violate bank’s rules, therefore are worth further investigation.

According to some market research reports in 2016-2019, almost 40% of the corporate loans in Wenzhou, Zhejiang province of China are associated with problematic guarantee-chain or guarantee-ring that a lot of corporates are involved. It would be highly beneficial to help the banks to understand the legitimacy of each and every applying loan even before the loan is issued, and constantly monitor a loan and take precautions when a loan’s risk grows over a certain bar or enters into a risky state. Oftentimes, helping a bank take preemptive action to protect its loan will avoid the large scale ripple-effect of chaining bad loans which usually involves hundreds of millions of dollars on each case.

With the help of aggregated information from various channels, like court filings, lawsuit verdicts, social media NLP/sentiment analysis, Ultipa Graph can identify high-risk corporate (and their loans) accurately and preemptively so that the bank can decide if they should withdraw the loan to prevent further damage to bank’s assets.

The below diagram shows that the red-dotted corporate is associated with 6 lawsuits and is convicted guilty in all cases with large sums of monetary judgments holding against it, meanwhile, the bank has this corporate customer guaranteeing multiple loans for other entities (or vice versa), this is a potentially high-risk situation, so that the bank better back out of these loan engagements to prevent future losses.

High-Risk Bank Loan – Red-dot Corporate Bearing High Risk in a Guarantee-Chain

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