Success in the digital era

Why operators are turning to enterprise contract assurance

As telcos are forced to collaborate with digital wallets, ecommerce can content partners, so they have to maintain strong contract assurance. And I bet you never knew that AI has a key role to play here? Ashwin Menon, product head, business assurance at Subex explains

No longer confined to conventional interactions, operator services are quickly expanding to include collaboration with digital wallets, ecommerce platforms and content partners. The breadth and diversity of the growing range of products and services reflect a deep reliance on an extensive network of partners – underscoring the importance of maintaining robust contract assurance practices.

Given the complexity and scale of these partnerships, the success of a telco’s B2B operations necessitates advanced strategies and tools to ensure compliance, performance, and strategic alliance across all contractual obligations.

This dynamic environment challenges enterprises to maintain a delicate balance between rigorous contract assurance practices and the agility to pivot in response to new opportunities and challenges. To meet these growing needs and navigate the dynamics of partner relationships, service providers are increasingly turning to contract assurance and intelligence practices.

ADD COMPLEXITY

The ever-increasing digital expansion within the enterprise sector brings with it a surge in both the complexity and volume of contracts. With every new partnership or service offering, enterprises face a fresh set of contracts, each bearing a unique set of nuances, terms, and conditions. The proliferation of contractual agreements extends beyond the initial creation phase, posing challenges in contract management, assurance, and compliance.

These mounting complexities has put a strain on enterprise teams that are tasked with navigating through contract intricacies, while ensuring that service delivery remains in alignment with the specified contractual obligations. The success of B2B operations in today’s digital era hinges on their ability to efficiently and effectively manage and assure contracts with a multitude of partners. Resulting from the inherent inefficiencies of traditional processes, operators are faced with increasing issues such as revenue leakage and non-compliance. Further, enterprises are challenged in aligning contract terms with actual billing and service data, resulting in a misalignment that leads to a disjointed and manual validation process, which ultimately introduces non-compliance and potential revenue leakage risks, as well as considerable delays.

Inefficiency is further exacerbated by a heavy reliance on manual processes, the use of outdated systems and a lack of integration between contractual terms and operational data. To mitigate these issues, enterprises must rethink their contract management.

There’s a pressing need for a more integrated, automated approach that can streamline processes, minimise errors, and enhance compliance and revenue assurance. By achieving agility and precision in contract management, enterprises are better able to adapt to the rapidly evolving demands of the digital economy, helping to ensure operational success. To streamline and enhance the contract assurance process, deep learning technologies are quickly becoming a necessity.

LEVERAGING AI AND DEEP LEARNING MODELS

AI and deep learning technologies enables enterprises to enhance their contract assurance processes by automating the extraction, analysis and validation of contract terms against actual operational data. There are five key areas of a deep learning-based solution for contract assurance – automated contract management, integration with operational data, scalability and speed, flexibility and customisation, and operational and financial benefits.

1. Automated contract management: By leveraging AI technology and deep learning algorithms, operators are able to process and analyse contracts regardless of format.

2. Integration with operational data: The platform’s ability to integrate with enterprise systems allows for the automatic validation of contract terms against billing, service delivery, and inventory data, ensuring that discrepancies in contractual obligations are identified in real time.

3. Scalability and speed: Designed to handle the scale of enterprise operations, deep learning has the ability to quickly process hundreds of contracts and validate terms against vast datasets, reducing time and effort spent on contract assurance.

4. Flexibility and customisation: Recognising the diverse nature of contracts and business models, the solution provides the flexibility to adapt to different contract formats and terms. Additionally, they support the inclusion of supplemental languages and custom requirements, ensuring that it remains effective across various operational contexts.

The deployment of deep learning technologies in enterprise contract assurance marks the dawn of a new era in how enterprises manage and assure their contractual obligations. By automating and streamlining the contract assurance process, enterprises can not only mitigate risks, but also unlock operational efficiencies, allowing them to overcome challenges and focus on innovation for strategic growth.

Ashwin Menon is product head, business assurance at Subex www.subex.com