In the Administration, Finance & Control area, Piteco has developed reconciliation functions and routines for the management of large volumes of non-uniform and unstructured data coming from various company business units, which require analysis, standardisation and validation activities to use such data in their business management systems.
Semantic Data Analysis
Using logics and functions that allow for the implementation of Regular Expressions, Piteco’s solutions initiate an innovative Semantic Data Analysis process as early as when the data are uploaded from the various source systems, which facilitates the subsequent application of Machine Learning algorithms and parametric matching logics for the dynamic processing of data flows coming from different sources.
With more than 40 years of experience with Treasury projects and the technological expertise of its Software Factory, Piteco is constantly committed to researching and implementing new available technologies underlying the acquisition and processing of information. Its goal is to significantly improve business efficiency indicators through Cognitive Computing functions – to manage highly variable Treasury operations in complex scenarios through self-learning functions – and the application of algorithms and procedures that make it possible to automate subsequent data processing phases.
Machine Learning & Smart Reconciliation
Piteco leverages the new possibilities offered by technologies underlying new Machine Learning paradigms by applying them to functions dedicated to the management of Cash Collection processes and automating the entire Collection Reconciliation process, even for unstructured payments, reducing uncertain cases, in which human intervention is often required, to a minimum.
In this context, Piteco’s Match.it supports companies that have significant invoicing and collection volumes, not only automating matching between payments made and receivables due, but also significantly eliminating low value-added manual interventions, guaranteeing companies the automatic matching of up to 95% of transactions by applying mathematical algorithms that identify similarities between different pieces of information.
Sectors of Application
The distinctive feature of Piteco’s Semantic Data Matching functions is that they support non-uniform data matching processes in different business sectors and company areas, bearing witness to the in-depth customisation and parametric definition of the data structure.
Excellent results and replicable best practices have been achieved in Large-Scale Retail, for the reconciliation of cumulative payment instructions and invoices, customer credit notes, allowances and discounts.
In the Consumer Credit area, optimising the reconciliation of collections from loan instalments.
In the e-commerce world, reconciling front & back end data, online orders and credit card collections, managing carriers as well as cash on delivery.
In the Insurance sector, for matching between daybooks, broker account statements and policies.
In the Utilities realm, managing the reconciliation between customer billing and any repayment plans.