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Shipping & Logistics companies are amidst an unprecedented change as digitization rapidly gains ground in the industry. While asset-based carriers, forwarders and brokers have invested in digitizing various areas of the supply chain, some gaps remain. The processing of documents such as bills of lading, consignment notes, air waybills, commercial invoices, packing lists, is still, in many cases, a labor-intensive, time-consuming and paper-based process.
The completely manual, repetitive and error-prone paper-based process results in numerous challenges:
Multiple document templates used by customers often lead to inconsistencies
Errors in data capture due to manual data entry and shipper-specific business rules adversely impact delivery, customs clearance and invoicing
Delays in receiving shipment information impedes operational planning and supply chain visibility
WNS Malkom, a proprietary platform enhanced by Artificial Intelligence and Machine Learning, addresses these challenges by automating the end-to-end shipment document processing. The platform enables instant data capture through an intuitive mobile app with the highest levels of accuracy. Its Artificial Intelligence layer continuously reviews earlier shipments and records every user-made change to learn which elements are critical to quality. Additionally, an embedded business rules validation engine consistently ensures correct application of customer-specific requirements.
WNS Malkom is a versatile shipment digitization platform that can be used for a variety of shipping documents including, but not limited to:
Bill of lading
Air way bill
99% data accuracy
Fewer invoice disputes
50% cost reduction
Faster, more accurate bookings
Faster shipment visibility
An integrated, intuitive mobile scanning app to automate the shipment documentation process in real-time
Ability to auto identify and process diverse types of documents and images fed through multiple channels such as e-mail, cloud folders and mobile apps
Intelligent OCR coupled with an Artificial Intelligence layer to automatically capture data (unstructured data and unstructured formats) with high efficiency
Unsupervised Machine Learning through advanced forecasting of attributes in various fields basis the use of historical trends and database
Custom business rule engine to create customer-specific rules on-the-go for any process
Robust workflow built to scale to support multiple users across multiple geos with in-built exceptions handling and dynamic task allocation mechanism
In-built analytics engine to provide interactive dashboards for monitoring daily performance, volume forecast, business insights and other Order-to-Cash metrics
Seamless integration into customers’ TMS through API, EDI or RPA
We combine deep industry insights with an understanding of the unique needs of shipping lines, ground carriers, air express, NVOCCs and forwarders to offer industry-best practices and expertise to our clients.
The solution embeds Artificial Intelligence-enhanced data extraction and contextualization, advanced Machine Learning algorithms and a fully configurable workflow to streamline the documentation process.
Machine Learning algorithms validate extracted data with your master databases and shipment history to drive unparalleled documentation accuracy.
WNS Malkom utilizes leading edge cloud-based (AWS & MS Azure) serverless architecture built for speed and scale with guaranteed availability.
Shipment information processed in WNS Malkom is integrated to your TMS through APIs or Robotic Process Automation. WNS Malkom also uses your TMS’ databases to ensure that updated customer account information and business rules are part of the data extraction.