Predicting the Future: It’s Time to Consolidate

Predictive Risk Scoring

The ability to score clients based on their transaction history can provide valuable insights that support more accurate cash flow forecasting and provide more predictable and effective working capital management.

Using pattern recognition and predictive characteristics, finance teams can effectively target accounts that pose the highest risk. This machine learning framework as part of your cash application provides:

• Payment date predictor – predict when a customer is most likely to pay based on experience and payment behaviour. 
• Late payment forecasting – looking in several places for payment due dates in multiple currencies is always going to be a challenge for clients who are reactive. This can result in customers only being contacted when a payment is already late which can impact the financial close. 
• Blocked order predictor – predicts blocked orders and recommends actions to avoid an order being stopped before it happens.
• Dispute validity predictor – predicts the list of all valid and invalid deductions with a confidence score and matches with reason codes. Finance teams waste hours looking through unresolved deductions with research showing that around 15-20% of disputes are not valid.

Having these capabilities on a single, integrated platform will enable finance teams to spend more time focusing on the right customer interactions and solving problems that are likely to pose the most threat to cash flow.

Boost Employee Productivity

The finance department has many repetitive, routine tasks that often involve manually inputting invoices, tracking receivables and logging payment transactions. These low return activities coupled with an inability to positively impact client satisfaction leave employees frustrated and demoralised. 

AI, combined with RPA, has the power to disrupt the traditional finance back office. Automation can speed up mundane tasks with AI mining the data for insights that can be leveraged by the front office – special offers, cross-selling opportunities, and investment opportunities. 

An accounts receivables solution powered by these innovations can radically change how an order to cash team operates by enabling:

• Dynamic worklist prioritisation – organises a collector’s and a deduction analyst’s worklist sorted by priority.
• Intelligent dashboards – one version of the truth that identifies the most critical customer/account based on the past-due date details and the collection amount.
• Faster search times – a single platform allows the finance team to function faster, decreasing their search time looking for different sources of data at the start of each day.

By expanding capabilities, talent pools, and leveraging powerful technology, teams can take on new operational practices and support complex processes that add more value to the organisation.

Transforming Customer Interactions

A single I2C platform with AI eliminates the need for customers to have to wait for an answer – be it a simple product or billing query or a credit decision. Chatbots and virtual assistants can answer common questions, enabling customer service reps to focus on more complex problems.

Examples of AI in action include: 

• Quicker decision-making – live customer calls are automatically transcribed, while the system highlights and captures the most critical points, which get saved in the call log. Analysts can make quick decisions based on the intelligent action items populated by the system from the call.
• Faster responses – draft emails can be prepared by a digital assistant with the ability to attach relevant documents based upon the interaction with a customer. The analyst can then manually configure the email if required and send it out. 
• Intelligence to predict the next best action – collate all emails into a single repository. A digital assistant enables further automation by following up phone calls with suggested emails and action items based on the discussion with the customer.

A Single Platform is Driving the Future of Finance 

“While demand for first-time I2C application purchase is anchored on enabling automation and improving efficiencies, the shift toward an integrated application to manage end-to-end I2C processes has become a key requirement for most finance organisations”

Gartner: Magic Quadrant for Integrated Invoice-to-Cash Applications

Running a siloed order to cash process results in lost opportunities to collect receivables, lack of credit visibility, risk exposure, and a poor customer experience.

An AI-powered integrated receivables platform removes the silos between credit, cash application collections, deductions, billing, and payments and provides a complete view of the customer and their interactions. 

Monitoring this data can help predict payment patterns and customer behaviour, resulting in the delivery of better offerings and a more seamless client experience. 

“By leveraging an end-to-end accounts receivable platform, we have been able to increase turnaround and response times, improve the effectiveness of collections and increase Straight-Through-Processing rates. We are also able to track team KPIs in real-time. This has been a critical key success factor in demonstrating value to other parts of the organisation.”

Paul Buckham, Global Process Owner, Order to Cash, AstraZeneca

By incorporating AI and machine learning on the same receivable’s platform, organisations will reduce the number of manual transactions posted, close their books faster and reduce the cost of regulatory compliance. Companies that do not leverage these capabilities fully, will inevitably lose market share and struggle to build long-lasting relationships with their customers. 

HighRadius was recently named a Leader in the 2022 Gartner Magic Quadrant for Integrated Invoice-to-Cash (I2C) Applications. For more information and to download a free copy of the report,click here