Billtrust Introduces AI Tools to Provide Finance Professionals with Business Insights

Billtrust, a B2B order-to-cash and digital payments market leader, announced new AI functionality within its accounts receivable software platform to empower finance professionals to better understand their business, make strategic decisions and engage customers more effectively.

Billtrust has introduced a new generative AI tool, Billtrust Finance Co-Pilot, which offers unparalleled, deep analysis of “a customer’s data, allowing users to input queries in plain language and obtain instant insights and recommendations.”

Complementing Finance Co-Pilot “are two new analytics modules, Payments Analytics and Cash Application Analytics, which are user-friendly, self-service reporting dashboards within the Billtrust platform.”

Used together, finance professionals can “obtain information to speed decision making while getting a holistic view of their business in real time, leading to faster payments, improved cash flow and working capital, and more satisfied customers.”

Ahsan Shah, Senior Vice President of Data Intelligence, Billtrust said:

“Historically, it has been a struggle for finance teams to aggregate their data for better decision making. Our new tools apply analytics and AI to customer datasets, helping users gain unparallelled insights and a 360-degree view of their entire order-to-cash process including payment trends, buyer behavior, risk analysis and anomaly detection. Ultimately, our customers will benefit from dynamic analytics, real-time data and insights, and the ability to make quick, smart decisions which position their business for success.”

Kevin Permenter, Senior Research Director, Enterprise Applications at IDC, a global market intelligence firm, said:

“Cutting-edge accounts receivable technology involves a rapidly developing set of tools including advanced analytics and generative AI. Billtrust has made significant investments to build a robust, long-term AI and analytics strategy to help its customers truly harness the enormous potential in AI with the goal of helping users achieve positive business outcomes.”

Using Billtrust’s years of experience and extensive financial data repository, the generative AI-powered Finance Co-Pilot is optimized “to provide unmatched views of customers’ cash flow efficiency based on key accounts receivable user personas.”

Finance Co-Pilot provides deep analysis “with prescriptive insights and cognitive workflows to benchmark, answer questions and give recommendations – all from a customer’s own data.”

It can answer multi-step queries such as, “What is the total amount billed for account X?” and “What are my bottom X accounts with the worst payment history?”

With predefined questions that automatically generate prompts, as well as built-in data security features and access control mechanisms “to protect sensitive information, users can easily and securely access their data for unmatched insights.”

Payments Analytics supports strategic decision-making and empowers users “to evangelize broader business tactics like payment acceptance and surcharging strategies, all while offering a clearer understanding of buyer behavior and trends such as timeliness, payment preferences, and variability.”

It also enables a “more targeted customer engagement strategy for improved outreach and transitioning buyers to online platforms.”

Cash Application Analytics enables “a refined and targeted customer engagement strategy by helping users understand data on overall matching performance, match volume and payment volume at a buyer/payer level while recognizing trends at multiple levels of detail across flexible date ranges and intervals (customer, match type, job type, job name).”

It also isolates “bad payors,” allowing users to customize the parameters on how a bad payor list is formulated.

Both Payments Analytics and Cash Application Analytics “offer enhanced data analysis capabilities including flexible time series visualization (graphical and tabular), multi-series data representation, interactive KPIs with drill-down features, comparative data examination and competitive benchmarking.”

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