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Today we are going to talk about how to anticipate payment problems and anticipate problems for those customers who are not currently giving it to you.
At Gamco we develop software based on Artificial Intelligence and we have worked in recent years with large corporations and thanks to this, today we offer packaged solutions for small and medium enterprises - SMEs.
Here we will show you how to anticipate defaults and foresee payment problems before they happen. Not only for those customers who are already showing symptoms or those who cannot pay those invoices that are being issued, but also for those customers who have not yet experienced payment problems.
To do so, it is necessary to anticipate such problems and not only based on managing the debts of delinquent customers; Gamco has defined four key pillars on which to build in order to mitigate the impact on the business.
The first pillar is the Artificial Intelligence where machine learning generates predictive models and its objective is to make predictions, but not only to make a prediction, but to act according to that prediction in order to minimize the impact of non-payments on the business.
Once it is foreseen which customers may give us payment problems, we need to know how we are going to avoid that non-payment or minimize its impact on the business accounts?
In order to have a first level of knowledge and define the problem, it is necessary to: work with data, know our customer portfolio, which customers we are billing, what products, services or behaviors our customers are having according to the payments of those invoices.
Another axis to be taken into account is the axis of execution. There is no point in having good data or being able to exploit them to make predictions, if we do not act and, above all, do not act to customer loyalty to provide a good service and, above all, to ensure that there are no problems with the invoices that are being invested..
At Gamco, which has been dedicated to AI for more than 10 years, we have a software based on Artificial Intelligence that includes the axis of the data available to companies to PREDICT IMPAGES.
Fundamentally, this data allows us to know the customer and forecast payment behavior, knowing at all times what is being billed, at what price, when the customer is paying, whether or not there is an impact on these payments and, above all, what policies are in place.
This can be as easy as looking at the payment terms of that customer, seeing and alerting whoever manages the customer's account or directly going to arrange with a third party, such as a payment insurance/debt recovery service to manage that debt through management software that you have integrated into your company.
For example, GAMCO's ARM (ADVANCED RISK MANAGEMENT) is an advanced risk management software that manages the entire risk chain.. From the admission, including fraud, the monitoring of the risk we already have within the company of those customers with whom we are working, the forecast of possible non-payments, the avoidance mechanisms as mitigation of that predicted non-payment and, once the debt is confirmed, knowing the best way to deal with the recovery of those unpaid invoices.
This has already been demonstrated and tested in large corporations such as large financial institutions. Below we share with you a real example of one of our risk management software:
This graph shows a retail customer loan portfolio with different colored bars to indicate the level of default alert.
If we compare these pairs of bars, what is shown are the customers managed with the procedures that the entity had in place (the bars on the right) versus the customers managed with our risk management software.
As you can see, we have been able to lower our non-payment costs by an average of approximately 28%.. All this translates into a very significant return of money.
If we zoom in on that graph, we can see the ARM group (customers that are being managed by Gamco's ARM systems), versus customers that are being managed with other statistical models:
In this particular case, the portfolio was billions of euros and we can see how this translates into hundreds of millions of euros of savings for the company. It is not only an economic benefit but also in hours spent, in loyalty of customers who are really good for the company, supporting managers/staff so that they can have more time to perform their tasks while the AI supported software works to predict and guide us in a simple way on how to act depending on the severity of the predicted customer default.
This type of technology is not only available to large corporations, but also to SMEs thanks to GAMCO's packaged solutions.
Its implementation is very simple since only two inputs to our system are needed:
Making use of our software "as a Service"We are able to deploy in a simple way in the systems that the company currently has, all our technology without affecting practically nothing in the infrastructure or in the databases, being able to:
Deploying this type of solution to a specific customer is usually a very fast process and requires 3 steps:
Automatic synchronization:
2. Auto-tuning of models:
3. Integration with third parties:
In this machine learning the software learns from the data of each company where it reflects: What are my customers, what are my services, what are the prices, what is the turnover, and in short to know What is the behavior of individual customers?
The system learns when that "good customer" is currently paying and suddenly changes its behavior, which can lead to invoice payment problems in the future.
This whole process usually takes 10 days. It is estimated in two days of staff to make the data dump and from there we start working with an analysis tailored to each company to know what is the way of working of that company and what are the mechanisms they have to manage debts or, rather, the predictions of defaults that we will have forecasts of delinquent customers.
Start with a free evaluation!
If you found it interesting, we leave you with GAMCO's participation in the Business+ ' event.Financial Vision 2022'. In this video, our CEO Fernando Pavón, will explain everything we have seen. Don't miss it!
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