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Insights and Expertise

Why startups risk clearly what will go through the account and what the
new client will be using the services for. They check the
account freezes, and industry, the potential incoming and outgoing amounts,
how regularly they receive payments or pay out suppli-
ers, where these transactions originate from, or are going
how to prevent it to, in what currency, and who the potential counterparties
are. These all represent important information which can
affect the risk profile.

But if the potential customer is a simple startup and has
no actual data about its clients, jurisdictions, turnover
or transaction volumes, it can only send projections and
business plans, which are usually either very optimistic
or too reserved. Of course, no one can see the future, but
when it comes to financial planning, it is almost impos-
sible to determine how well the operation will take off in
certain jurisdictions, like Europe, in the States or in Asia,
or whether it will take off at all.
Prediction versus facts

Once the providers collect all the relevant data about their
By Viktoria Soltesz potential clients, they input them in their special risk soft-
PSP Angels ware. This system continuously compares the real trans-
actions against the information entered at the start, judg-
odern fintechs and banks promise security ing every deviation as potential risk, which triggers auto-
and convenience, but the very same systems mated alerts. Even small differences, like receiving funds
that guard the global economy can also from new clients or in unexpected currencies, can trigger
M disrupt cash flow within hours. We have all a review or account or even a complete freeze.
seen what damage it can cause when banks block a trans-
action, demand more documents, or even freeze accounts When growth looks suspicious
completely, but these issues are often predictable with Banking algorithms operate by prediction, not logic. Once
proper planning. the initial profile is saved, the system expects the business
to stay within that framework forever, or at least close to
Cash flow headaches stay away when we maintain a clear it. But when the company grows, enters new markets or
and open relationship with our banks and financial insti- starts processing higher volumes, the algorithm can trig-
tutions, presenting the purpose and background of each ger a review: the bigger the difference between what was
transaction in a straightforward way. Banks need data predicted and what happens in practice, the higher the
about our business. But what can we do if our business risk of a check.
has no information yet, because it is a startup?
Onboarding without data Of course, compliance officers have the option to review
everything and switch the account back to normal, but
When a bank, financial institution or even ISO starts a they usually ask for an explanation of why the predicted
new business relationship with a client, they all want to figures are so far off from the actual ones.
know what they are dealing with: what the opportunity
is for wrongdoing, fraud or tax evasion. These providers Industry studies (for example, Dow Jones 2022; LexisNexis
calculate risks not based on already happened facts, but 2019) suggest that around 10 to 15 percent of flagged trans-
on the assumption of what could go wrong, and measure actions require human review, during which funds may
the results in a so-called customer risk profile. remain temporarily blocked, and even though the funds
are usually, eventually released, this causes several days
The higher the opportunity of something bad happening, of delays. Firefighting operational panic and adding the
the higher the risk of that new customer is. The higher the lost opportunity costs, this can be very damaging, and
risk, the higher the fee, and obviously, the worse the terms sometimes even lethal for bootstrapped teams.
and conditions are. Certain high-risk clients are unable to
access certain financial services simply because they are Whose fault is it?
deemed not worth the risk for the providers, at all. Fraud escalation often has nothing to do with actual mis-

Information collection conduct. Banking and financial institutions are using very
sophisticated fraud alert systems, where these software
To evaluate the risk accurately, all banks and financial in- often see growth and criminal activity through the same
stitutions need to collect data about their potential client's lens because both appear as unplanned changes.
operations as well as on their money flows to understand
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