By simplifying data preparation, connecting all your data in a single repository, and providing flexible, powerful rules and scoring mechanisms, DataWalk uniquely provides breakthrough levels of analytic agility. DataWalk helps enable procurement fraud detection, and also helps accelerate procurement fraud investigation.
Easily prepare and connect All your dataKey procurement data associated with vendors, customers, payments, and receivables may reside in different systems which cannot be easily reconciled, and this greatly complicates procurement fraud detection and investigation. DataWalk eliminates this challenge by enabling you to easily ingest any or all of your internal data, connect it all together, and then integrate this with any desired external data such as sanctions lists, PEP lists, or subscription services. DataWalk then enables you to do sophisticated analyses across all this data, through a simple visual interface, to accelerate and simplify procurement fraud detection. You can also easily ingest and connect case-specific content such as billing data or emails with just a few clicks in support of procurement fraud investigations. Unlike other systems, DataWalk does not require that you first clean your data, as DataWalk can ingest your data the way it is, and then enable you to transform and clean the data as needed and on your own, without requiring work from IT or data owners.
DataWalk is based on a Big Data architecture which can easily handle many billions of records, so you don’t need to worry about running out of capacity even if you have vast amounts of data.
Smart entity resolutionFailing to have clean vendor data can result in duplicate entities and provides fraudsters with a vulnerability to exploit. DataWalk enables you to perform entity resolution by indicating common attributes and similarities which may indicate duplicates across vendor data, and this can be key for procurement fraud detection. By leveraging machine learning capabilities, DataWalk is able to automatically recognize addresses of vendors in various formats which might be downloaded from external data sources, and normalize them in just a few seconds. This can be done instantly without a big data clean-up project, and without touching the original records.*
Library of editable predefined indicatorsDataWalk provides a library of predefined indicators and scenarios for employee and contractor frauds. You can easily modify existing rules or create new rules to maximize intelligence gathered from your data. All of this is done via an intuitive visual interface which does not require you to have expertise in SQL, programming, or a scripting language. DataWalk provides you with extraordinary agility for testing new hypotheses, and for identifying suspicious patterns and hidden links across all your data. These unique capabilities can significantly increase your procurement fraud detection capabilities.
Proactively detect procurement fraud, waste and abuseYou can easily combine and weight multiple rules to create a powerful procurement fraud detection system to identify the people, organizations, or transactions which are most suspicious. This enables you to utilize more accurate, intelligent risk scoring to conduct ongoing procurement risk assessments across your procurement systems and supply chain. Scores can be further enriched by combining rules/indicators with machine learning algorithms and data clustering algorithms (Social Network Analysis). Being able to easily generate and tune these sophisticated scores can help you to significantly reduce false positives in weeks, or even days. Scoring can also be used to perform checks on new contractors and new employees entering high-risk groups.
Dramatically accelerate procurement fraud investigationsSeeing all information around the highest scoring, highest risk people, organizations or transactions - including relationships, components and which rules which were triggered - enables you to start your procurement fraud investigations. DataWalk dramatically accelerates procurement fraud investigations, providing tools for forensic analysis such as Folders (which provides a single place where you can see all information about a person, case, or anything else) and link charts (without the overhead typically associated with preparing for link analysis). DataWalk link charts enable you to identify hidden relationships and view large networks of interconnected objects to quickly spot patterns or anomalies. DataWalk link charts also integrate with maps, support time-series analysis, visualization of flows, and include Social Network Analysis heuristics.
Automate your anti-fraud processesTo further enhance procurement fraud detection capabilities, DataWalk provides a powerful alerting capability to monitor anything across all your data, including suspicious conditions associated with contractors, employees, invoices, proposals, or anything else. Alerts can be easily configured and edited, and data is constantly scanned to check against risk indicators.
Real time collaborationDataWalk is designed as a collaborative, server-based, multi-user software platform which enables multiple users to work on the same objects without data synchronization. Private data sets, connections, analyses and investigation files can be seamlessly shared with authorized colleagues within your organization. DataWalk enables you to easily share comments on cases, individual data elements, or connections on a link chart, which can help facilitate procurement fraud investigations.
Fast time-to-results, at a fraction of the costDataWalk enables you to start getting results with your new system in days, not months or years. Then after such a rapid implementation, you can always get fast results as you can go from idea through data enrichment, scoring, link analysis, and graph algorithms to final conclusions, in minutes or hours.
DataWalk is a fraction of the price of alternative Enterprise-class systems, both at initial purchase, and over the lifetime of the solution.
---------- * address resolution capabilities available summer 2019