XU: Chaser has released a number of innovative features over the past year, what’s the overall mission?
SD: Chaser’s mission is to give SMEs worldwide the confidence that they will get paid for their work, help them reduce late payments, save time, and improve cash flow in an efficient and friendly way.
With the increased availability of artificial intelligence and machine learning technology, Chaser has been able to offer SMEs cutting-edge technology to further improve their chances of receiving timely payments from customers.
XU: Chaser's recent success includes the development and implementation of AI features. Could you delve into how these features cater to the needs of credit and collections teams?
SD: 50% of businesses spend 4 or more hours every week on their receivables tasks. This time goes to tasks like working out which customers to chase, when, and how often. In total businesses waste a predicted 56.4 million hours per year on these types of tasks, according to QuickBooks.
The introduction of these AI features helps credit and collections teams significantly cut down the time they spend on these time-consuming tasks. Currently, they include Recommended chasing times, Payer ratings, and a Late payment predictor.
XU: Can you tell me about how you recommend chasing times using AI?
SD: Recommended chasing times analyse data on thousands of B2B payments to suggest a custom, optimal time and day to send customer payment reminders to increase the chance of payment. This new feature uses AI to let SMEs reach customers exactly when they’re most likely to pay, automatically.
XU: How do AI-generated Payer ratings help your users?
SD: To help businesses decide how to prioritise their collections efforts, they can use newly-released Payer ratings. Payer ratings use data on customers’ previous payment behaviour and compare trends seen across Chaser, assigning every payer an AI-generated ‘rating’. Ratings are ‘Good’/‘Average’/ ‘Bad’ and predict how likely a customer is to pay their future invoices on time. This lets SMEs who are often strapped for time see at a glance how their customers are paying, prioritise effectively, optimise their follow-up approach for different payer groups, and instantly see who their problem payers are.
XU: What insights can SMEs gain from the Late payment predictor?
SD: The Late payment predictor gives instant AI-generated predictions on how likely an invoice is to be paid late, assigning a percentage score out of 100. This gives SME finance teams instant visibility on whether to expect cash on time, problem accounts they should prioritise, and whether to pursue collections.
All of these features are designed to make life easier for credit and collections teams, improve decision-making, and help them to save time and minimise late payments.
XU: How has the implementation of AI in accounts receivables impacted financial processes for businesses?
SD: AI has had a tremendous impact on streamlining rules-based financial processes for businesses. For example, the use of machine learning algorithms can streamline tasks like loan processing and reduce risk by up to 40%. Big data analysis can help identify patterns for more accurate market predictions or fraud detection.
Ultimately, the use of AI helps finance teams run their processes more efficiently, and condense large amounts of data to help them make more informed decisions that can improve their businesses' financial outcomes.
In the context of accounts receivables, for example, we have also seen these benefits play out. We know that users who send their reminders at Recommended chasing times, using Chaser’s new AI feature, are getting paid on average 3 days faster than those who don’t utilise this technology within Chaser.
XU: Chaser has successfully helped businesses collect over $5 billion this year. Can you share some key strategies that contributed to this impressive achievement and set Chaser apart in the industry?
SD: Chaser is thrilled to have helped businesses collect $5 billion through the software in 2023, and this target was reached more than 3 months earlier than expected.
One of the key functionalities that have contributed to achieving this goal is SMS payment reminders. This lets users increase their chances of payment by sending a text message reminder to their customers’ phones. With the inclusion of payment links, SMS payment reminders give users’ customers the convenience of being able to pay invoices instantly from their phone. By using a combination of email and SMS payment reminders, SMEs have increased their chance of getting paid within a week of their invoice due date by 56%.
Although we have reached the $5 billion goal, Chaser’s mission remains the same; to support SMEs worldwide to get paid in an efficient and friendly way so that they improve cash flow.
XU: What key innovations are you looking to invest in across the next three years?
SD: Chaser is continuing to find ways to remove the manual work, stress, and uncertainty that comes with accounts receivables management. We are carefully researching which tasks and processes receivables teams spend the most time on, and are finding ways to use newly available technology to improve decision-making and automate these tasks. Ultimately, the innovations in our roadmap across the next three years aim to let finance teams move away from manual, repetitive work, aid decision-making, and let them spend more time focusing on supporting their business growth.