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Ultrasonic Proximity Verification BI for Digital Wallets

How Ultrasonic Proximity Verification Improves Business Intelligence for Real-Time Access Patterns in Digital Wallets

By 2026, the number of digital wallet users is projected to soar by 53%, reaching 5.2 billion globally —over 60% of the world’s population. In this burgeoning market, the strategic integration of ultrasonic proximity verification with business intelligence (BI) systems offers a critical advantage. 

But how clean is your user access data? Can you extract what you need from your users’ access patterns to make complex decisions in real-time? 

It’s not an aspirational concept or a brand promise to shareholders in 2030. Advanced technologies from artificial intelligence, machine learning, and data-over-sound proximity verification work harmoniously together and can now be leveraged for analytics toolkits. Real-time data derived from digital wallet interactions can empower companies in the payments ecosystem to stay ahead of competitors and catalyze enhanced user experiences and security measures. 

TLDR; Key Takeaways

  • Secure and immediate data on user access patterns are crucial for real-time decision-making.
  • Analyzing real-time access patterns aids in optimizing wallet features and detecting fraudulent activities.
  • Integrating artificial intelligence tools and ultrasonic proximity tools can improve user experience and security protocols.
  • Monitoring advancements in technology delivery mechanisms and regulations will help CXOs forecast and prepare to implement more modern business intelligence frameworks.

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The Convergence of BI and Security Technologies

Blending business intelligence with security and proximity technologies may signal a new era for digital financial services, but it hasn’t always been this easy. In the last twenty years, digital finance tech stacks have become notoriously bloated in a near-constant gold rush to install the next bigger, better tool, piling one integration point after another onto a legacy framework. 

The number of upstream and downstream connections has contributed to data integrity issues and, in some cases, exposes payment companies with less control over the security of the connection points. The opportunity to simplify, modernize, and secure the business intelligence tech stack is highly compelling and timely.

Real-time insights into access patterns elevate security and play a critical role in shaping strategic decisions. 

Far from just an operational necessity, this convergence is shaping a new landscape in financial technology. Historically, as digital transactions have increased, so has the complexity of threats, making this integration an essential evolution in digital finance security.

Ultrasonic Data Can Deepen Business Intelligence

Ultrasonic technology offers a seamless, robust method for securely transmitting user proximity and transaction data and protecting the integrity of financial payments. This technology uses sound waves to create a secure and immediate verification system without physical contact.

Real-Time Data for Informed Decision Making

This instant data access allows executives to adjust swiftly to threats and opportunities, enhancing their ability to make informed decisions and react quickly to market changes.

For instance, if there is a sudden spike in transactions in a particular region, product leaders can quickly analyze this trend to determine whether it signals a promotional success or a potential security issue. Similarly, decreased transactions might indicate a user interface problem or a need for additional features that enhance user engagement.

Let’s say a mobile payments platform notices an unusual pattern of large transactions occurring at a time when transaction volume is typically low through its digital wallet platform. By analyzing the proximity data, the payments platform can quickly investigate its legitimacy. The platform uses this insight to adjust its fraud detection algorithms to accommodate legitimate transactions, reducing false positives and improving customer satisfaction. 

Better yet, a machine learning tool can automate the adjustment process based on the proximity data detected.

Enhancing User Experience Through BI Insights

Integrating ultrasonic proximity verification and business intelligence data can also enhance user experience. To seize the “micro-moment,” digital wallet applications are evolving from apps to super apps with more intuitive user interfaces that cater to an individual users needs by understanding their behaviors and preferences.

One example to illustrate this is through proximity marketing. When the data shows a significant portion of users frequently make digital payments at specific retailers, a real-time trigger could serve a personalized “loyalty offer” – a reward, discount, etc – for a similar purchase or at the same retailer, which can extend user engagement and the session duration.

The more engagement points and the longer the session, the more insights can be gained from user engagement to further personalize their digital wallet experience. For instance, a fintech startup may rely on BI insights from ultrasonic proximity verification to customize its user interface. However, a pattern may arise of users hesitating before finalizing transactions or abandoning their cart. 

Abandoned carts and other delays in transaction execution may be a sign of confusion on the user’s end or indicative of security concerns. In response, they might redesign their digital wallet interface to include clearer transaction confirmation prompts and add a quick-access feature for viewing transaction histories. This adjustment, informed by direct insights into user interaction patterns, can improve user confidence and speed time to purchase, evidenced by a marked decrease in actions like transaction abandonment, ratings and reviews, and other performance signals.

Ultrasonic Verification: Use Cases for Access Pattern Analysis

This technology provides insights into how digital wallets are accessed, offering a granular view of user behavior and transaction security. As digital wallet user access patterns grow more complex, adopting a structured approach to data discovery is essential to effectively utilize this data without being overwhelmed by its volume and diversity.

This process starts by defining the scope of value, which dictates the selection, procurement, and maintenance of relevant data, ensuring it aligns with specific business goals and complies with regional data privacy and security regulations. Effective discovery in this context requires developing hybrid data models that integrate automated classification with traditional data management techniques to facilitate precise and actionable insights into user behaviors while remaining compliant with data regulations and maintaining data integrity.

Identifying Trends and Anomalies in Wallet Use

Ultrasonic proximity verification provides a wealth of data that allows companies to continuously monitor and analyze trends and potential anomalies in wallet use. For example, a digital wallet provider may notice an unusual increase in transaction volume during non-peak hours. By scrutinizing this data, the provider could determine whether this pattern represents a new user trend, such as night-shift workers adopting the wallet for late-night purchases or if it signals fraudulent activity.

When a mobile payment company detects a series of high-value transactions occurring simultaneously across multiple accounts, immediate action is typically needed to react to the threat that may have already happened. In a more advanced defensive strategy, a company can quickly trace these transactions to a compromised point of sale through real-time data analysis of ultrasonic proximity or transaction data. This prompt detection facilitates the decision-making of payment organizations to freeze the affected accounts, notify affected users, and prevent further fraudulent activities, thereby protecting user funds and maintaining trust in their platform.

Optimizing Wallet Features Based on User Behavior

The data facilitated by ultrasonic proximity verification BI can help companies tailor their digital wallet features more effectively to user behaviors and preferences. For instance, if data shows a high frequency of transactions among young adults in urban areas, digital wallets could be optimized with features like social payment options or integration with urban transit payment systems, enhancing relevance and convenience for this demographic.

Suppose a digital wallet company observes that a significant portion of its users frequently use digital receipts for warranty and returns purposes. In that case, an opportunity may arise to optimize the wallet features. For instance, the company can develop an enhanced digital receipt feature that stores receipts, categorizes them, and sends reminders when warranties are about to expire. This new feature, developed based on direct user behavior insights, can increase engagement time and customer retention, as users find great value in the ease and efficiency it adds to their shopping experiences.

Implementing Ultrasonic Proximity for BI Enhancement

The integration of ultrasonic technology into BI systems involves several considerations that are crucial for successful deployment.

Technical and Operational Considerations

While the actual Implementation process of an ultrasonic proximity verification SDK is simple and can be done in a matter of minutes, technical and operational considerations will be needed to:

  • Determine the data process flows – upstream and downstream impacts and the flexibility to change;
  • Assess compatibility with existing hardware and software platforms;
  • Safeguard data security and maintain user privacy; and
  • Adhere to regulatory standards

Integrating ultrasonic proximity verification alongside AI into a digital payments app presents complex challenges, particularly when addressing the diverse technological infrastructures across global markets. For instance, an international financial services firm may find that their current payment platforms, which utilize NFC, WiFi, or radio technologies, need to be more readily capable of real-time data processing. 

While incompatibility can hinder the seamless integration necessary for leveraging real-time business intelligence, AI and ultrasonic tools don’t have to be replacement tech. 

For example, to mitigate this, the financial services firm could develop a layered technology approach where ultrasonic capabilities are embedded as an additional option rather than a replacement. By doing so, they ensure continuity in markets where NFC and other technologies are too embedded to replace while capitalizing on the advantages of ultrasonic proximity verification and artificial intelligence in environments where it is needed. This approach allows for phased integration, with continuous evaluation and adjustment to meet the dynamic needs of global markets.

Overcoming Challenges in Integration

In the context of integrating ultrasonic proximity verification and AI for business intelligence purposes, internal challenges often stem from the complexity of implementing new technologies that require substantial changes to existing processes and systems.

Implementing focused initiatives for testing, iterations, and scalability is a practical way to tackle these challenges. An agile testing framework of ultrasonic and AI integrations in controlled environments can provide valuable insights into system performance, integration issues, and potential operational impacts before full-scale deployment. 

Early stakeholder engagement is equally important; involving key personnel from IT, operations, and executive leadership can generate alignment and foster a supportive environment for technology adoption. This collaborative approach smooths the integration process while tuning the internal systems to better future-proof the company’s strategic roadmap.

The Future of BI in Digital Wallets with Ultrasonic Technology

Payment facilitators are leading the charge in modernizing and innovating within the digital wallet sector. A recent study conducted jointly by PYMNTS and Carat from Fiserv highlights that payment facilitators, or “PayFacs,” can now manage the entire transaction and merchant experience to make deeper inroads into the digital wallet arena. 

This strategic approach could transform their position in the market. The study, which involved over 300 executives, found that 71% of PayFacs are actively enhancing and broadening their digital wallet functions to secure a substantial competitive advantage in the industry.

The role of ultrasonic proximity verification coupled with artificial intelligence tools within BI frameworks is becoming increasingly indispensable as technology evolves. The ability to innovate business intelligence tools and processes for digital and mobile payment systems hinges on deeper integration with security technologies. 

According to a study by PwC Luxembourg, merely having more data, better analysis, intuitive visuals, and transparent data does not – in itself – generate shareholder value. The real impact on shareholder value depends on the speed and sophistication of operations within the payments industry. Additionally, choosing the data and analytics operating model is crucial in determining a company’s capacity to create new shareholder value.

Predictions for BI and Security Technology Convergence

The future will likely see selective acquisitions of big data firms and a radical disruption of the existing business intelligence model in the digital payments ecosystem. AI and machine learning models can augment this integration, providing more advanced analytical capabilities and predictive security measures. 

Here are two examples of how this could converge:

Predictive Analysis for Fraud
Use AI to analyze the data collected via ultrasonic proximity and transaction verification to shift from a model of reacting to fraudulent activity to one that predicts and prevents fraud before it occurs by identifying patterns that deviate from normal user behaviors.
Personalized Experiences and Proximity Marketing
Use machine learning technology to leverage ultrasonic proximity data sets to roll out new and disruptive services or offers like user personalization or proximity marketing. 
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By understanding the context in which transactions occur—such as time, location, and frequency—AI algorithms can directly offer users personalized spending insights and budgeting advice. This could include identifying frequent spending trends and suggesting budget adjustments, recommending new wallet features that align with the user’s lifestyle, or hyper-personalizing ads and offers from partners.

Internal Organization Prep is Critical for the Next Wave of BI Innovations

Payment industry executives must stay informed and agile on advancements in AI, emerging cybersecurity threats, and evolving global data protection laws. By understanding these elements, companies can better position themselves to take advantage of new opportunities and mitigate potential risks. 

The often followed contemplative approach to decision-making—crawl, walk, run—while practical in other areas of a digital wallet or payments organization, may be too risk-averse to keep up with the pace of business intelligence innovation. An embedded corporate innovation team can be a great place to study, prepare for, and pilot iterative rollouts of digital transformation initiatives.

Prioritize Time to Value Through AI and Ultrasonic BI Solutions

The integration of ultrasonic proximity verification into BI systems addresses current security and operational challenges while setting the stage for future advancements. This strategic approach to the digital transformation of business intelligence to create better business outcomes can have a trickle-down impact on end-user trust and loyalty and accelerate market competitiveness by adapting to and anticipating changes in the digital financial landscape.

From data to analytics, it’s imperative to remember that time to value—from insight discovery through action on insights—must be a top priority to gain the most shareholder value.

When you’re ready to transform your big data into real-time decision-making on steroids, let’s talk.

LISNR’s ultrasonic Radius SDK works seamlessly with artificial intelligence platforms to collect new types of valuable data that AI or ML toolkits use to interpret and generate predictive modeling for the next wave of your BI.