Sponsored: Telcos analyse data from their networks for customers and billing records, yet enterprises rarely use the massive amount of data generated by their own networks
Big data, a term coined in the 1990s, refers to data sets that are too large or complex to be dealt with by traditional data processes. Imagine, 30 years later, just how much ‘bigger’ data really is. Large data sets from IoT devices or automation need to be processed and analysed to derive value or to make data-driven decisions.
One area often overlooked as an opportunity for big data analysis is the communications network. Communications Service Providers (CSPs) have utilised big data analysis of their networks with regard to customers and their billing records, but rarely have enterprises utilised the massive amount of data generated by the networks within their own company.
Data is a strategic asset for businesses and Oracle recognises the immense value that data holds in making business decisions, driving corporate strategy, and unlocking new opportunities for enterprises. With a comprehensive network view, Oracle Communications adds to the Big Data portfolio with advanced analytics into a company’s infrastructure, traffic behavior, and end customer communications.
For example, gathering a complete view of enterprise traffic, a company may perform employee call analysis to reveal a virtual map of internal collaboration and reliance on external partners and vendors. Call center data may reveal overall or individual performance metrics, as well as customer satisfaction, handle time, and service-level agreement performance.
Through advanced data analytics, enterprises can identify customer trends and interaction opportunities, uncover historical networking trends, or predictive call patterns, spot potential security breaches, and enable more proactive security measures.
Applying big data analytics to communications
With data sources including behavioral data, demographics, and purchase data, solutions employing predictive analytics and machine learning capabilities can identify patterns. These patterns can then be leveraged to identify a complex issue – particularly at large companies operating large networks, pinpointing a specific problem can pose a unique challenge.
Whether a company is encountering sporadic issues where one location is experiencing poor voice quality, while another is experiencing frequent dropped calls isolating and finding the problem is a daunting task – both expensive and time consuming. However, by leveraging the power of data and analytics, the enterprise can employ a solution to review the data and patterns to uncover the problem.
Another way that analytics can support enterprises is through improved network and call center efficacy. Using data and analytics, organisations can determine how well certain call campaigns are performing, how well agents are performing, and even predict trends.
Securing the voice network
A recent report by Metrigy identified voice as the most widely used channel, with 73.1% of all interactions either using voice initially or as an escalation from another channel. As such a critical channel for businesses, enterprises are employing communications analytics tools to enable more proactive security measures and relieve contact center agents from the burden of authentication.
A recent study by CrowdStrike Intelligence identified an increase in social engineering using human interaction, such as voice phishing (vishing), to successfully download malware or circumvent multifactor authentication, proving direct interaction with victims remains a valuable asset to cybercrime operations.
Contact centers continue to be frequent targets for this style of attack, and the challenge of screening often falls to the individual agent. The FTC reports that 20% of the fraud reports it received in 2022 had a phone call as the contact method, with another 22% from contact via text message.
American consumers reported a total of $798 million lost to fraud via phone call, with a median loss of $1,400. With the phone (inclusive of vishing and smishing) the most common attack vector used by scammers when trying to reach a target, phone based attacks are typically more successful than other attack vectors such as phishing – using email to reach a target.
Caller validation
By reviewing metadata from incoming and outbound calls, including information of where the call originated, the time, and the destination, analytics solutions such as Oracle Communications Security Shield, can identify if a pattern is reminiscent of a known fraud scheme or unusual comparative to the device or user’s normal activities. These real-time predictive analytics enable enterprises to be proactive in their security measures, acting well before an attack happens, rather than reacting after the event.
Traffic validation
The business analytics information accessible in solutions such as Oracle Communications Security Shield provides actionable insights and an intuitive view into network traffic and threats. Users benefit from being able to detect anomalies, investigate, and determine remedies with new clarity.
Phone number reputation monitoring
Analytics solutions will soon be able to deliver value for outbound calls, as well. A frequent challenge of enterprises is ensuring their outbound calls are not labeled as ‘spam’ or ‘unknown’ when attempting to reach their customers. According to recent research, 88% of customers will not answer an unknown caller, making it challenging for enterprises to connect with their customers.
With patterns akin to spam calling (one number reaching out to many numbers, average call duration, and low number of repeated calls to the same number) outbound call centers are frequently mislabeled as spam. Analytics solutions can evaluate the outbound calls and monitor and detect if it’s been tagged as spam, provide mitigation steps, and recommendations to the enterprise to ensure calls moving forward are branded to display the appropriate information on the recipient’s device.
Empowering the network through big data analytics
Prior to cloud computing, employing this level of analytics was cost prohibitive for most companies. The analytics derived from big data were not worth the cost of the added hardware and software required to collect and process the data. With the high performance of the cloud, ample storage, and the SaaS business model, any company regardless of size may tap into the power of analytics. Cloud-based analytics empower enterprises to enhance network infrastructure, enhance network and call center efficacy, improve the customer experience, and restore or build trust in phone calls and phone numbers.
About Douglas Tait
As Director of Product Marketing, Mr Tait is driving the market strategy and tactics for Security, Intelligent Edge, Core Networks, and Hybrid Cloud in Communications. Prior to Oracle, Mr Tait was the director for Global Telecom Markets at BEA and founded the JAIN initiative defining Javaâ„¢ technology for communications at Sun. He organised international standards, community, and user group meetings for creating standards and driving the communications market toward standard based interfaces, platforms, and protocols.