Artificial Intelligence

Integration of Artificial Intelligence and Advanced Analytics


What does Integration of Artificial Intelligence and Advanced Analytics mean in Business?

 

Disruptive technologies like artificial intelligence (AI) and advanced analytics have had a transformational impact on the finance industry. They are also changing the way enterprises interact with their clients and run their organizations. The emergence and rapid growth of these technologies helped companies enhance their processes and operations.

While data analytics refers to drawing insights from raw data, advanced analytics help collate previously untapped data sources, especially the unstructured data and data from the intelligent edge, to garner analytical insights. Meanwhile, artificial intelligence replicates behaviors that are generally associated with human intelligence. These include learning, reasoning, problem-solving, planning, perception, and manipulation. Some latest iterations of AI, like generative AI, can also create creative artwork, music, and more. Though these technologies sound diverse, their synergy would bring tremendous innovation across several industries.  When powered by AI, advanced analytics algorithms can offer additional performance over other analytics techniques.

World Economic Forum states that the COVID-19 crisis provided a chance for advanced analytics and AI-based techniques to augment decision-making among business leaders too.

In a study conducted by Forrester Consulting on behalf of Intel, 98% of respondents believe that analytics is crucial to driving business priorities. Yet, fewer than 40% of workloads are leveraging advanced analytics or artificial intelligence. For instance, according to Deloitte Insights, only 70% of all financial services firms use machine learning to predict cash flow events, fine-tune credit scores, and detect fraud.

Advanced analytics and artificial intelligence are emerging favorites in the finance sector as they help firms authenticate customers, improve customer experience, and reduce the cost of maintaining acceptable levels of fraud risk, particularly in digital channels. As finance firms race inch to disruption, the velocity of fraud attacks and threats also increases. The amalgamation of these technologies helps mitigate such threats before there is any severe damage, thus increasing compliance. This is achieved by assessing risks, identifying potential suspicious activities, preventing fraudulent transactions, and more. Since AI powered analytical algorithms are adept at pattern recognition and processing large quantities of data, it is key to improving fraud detection rates. For customers, they can help authenticate any financial services they may be using and issue alert the customer if something is wrong.

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This fraud detection capability is also helpful for brand marketers to distinguish successful campaigns and avoid wasteful spending. Boston Consulting Group has observed that consumer packaged goods (CPG) companies can boost more than 10% of their revenue growth through enhanced predictive demand forecasting, relevant ­local assortments, personalized consumer services, and experiences, optimized ­marketing and promotion ROI, and faster innovation cycles; all via the said technologies.

While factors like data silos, fear of missing out on the race to digital transformation and agility have influenced companies to rely on data-driven insights, they must leverage advanced analytics and artificial intelligence, to stay relevant in the market. In its September 2017 article, titled “How Big Consumer Companies Can Fight Back,” Boston Consulting Group also mentions that these technologies top industry players can use them to transform their data into valuable insights. In other words, it can augment an enterprise’s ability to execute data-intensive workloads and, at the same time, keep the HPC environment adaptable, responsive, and cost-effective.

However, there are many difficulties faced by companies when adopting them too. As per a research survey by Ericsson IndustryLab, 91% of organizations surveyed reported facing problems in each of three categories of challenges studied, including technology, organizational, and company culture and people. It is true that artificial intelligence and advanced analytics tools allowed navigation and the re-imagining of all aspects of business operations, and the COVID-19 pandemic expedited their adoption. However, despite being arguably the most powerful general-purpose technologies, companies must recognize potential, use cases, and strategize the right action plans to accelerate their artificial intelligence and advanced analytics undertakings.

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