AVANTGARD
Receivables, treasury, and payments solutions and services
TURNING PROBABILITY
INTO PROFIT
USING RISK-BASED
COLLECTIONS TO QUANTIFY
FUTURE CASH FLOW
C.J. Wimley
executive vice president of trade liquidity solutions,
for SunGard’s AvantGard business
Overview
Risk-based collections
Cash flow forecasting has never been more important and it’s
no secret in today’s market that for a company to maintain a
healthy cash flow, it needs to be doing business with healthy
customers. Applying the correct approaches to assessing a
customers’ financial health, and the risk associated with their
business has long been at the forefront of everyone’s minds.
Whether it be foreign exchange, counterparty, interest rate,
market or credit risk, assessing all of these measures of risk is
of paramount importance.
There is a multitude of ways to apply risk-based collections, all
of which may apply to one company’s trade receivable
portfolio given the vast differences in the customers that have
open credit lines with the company. The differences in these
customers’ ability to pay, their credit rating based on agency
data, their industry, their geographic location, the invoice
value, age of balance, their remaining credit limit, their ability
to use alternative methods of payment, their historical
payment behaviour and the commercial risk involved (the risk
of losing the customer), must all be analysed to ascertain how
to reap the highest return on the investment the company has
made by extending them payment terms. But perhaps the
single biggest factor in determining how to best use a specific
receivable is the probability of payment. Assigning a
probability of late payment or of loss that utilises all the other
factors mentioned, provides an organisation with the best
information with which to segment and treat receivables. If a
company can classify their receivables into groups of
customers - those with a high probability of on-time payment
versus those that will be delinquent versus those that have a
high probability of loss - they will be able to apply specific
treatments to each of those segments of the portfolio that will
result in generating the most liquidity for the least cost.
However, when it specifically comes to assessing the credit
worthiness of a customer, traditional risk management fails to
consider ‘Cash at Risk’ (CAR) - the risk tied up in one of your
biggest assets, the trade receivables portfolio. Outstanding
balances from the accounts receivables (A/R) process typically
account for the largest source of potential funds available to
any company. Hence monitoring the risk of ‘if and when’ that
cash will come in, not just today but in the future, is crucial to
accurately quantifying your company’s cash flow and in turn
your ability to invest and borrow against it.
From a study commissioned by SunGard last year, it was found
that while 34% of participants reported using their receivables
as part of their overall capital structure, 81% were not
performing any kind of risk analysis on the entire portfolio on
a monthly basis. This lack of control and understanding can
impact the decisions you and your organisation make on how
to most effectively manage this cash.
There seems little doubt that being able to quantify the
probability of delinquency for all receivables allows us to
develop the necessary financial strategies with which to make
informed business decisions. Essentially we need to be
performing behavioural analysis on our trade receivables to
measure the statistical probability of the customers paying on
time. Statistical modelling will allow companies to view their
receivables and sales forecasts with a critical eye. And by
determining the customer’s propensity to pay - and when they
pay - companies can deliver more accurate cash forecasts.
Having moved from a more judgmental approach to portfolio scoring, part for collections and part for
credit, we now score a large portion of our receivables. We have increased the frequency of our credit
scoring to almost daily and we have risk scores on the lowest risk customers on demand at any time.
We use this for supplier risk to look at their credit and even real-estate and sub leasing deals, and then
can incorporate the information into other areas such as cash flow forecasting.
Steve Strong
global credit risk manager,
Google
2 Turning probability into profit – Using risk-based collections to quantify future cash flow
Technology lends a helping hand
Leveraging your risk score to
quantify future cash flow
A recent survey conducted by analyst house Aite Group
confirms that risk analysis forms a key component of accurate
cash forecasting and that the role of the treasurer is evolving
to become increasingly more strategic. The ability to provide
more predictive and intelligent information is an increasing
demand and one where sophisticated technological tools
may be required. With that said, the study also showed that if
data from the A/R portfolio is indeed being used to help
quantify future cash flow, by far the majority is still doing it on
a manual basis.
SunGard’s Predictive Metrics was established in 1995 to
provide automated analytics and predictive credit scoring for
B2B and B2C businesses. Pioneers in using a company’s own
internal A/R data, Predictive Metrics is able to create statistical
portfolio scoring to quantify specific risk probabilities on your
accounts. And it is that capability that most separates it from
generic credit agency data or in-house judgmental-based
scoring which is formed purely on varying individuals’
experiences and opinions. The scores produced as the
product of statistical-based scoring essentially provide a
measure of the risk that a given customer will pay their bill on
a timely basis. The standard output from a statistical-based
scoring system includes not only a credit score but, but also
the probability that the account will go bad i.e. Probability of
Bad (PBAD) within a specified period from the scoring date,
usually six months, and an estimate of the cash value of the
account that is at risk. These values, when properly applied,
will aid you in allocating collection resources to specific
accounts such that the return on investment (ROI) from
collection operations will be maximized. In more simple terms,
the statistical modelling leverages historical payment data and
accounts receivable files in order to predict the probability (%)
of a specific customer becoming delinquent at some point
during the six months after the score date. This information
can then be used to drive collection strategies, improve credit
decisions and quantify future cash flow.
By knowing and using the probability of the occurrence of
specific credit and collection events, it is possible to optimise
the allocation of the resources available in a given credit and
collections environment, thereby developing strategies that
mitigate the possibility of negative results, while
simultaneously increasing the credit lines of low risk accounts
and providing the opportunity for additional revenues. For
example, where a particular collection strategy based on a
more judgmental model may not have been working well, it is
extremely difficult to determine which factors and weights
need to be adjusted. However, with a statistical risk-based
score it is a straight forward process to determine which
variables are causing the problem and the information is used
to drive a different approach and adjust the strategy
accordingly. As a result of better collections prioritization,
days sales outstanding (DSO) and bad debt is reduced and
cash flow is increased.
The prediction and probability of current and future payment
behaviour can be used to help identify opportunities to grow
the value of the perpetual asset that is the trade receivables
portfolio, and in turn impact future cash flows. Another key
element often overlooked is foreign receivables. Often treated
differently in a capital structure, foreign receivables represent
an increased risk and this should be factored into the cash
forecasts. Overlaid with the sales forecast, the detail around
trade receivables will help you gain a more accurate view.
To conclude, performing risk-based statistical scoring should
be an integral part of any collections practice and one that
should always form a key component of the cash flow
forecasting process. Whether it is a need to drive and predict
free cash flow, an interest in mitigating bad debt or even a
desire to reduce counterparty risk around suppliers, treasurers
are increasingly required to take a bigger interest in trade
receivables. We see this as a developing story and the more
that treasury becomes involved, the greater the integration
between these functions and the more effectively companies
will be able to quantify future cash flow, in turn contemplating
their receivables for borrowing and securitization and
ultimately improving their overall financial health.
We have developed a risk strategy
whereby we score our portfolios
quarterly, but only about 50% of our
locations are doing it at the current time.
Bill Uhrich
director of corporate credit,
Dresser GE Energy
www.sungard.com/avantgard 3
About SunGard’s AvantGard
The AvantGard solution suite includes credit risk modeling, collections
management, treasury risk analysis, cash management, payments system
integration, and payments execution delivered directly to corporations or via
banking partners. AvantGard solutions help consolidate data from multiple in-house
systems, drive workflow and provide connectivity to a broad range of trading
partners including banks, SWIFT, credit data providers, FX platforms, money
markets, and market data. The technology is supported by a full range of services,
including managed cloud services, treasury operations management, SWIFT
administration, managed bank connectivity, bank on-boarding, and vendor
enrollment, and is delivered by a team of domain experts.
About SunGard
SunGard is one of the world’s leading software and technology services companies.
SunGard has more than 17,000 employees and serves approximately 25,000
customers in more than 70 countries. SunGard provides software and processing
solutions for financial services, education and the public sector. SunGard also
provides disaster recovery services, managed IT services, information availability
consulting services and business continuity management software. With annual
revenue of about $4.5 billion, SunGard is the largest privately held software and
services company and is ranked 480 on the Fortune 500. For more information,
please visit www.sungard.com.
©2012 SunGard.
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