Knowing the customer’s complete background before agreeing to a loan will help to detect potential risks of late payment or identify payment guarantees
Good financial health, according to GDS Modellica, requires effective technology to manage debt recovery and detect identity fraud quickly.
Prevention is better than cure. For a company to stay in good financial health, it’s important to spot problems before they arise, particularly when it comes to debt collection. A key part of this is knowing the customer’s complete background before agreeing to a loan. This will reveal any previous defaults and help the company to assess the future risk of late payments and identify payment guarantees. According to Antonio García Rouco, managing director of GDS Modellica, “These days, there is a huge amount of customer data available which can be easily accessed. This can be extremely valuable for banks and means that they can use a customer’s payment history, spending habits, social media presence and even browsing habits when deciding whether to agree to a loan. New technology is emerging all the time that makes it cheaper for companies to efficiently use and store these vast amounts of data, as well as supporting their decision-making processes”.
When a bank agrees to provide a loan, they have to trust that the customer will honour their payment terms and conditions. But lending always comes with risk. To mitigate these risks, GDS Modellica offers the Modellica Collections Engine (MCE). This is a solution that evaluates the borrower’s situation using their credit history and predictive data from their connections, whether they’re an individual or an SME. This data analysis can be extremely powerful for developing the right strategies to personalise their debt recovery processes, increase efficiency and maintain long-term relationships with good customers. This technology can also help banks manage customers that may have problems in the near future. Spotting a potential default before it happens is always the best way to reduce the portfolio in arrears, as well as increase customer loyalty and profitability.
Defaults don’t just knock company accounts out of shape; they can often put the company’s very survival in jeopardy. Sometimes, it might just be a late payment, but on other occasions, the situation is more complex. In some circumstances, companies can be left with no option other than to delegate the task to experienced professionals, who will aim to recover the debt using different technologies and a range plans and techniques that provide a more complete view of the constantly changing economic situation.
These days, technologies like artificial intelligence, intensive strategy management, chatbots and virtual assistants are being used to automate and streamline debt collection and recovery processes. These types of technology can help make intelligent interfaces more personal and more human as we look to the future.
1. Segment your debts according to the way they need to be handled. Before going down any legal channels, you should exhaust all other possible routes. This includes seeking support from professionals, using technology and can be either in person or online.
2. Timing is critical. If you act fast, you’ll have a greater chance of recovering the debt. Make use of technology to quickly implement new strategies in response to changes in customer behaviour or the performance of your portfolios. You should also continuously measure and assess your strategies to ensure that they’re providing good results.
3. Any negotiation process should be direct and personalised if you want the greatest chance of recovering the debt. It’s important to make your negotiation and payment processes as flexible as possible for a defaulting customer. Approach each case in an individual way and provide convenient payment options whether online, using chatbots and payment gateways, or in physical branches.
4. If you use customer history efficiently, you’ll be able to segment or design your strategies in accordance with objective criteria, such as the amount due, days in arrears, number of non-payments, type of customer, historic behaviour, etc.
5. Detailed tracking will improve the management of your debt collection process. Using automated processes will enable you to spot problems before they arise and act quickly, and this will make a big difference to your results. Prioritise the necessary steps, focus on debtors who are likely to pay and aim to provide convenient payment methods in order to resolve the debt.
6. Avoid wasting time going down dead ends. Identify and separate any fraudulent accounts hidden in your loan portfolio. Many will probably be non-recoverable, and the rest will require a totally different approach.
7. Taking both broad and detailed approaches, separate accounts that should be managed internally (and decide how long for) and decide which should be passed to external agencies. Evaluate the performance of each agency so that you can bear this in mind next time you distribute accounts.
8. Intelligent systems should help and make a difference even if the process is managed manually by a person. Use of the correct language based on predefined scripts, with personalised and prepared reasoning will convert many actions into payment commitments and later revenue.
9. Prioritise actions and focus on customers who will pay. Try to find the right options to facilitate payment and address the debt.
10. Consider potential legal problems and solutions. Make sure that a cost-benefit assessment forms part of any automated processes.
According to García Rouco, companies should put more faith in powerful, innovative technologies like automation, prediction, advanced analysis and artificial intelligence. These technologies will help to transform current business models by helping to develop intelligent, precise and non-intrusive strategies.
Technology should make it possible to use external sources of information, and having access to rich data sources will provide a more complete view of your customer portfolio, enabling smart decisions based on data analysis. At GDS Modellica, they use DataView360, a solution which makes it possible to pool together data from internal and external sources, such as credit bureaus, fraud agencies and ID verification services. DataView360’s power and flexibility, along with their experience and knowledge, makes it possible to mitigate risks and provide a flexible approach for managing cases on a large scale. GDS Modellica can help companies precisely and intelligently segment their debtor accounts and gain greater visibility of customer information. This then makes it possible to increase efficiency and strategically focus activity to increase debt recovery, direct collection efforts, automate decisions and increase the retention of those good customers who simply have one-off problems.