APiO is developing and deploying machine learning (“ML”) algorithms (machine learning is a sub-field of Artificial Intelligence) to drive decision-making on entity validation, risk scoring, financial exposure, pricing and other aspects of invoice investing. Machine learning can analyze and correlate huge amounts of financial and operational data to find patterns which would otherwise require immense manual effort or go unnoticed to human analysts. For instance, ML algorithms can determine if suppliers are reporting accurately about revenues and expenses by inspecting their transaction history and comparing their data with that of similar businesses.
World-class data scientists have devised a risk scoring process based on a proprietary 15-step process which leverages hundreds of data points. The result is a statistical model of an entity’s financial health, its propensity to pay, likelihood of default, and anticipated timing of payment and remittance. APiO’s modeling and scoring processes are then continuously refined and improved by ongoing comparison of calculated expectations to actual results, iteration and retraining of the algorithms, and re-training of the risk engine.
APiO is also deploying ML and AI technologies to anticipate and detect fraud by comparing individual organization behavior with baseline data of normal customers so that outliers can be flagged in real-time.
This same underlying technology will be made available to banks, credit unions and other financial institutions interested in improving their loan underwriting processes, and to auditors interested in accelerating their analyses and deepening their insights into their customers true financial condition.