How Late Risk Data Can Turn Confident Deals Into Future Defaults

Breaking Risk Silos from Creditsafe shows how, to the regret of lenders and credit professionals, risks may go unreported or unheeded. Defaults down the line are a sign that something went wrong.

It’s not that risk teams lack access to data and tools. Instead, risk signals can appear well after deals are struck. Without these signals, lenders often succumb to pipeline pressure. That makes it easier for lenders to ignore late-arriving signals rather than applying the brakes.

Data is often siloed so different teams aren’t operating from the same playbook. According to IDC Market Research, companies lose 20–30% of their revenue annually due to inefficiencies caused by data silos. Without data sharing, risks can take a back seat to the urge to maximize volume.

Creditsafe says the core problem isn’t disagreement over the facts. More troubling is that the facts aren’t shared until late in the game. 

Chief Operating Officer for North America at Creditsafe, Steve Carpenter said that when sales and finance departments operate from different risk data, both sides lose.

“As economic uncertainty and late payments increase for businesses, misalignment between sales and finance teams can lead to higher bad debt, lost revenue, damaged customer relationships, and strained cash flow,” said Carpenter.

“Sharing credit risk data earlier in the sales process is the fastest way to reduce regret, deal friction, and cash flow strain,” he said.

When sales and finance departments operate from different risk data, both sides lose.

Hindsight is a great thing — that’s often when the dealmakers and the risk-measurers agree that a deal was flawed from the outset. Without timely risk intelligence, business moves forward with blinders on.

Different incentives lead to different outcomes. The study shows that about half of sales leaders are gung-ho despite low credit scores. But 41% of finance leaders would turn down the same deals. Lenders are often caught in this “do it” syndrome, ignoring early warnings only to be greeted with delinquencies and policy breaches.

Late risk data doesn’t carry as much punch once the contracts are signed. Little wonder that a culture develops where exceptions become routine. As overrides increase, more flaky deals end up in the books.

The damage caused by delayed risk signaling is cumulative. The friction is not limited to credit decision-making.

Research by McKinsey has identified that fragmented data environments cost trillions of dollars in lost productivity and inefficiency in decision-making across industries; as such, the costs of delayed or disconnected information are substantial at scale.

Marginal decisions pile up and poison portfolios. Creditsafe explains that the problem can suddenly become apparent. With different group incentives and siloed data, it’s only a matter of time until delinquencies rise.

The costs of delayed or disconnected information are substantial at scale.

Lenders then have to rely on back-end remedies such as collections and lawsuits. All this can happen months or years after risk governance breaks down.

Federal Reserve guidance emphasizes the need for risk monitoring systems that provide “timely reports on the financial condition, operating performance, and risk exposure of the consolidated organization” so decision-makers can “identify any adverse trends and evaluate adequately the level of risk faced by the institution.” 

Eventually, the problems mushroom. Despite aggressive growth, cash flows slow down after a long period of lax risk policies. Lenders have to pay the piper for not enforcing underwriting standards early on.

Creditsafe says don’t blame the data, blame the enforcement of credit policy (or lack thereof). One wonders what the uses of deal-kill thresholds and risk limits are if they are ignored.

Lenders must grapple with the way they design their credit policies if they want to sidestep bad deals. For example, they could embed third-party risk signals into their loan origination systems. They could also beef up automated approval limits as well as document reasons to override rejections.

In other words, let the system throttle over-eager dealmakers. Of course, competition can be relentless. Even if questionable deals go through, a good system will throw up objections or even vetoes when the risks are too high.

We are living in a time of tight money and tighter scrutiny of payment behavior. By heeding Creditsafe’s research, institutions may take a new look at their underwriting standards.

Structural failures such as late signals and siloed data shouldn’t be treated as isolated incidents. Once conditions take a turn for the worse, these issues pop up like unwanted weeds — remedies are costly and time-consuming.

Lenders should view the findings as proof that strong underwriting can be trumped by poor policy enforcement, late signals, and whether systems can prevent late-stage overrides.