Technology
Avoiding Security Complexities
Many years ago, the firewall was everything. Defence-in depth was a concept defined as layered defence with multiple firewalls on the path.
Behind the firewall was a fortress. Organisations designed networks with strong perimeters and demilitarised zones to ensure the crown jewels were well-protected. Attackers had a difficult time trying to break into the firewalls.
On the physical layer, Network Admission Control (NAC) technologies were implemented to prevent intruders from having direct access into the network by preventing them from plugging unauthorised devices into the network. Before a device was admitted, it had to meet a minimum requirement defined by the organisation.
Those years are gone and maybe gone forever. Cloud computing, Bring Your Own Device (BYOD), Artificial Intelligence, Internet of Things (IoT), VPNs and Remote Working Capabilities have dramatically changed the way businesses run.
These technologies have introduced a level of innovation and disruption that were unimaginable only a few years ago. They have resulted in the collapse of the traditional network perimeter, thereby increasing the attack surface for cyber-attacks. Enterprise networks coverage is today being extended beyond our imagination – outside the traditional datacentres to smartphones, cloud platforms, mobile computers and IoT interfaces without geographical boundaries.
The bad guys now have a plethora of interfaces to launch their attacks on; they do not have to breach the network using traditional social engineering tactics physically.
The recent changes in the work environment occasioned by the COVID-19 have further amplified the extension of network boundaries beyond the traditional datacentres. Employees work from home with devices and connections into the enterprise networks that were not originally designed for such. Improvised connections were made to allow functionality because the pandemic came without announcement.
The danger this poses is that some of these end devices were not originally designed with security in mind. Even if security was a consideration, not so much for enterprise data protection. These devices are most of the time not hardened, and their owners may not understand the effects on the overall organisational security posture.
A handful of these devices are installed with default passwords, and most times, these passwords are not changed during or after installation.
So, it is easy to guess the password by manual methods or using advanced dictionary or brute force attack methods. Another risk posed by these endpoints is the lack of security updates and patches. Because they are sometimes not seen to be part of the enterprise network, they are not included in the patch management programme, and their presence introduces high-level vulnerabilities within the enterprise network.
It then becomes easier to utilise malware that could tunnel through the firewall to breach the enterprise network, instead of spending months and years trying to break into the firewall or layers of firewalls.
In recent years, large-scale attacks have been launched using malware by exploiting known vulnerabilities and security gaps on endpoints.
For example, the WannaCry, Petya and another variant of Petya, the NotPetya were employed to launch attacks on enterprise networks through vulnerable endpoints. Another danger with this trend is potential data leakage because these devices are used to either temporarily or permanently store organisational data.
There is also concern about device loss. If these devices are lost, there is a risk of exposing the organisation’s data to unauthorised entities, and that could both result in financial and reputational damage.
These dangers are also expanded by the impact of the COVID 19 pandemic, where organisations made ad hoc improvisions to support businesses while employees work from home.
As commerce resumes, organisations are beginning to discover some capabilities to support their businesses remotely, and they are also rethinking their business continuity strategies.
For some businesses, this is not just a temporal shift, but a change which has permanently altered the operational procedures of the organisation.
Legacy cybersecurity strategies, techniques and investments will not be enough to mitigate the rising cybersecurity concerns introduced by this new way of working. Protection has gone beyond throwing in uncoordinated technical solutions and efforts.
Organisations need to rethink a new approach for the protection of their assets within the ever-growing complexity both to remain afloat and also to derive commensurate Returns On Security Investments (ROSI). A well-crafted strategy will ensure that cybersecurity efforts are coordinated within the enterprise, without duplication of efforts and resources, which will, in turn, drive down the cost of implementing cybersecurity initiatives.
To improve the security posture, organisations must do the following:
Continuously monitor the devices, applications, and processes running on the network.
Automate security monitoring and mitigation.
Implement systems that are capable of automatic detection, isolation and containment of threats within the network.
Ensure that monitoring covers event data, session data, and historical data on endpoint usages, such as past processes, network connections, and other information.
Another measure organisations should take is reducing complexities. The extension of the network boundaries has not stopped organisations from using existing network solutions to protect the enterprise network.
However, in a bid to ensure the protection of the on-premise infrastructure and the ones beyond the organisational traditional network boundaries, organisations combine existing technologies with new solutions and the resultant effect is an increase in complexity.
To effectively manage security, organisations should put measures in place to ensure a reduction in complexity and enhancing visibility. This can be achieved by unifying all efforts and technologies for managing both on-premise and off-premise infrastructure in a single platform. Beyond technical controls, organisations should develop procedures, standards, and policies for acceptable use of organisational resources.
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The rules have changed. How companies actually know their customers — really know them — looks almost nothing like it did ten years ago. Old-school research methods are drowning. Too slow, too narrow, too dependent on humans manually stitching together datasets that have already gone cold. Markets shift in days now, not quarters. And the cost of a slow read on consumer behavior keeps climbing. This isn’t just a tooling upgrade. The underlying logic of how businesses decide what to build, what to charge, and who to reach has been gutted and rebuilt from scratch. Staying reactive isn’t a strategy anymore. It’s a liability.
1. Real-Time Data Processing and Pattern Recognition
Consumer intelligence used to run on stale numbers. Analysts dug into data weeks — sometimes months — after whatever actually happened. Modern AI kills that lag. Entirely. These systems chew through enormous volumes of behavioral data on the fly, surfacing patterns that human teams couldn’t find in the same timeframe with ten times the headcount. Machine learning algorithms can process millions of customer interactions, transactions, and behavioral signals simultaneously — pulling clean signal out of what would otherwise be undifferentiated noise. A retailer can track sentiment across social media, reviews, and support tickets right now, catching a brewing problem or an emerging trend in hours rather than weeks. Inventory shifts, pricing moves, message pivots — all of it happens before a trend fully crystallizes. That’s a different game entirely.
2. Predictive Analytics and Consumer Behavior Forecasting
Here’s what actually changed: AI stops consumer intelligence from being a backward-looking exercise. Instead of cataloguing what customers already did, companies can now forecast what they’re likely to do next — and with striking accuracy. Advanced ML models thread together historical patterns and live behavioral signals to predict churn, flag high-value prospects, and project demand across entire product lines. A telecom company can spot which customers are quietly drifting toward a competitor before they ever make the switch — and intervene first. That’s not a marginal improvement. It’s a fundamentally different posture. Resources flow toward the segments that actually matter, rather than spreading thin across the whole base and hoping something sticks.
3. Personalization at Scale
Consumers expect personalized experiences. Full stop. Meeting that expectation at scale — for millions of people at once — is simply beyond what human analysts and traditional segmentation can deliver. Machine learning models read individual purchase histories, browsing patterns, preferences, and demographic signals to build dynamic profiles that drive product recommendations, custom messaging, and tailored interfaces. When building and refining these individualized profiles, marketers who need to enrich their first-party data with verified behavioral signals rely on audience data providers to ensure their models are trained on accurate, high-quality consumer information. An e-commerce platform can serve each visitor a genuinely different experience — different layouts, different offers, different content — all built around that visitor’s unique fingerprint. Conversion lifts. Lifetime value climbs. People respond when recommendations actually fit their lives, not just the average of everyone else’s.
4. Sentiment Analysis and Brand Perception Monitoring
Knowing how consumers feel about a brand means wading through unstructured mess. Reviews, comment threads, support tickets, social posts, video captions — none of it parses cleanly by hand at any useful speed. Natural language processing handles it. NLP systems automatically scan text-based content across digital channels, classifying sentiment as positive, negative, or neutral while bucketing feedback by topic, product feature, or customer segment. An automaker can track online conversations about a specific reliability concern and catch it before it snowballs into a full-blown reputation crisis. No waiting for quarterly surveys. No lag. Brand perception monitoring becomes continuous — and decisions about product fixes, messaging shifts, or service interventions get grounded in real signal rather than gut instinct.
5. Competitive Intelligence and Market Positioning Analysis
Competitive intelligence used to mean manual tracking, sprawling spreadsheets, and perpetually incomplete pictures. AI automates the entire collection-and-analysis loop. ML models watch competitor pricing moves, product launches, promotions, and messaging shifts across digital channels — then stack that data against a company’s own position. Gaps surface. Threats register earlier. A financial services firm can monitor exactly which themes competitors are pushing on social media and which ones are actually generating engagement — then sharpen their own positioning accordingly. Real-time visibility into competitive dynamics means strategic calls about where to invest, which markets to enter, and how to stand apart in crowded categories aren’t made blind anymore.
Conclusion
What AI has done to consumer intelligence isn’t incremental. It’s structural. Real-time processing of massive datasets. Forecasting future behavior instead of autopsying the past. Personalization that reaches millions, not hundreds. Continuous sentiment monitoring. Automated competitive tracking. None of these were realistic options a decade ago. They are now. Companies that wire these capabilities into their core operations make faster, sharper decisions — ones that show up directly in revenue, satisfaction scores, and market share. Those that don’t will keep falling further behind. And the gap between organizations that wield these tools well and those still grinding through traditional approaches? It’s not closing. It’s widening every quarter.
By Adedapo Adesanya
Redtech, a financial technology company backed by Mr Tony Elumelu’s Heirs Holdings, has intensified its pan-African expansion strategy as it extends its payment infrastructure beyond Nigeria and leverages recent global recognition to strengthen its footprint across the continent.
The fintech firm was named in the payments category of the World’s Top Fintech Companies 2026 ranking by CNBC and Statista. It is among the only 11 African companies recognised in this year’s edition.
Developed by CNBC and Statista, the annual ranking identifies 500 leading fintech companies from a pool of more than 3,500 businesses worldwide. Serving as a data-driven benchmark, the ranking highlights companies shaping the future of financial services through technology, innovation and scalable digital solutions.
The company said it is accelerating its push into new African markets with the rollout of digital banking and payment solutions.
As part of this expansion, the UBA RedPay mobile application is now operational in Benin, Burkina Faso, Côte d’Ivoire, Mali and Senegal, marking the company’s first significant digital banking presence outside Nigeria.
It has also introduced virtual account services in Ghana through a partnership with UBA, broadening its payment collection capabilities in West Africa.
The company said the move aligns with its long-term ambition to build a unified payment infrastructure that enables businesses to collect, process, reconcile, disburse and manage funds seamlessly across African markets.
Commenting on the company’s growth strategy, the chief executive of Redtech, Mr Emmanuel Ojo, said Africa’s increasingly interconnected digital economy requires payment infrastructure that can support cross-border commerce.
“Recognition from CNBC and Statista reflects the growing relevance of African Fintech companies on the global stage and validates our ambition to build Redtech into Africa’s payment infrastructure company.
“We are building the technology that enables businesses of every size to collect, pay and manage money seamlessly across channels and markets. As African commerce becomes increasingly digitally connected across multiple market borders, businesses need payment infrastructure that is reliable, secure, interoperable and designed for the realities of operating across the continent.
“Our goal is to help power that growth by making payments simpler and more connected for African businesses, while building solutions that reflect global standards.”
Redtech continues to scale its operations, with available numbers showing that the fintech has processed approximately N45.84 trillion ($33.21 billion) in transaction value through its flagship RedPay platform and deployed more than 55,000 point-of-sale terminals serving merchants across sectors including banking, fintech, retail, hospitality, energy and utilities.
Looking ahead, the company said it plans to expand its collections and financial infrastructure capabilities across all 54 African countries, enabling businesses and financial institutions to manage transactions across multiple markets through a single technology platform.
Technology
CREDICORP Expands Consumer Credit for Locally-assembled Digital Devices With C.L.I.C.K.D.
By Modupe Gbadeyanka
To expand affordable consumer credit for locally assembled laptops and devices for digital workers, the Nigerian Consumer Credit Corporation (CREDICORP) has launched the C.L.I.C.K.D (Credit for Laptops, Internet, Connectivity and Knowledge Digital Devices) scheme.
This initiative is in partnership with the federal government through the Three Million Technical Talent (3MTT) Programme.
It was designed to democratise access to consumer credit, expand economic opportunity and empower millions of Nigerians to improve their quality of life through responsible borrowing.
At the unveiling of the scheme on Tuesday in Abuja at the Afreximbank African Trade Centre (AATC), the chief executive of CREDICORP, Mr Uzoma Nwagba, said the initiative focuses on fellows’ training through the Learn2Earn platform, many of whom are acquiring in-demand digital skills without access to the devices needed to complete their training and transition into employment or entrepreneurship.
Delivered in collaboration with Fidelity Bank as credit administration partner and NASENI and Imose Technologies as device manufacturers, it will provide 1,000 locally assembled laptops to eligible fellows across Nigeria, with 77 beneficiaries in Abuja receiving their devices at the launch ceremony as the first phase of a nationwide rollout.
Assembling the devices in Nigeria shows how consumer credit can expand digital inclusion, strengthen local manufacturing and deepen the country’s technology ecosystem.
“C.L.I.C.K.D. transforms digital devices from a barrier into an opportunity. By embedding affordable consumer credit into a national talent programme like 3MTT, starting with locally assembled laptops, we are giving qualifying Nigerians a responsible pathway to the tools they need to learn, work and earn, while advancing the federal government’s vision for industrial development and job creation on both sides,” Mr Nwagba averred.
Also commenting, the Minister of Communications, Innovation and Digital Economy, Mr Bosun Tijani, said, “Nigeria’s digital economy can only thrive when our people have both the skills and the tools to succeed.
“Through C.L.I.C.K.D., we are helping qualifying Nigerians participate more fully in the opportunities created by the 3MTT initiative while strengthening local manufacturing through the use of locally assembled devices.”
C.L.I.C.K.D. is CREDICORP’s flagship device financing initiative, open to working Nigerians nationwide, with the 3MTT programme as launch partner for this first phase. Interested Nigerians can register at www.credicorp.ng/clickd.
