Future-proofing Business with Enhanced Data Intelligence

By Martin Laesch , Chief Technology Officer at Neural Technologies

In our digital age, data is evolving in every aspect of our lives, from business to leisure; so much so that data has become a rich source of value, storing information which is key for mapping the future of our habits and lifestyles.?

In enterprises, the same data is crucial for predicting consumer behaviors and developing dynamic business models which effectively and efficiently meet customer demands as they change. The speed at which data is generated in the business sector today is unprecedented, giving enterprises volumes of valuable data to inform business opportunities and drive its performance. To do so successfully, however, the value of key data must be harnessed and so avoid the risk of falling behind in the market. This is the key driving force behind business growth and gaining a competitive edge in the industry today.

As a result, enterprises constantly face the challenge of managing complex data records to optimize their intelligence. Newly adopted technologies such as Artificial Intelligence (AI) and Machine Learning (ML) have enabled enterprises to extract the value of their data to inform key business decisions and reach their full potential. In a highly competitive market, enterprises must integrate AI and ML technologies to overcome these barriers and drive business growth and success.

Putting the Odds in Your Favor

Less than?30 percent of organizational digital transformations succeed. This is due to a number of factors, including market growth and pace. The hyper-competitive business environment that has been cultivated by the rise in data traffic and value has caused unprecedented pressure on businesses. Right now, organizations are forced to choose between reinventing their business to prioritize data management and processing or falling behind. In failing to keep up with the market disruption, enterprises are also failing to meet the expectations of their customers.

Having to invest significant amounts of money to ensure the fastest turnaround, least amount of downtime, and highest quality, many organizations are apprehensive to spend what is needed, with fears that return on investment (RoI) and revenue will suffer. As a result, they become stuck in traditional, analog business culture, unable to realize their full potential.

Information Filtration

To succeed in digital transformation, organizations must prioritize their data and decide how best to analyze, review and compile the most critical information from different systems across their internal network. Once harmonized, the filtered data must be transmitted to new systems easily, without error or mistranslation, to truly reinvent the business.

By using a full-coverage digital transformation platform, these concerns can be reassured. Automated information governance solutions analyze complex data landscapes to filter the most crucial information based on learned criteria to allow organizations the opportunity to make better-informed decisions. Information governance uses defined roles, processes and policies to manage data assets and ensure their integrity, accuracy and security.?

This strategic approach is paramount in managing data effectively to optimize operations; without this structure, valuable data is made vulnerable by human error, increasing the risk of being lost, leaked or hacked. Not only does this protect the organization from infiltration and maximize the utility of both internal and external data, but this also reassures customers who are trusting these platforms by guaranteeing compliance with protective regulations such as the General Data Protection Regulation (GDPR).

This premise of established policies and rules to create an understanding based on algorithmic methodology lays the foundations for an effective AI and ML ecosystem. Thriving on the rich and expansive amounts of data, information governance reinforces the intelligence of AI/ML, feeding it the information it needs to advance its predictions to empower business decisions with the utmost accuracy.

Rest Assured

By continually updating the predictive model, data filtration, harmonization and the use of ML solutions help to provide deep analytics of extracted raw data. In doing so, ML technology can offer fraud detection, business assurance, and analyzing trends and root causes to steer organizational decision-making in the most beneficial direction. A critical component of ML is producing confidence and reasons explanations to support decision-making; by implementing Unconstrained Anomaly Detection, businesses can confidently predict risks and address any subsequent issues in real time, protecting against fraud and identity theft.

When developed in hybrid with AI designs, like those offered by?Neural Technologies, the risk mitigation and business assurance aspects of the solution excel. By performing predictive analysis for full-coverage Risk and Fraud Management in near real-time, the module’s Model Building algorithm analyses customer and corporate behaviors to build upon its predictive portfolio and better inform the system.?

With a feedback loop ingrained, learning metrics are automatically retained and improved upon to learn over time, future-proofing the system. Such deep learning can be used to prevent issues before they occur both internally and externally, including identity theft, subscription fraud, commercial misuse and platform malfunction, protecting both the operators and the customer.

Neural Technologies' product portfolio offers full-coverage?Digital Transformation solutions, employing system integrity from conception. Interoperable with a range of OEM system interfaces, the solution is affordable and eliminates the need for full-scale network upgrades or replacements. By investing in quality solutions as a base level, any and all subsequent AI and ML technology can perform to its fullest potential, being fed the appropriate information for the best-informed operations.

Getting a Head Start

By capitalizing on the move to digitalization early, organizations can position themselves as market leaders at the forefront of digitally driven services. To unlock their full potential, businesses should hone their focus on data management and information governance as a stable foundation for their digital transformation using the latest technologies in AI and ML.?

By developing internal enterprise networks with digitalization and data ingrained from the ground up, new business models, improved customer service and new insights are attained long-term. This opens up the potential of the business as a whole, offering a more diverse range of revenue-generating avenues which can be developed further as corporate goals evolve further. This future-proofed approach is protective of RoI and revenue growth and will only serve to be more valuable as trends fluctuate, with the AI and ML solutions becoming more informed and precise the longer they are implemented and the more data they harvest.

Digital transformation journeys must be seriously considered and invested in to be successful – without this, the lack of urgency undermines the initiative and technology, and no benefits will be seen. By implementing high-quality, full-coverage solutions that are right for the business, enterprises can excel in their digitalization, maximizing RoI.?

This approach must be considered and prioritized by organizations to remain competitive. The disruptive nature of the current market, the ever-accelerating rate at which technology and data are evolving and the increasing expectations of the customer are all aspects that must be met. Whilst this creates immense pressure, it is clear that failing to do so can be catastrophic. Therefore, businesses should drive their strategies towards the future, utilizing the solutions available and remaining dynamic to keep up with the fast-paced lifestyle of today.