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Artificial Intelligence

How AI Is Helping Fintechs Provide Intelligent And Better Financial Services

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AI fintech services

We live in an era of data. In today’s world, data is the new gold. The quality of services now significantly depends on how much insight can be extracted from data to help in the creation of the services. For fintech organizations, building services that harness the power of data and artificial intelligence has now become necessary to ensure that the services are tailored to meet the needs of customers. Artificial intelligence is now being used in various ways to help fintech companies provide intelligent and improved services. Some of the major areas of AI application in fintech are discussed in this article.

Risk Assessment

From insurance companies to banks and other fintech institutions, assessing credit worthiness and estimating the level of risk associated with every transaction has become very crucial. Now, many fintech companies employ the use of AI in determining the credit profiles of clients which helps to minimize financial losses when customers fail to repay loans or meet other financial commitments. 

Predicting and preventing fraudulent transactions is another challenge that fintechs are using AI to solve. Using machine learning algorithms, fintech organizations are able to build more accurate fraud detection mechanisms to curb the activities of scammers. The advantage of using machine learning for fraud detection in financial systems is that the machine learning model can learn from the financial data by itself. Thus, it is able to uncover hidden patterns and make a more robust prediction compared to traditional fraud detection algorithms. AI-based fraud detection algorithms can also be used to verify insurance claims and flag fraudulent ones. 

Churn Prediction

Customer churn is an important Key Performance Index (KPI) for any organisation. Preventing customer churn is aimpoaaaustomers and improve customer engagement. Many fintechs across the world now use AI to increase customer retention by understanding customer behaviour and making data-driven decisions to retain the audience of customers.

Intelligent Customer Service

Customer service is an aspect of fintech that has been significantly transformed by AI. The use of AI in this area has drastically reduced the need for human customer care representatives and the cost associated with employing these representatives. With AI, more customers can be attended to more efficiently via chatbots, virtual assistants etc. 

Chatbots are, particularly, one of the most common uses of AI in fintech customer service. Chatbots are sophisticated conversational AI applications that can engage with customers, address complaints and basically fill in the gap of a human employee. Chatbots have now become faster and easier means for customers to fix issues they have while using fintech services.

The Future of Fintech With AI

The use of AI in financial technology extends beyond risk assessment, churn prediction and intelligent customer service. Areas like payment processing and sentiment analysis are also being transformed by AI. Organizations like MasterCard and Visa have been able to improve the quality of their services by leveraging AI to achieve this. Personalized banking and financial services will define the future of financial technology. Better experiences will be developed for each customer in a unique and personalized manner. This may be impossible without AI. The future of fintech is geared towards smarter and more intelligent services, with AI steering the wheel to this future.

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Kehinde is a driven human who is passionate about leveraging technology to transform the future of humanity and the way we all live. His interest lies in constantly getting valuable information and being part of a mission that seeks to create a transformative radical shift.

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Artificial Intelligence

The Metaverse in Bits and Pieces

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The metaverse is coming. Or maybe it is already here. But interest in the concept has soared higher than ever before after Facebook CEO, Mark Zuckerberg announced that his newly renamed company, Meta Systems Inc., would take up the task of building a metaverse within the next few years. The metaverse, which started out as a fictional concept in the 1992 book “Snow Crash” by Neal Stephenson, is a virtual reality built on top of the real one in which people live, interact and do what people do. Meta Inc. hopes to bring this vision to life by “rendering the internet” in 3d.

The metaverse is going to be a virtual world but a much more immersive one, more so than our current digital worlds. The aim is to create a reality that would otherwise be indistinguishable from the real one in many aspects while also outdoing real life in others. The possibilities are endless. However, the crux of the matter remains that if a metaverse is built in the way currently envisioned by Meta Inc. and other tech visionaries, then the people living in those virtual worlds obviously would interact in ways already done in real life and more.

Living out life, working, playing and socializing from a 3d digital space inevitably means economics will come to play in some way. The question of how technologies like the blockchain and cryptocurrencies would fit into this digital future remains fuzzy but many are optimistic that cryptocurrencies would be the currencies of the metaverse. And they certainly could. The most touted features of blockchain based cryptocurrencies such as immutability and security are one of the biggest talking points for why cryptocurrencies should take center stage in the finances of any metaverse and should the metaverse use cryptocurrencies for its transactions and exchange of value, it could further boost their mainstream adoption.

NFT’s are also getting a buzz from the metaverse concept. While NFT’s have had their fair share of criticism, amongst which are that NFT’s are not environmentally friendly or that purchasing NFT’s is akin to buying air, all that could change in the metaverse. The issue seems to have been that an NFT token was not much use in the real world, however, this would or could be radically different in a virtual one. NFT’s provide a solid opportunity for metaverse users to own virtual property which would be NFTs of real estate to artwork or memes, all real-world items or commodities carried over to the virtual one.

What, if anything, would be the fate of fiat currencies in the metaverse? While conversation is going strong about the role of cryptocurrencies and NFTs in these virtual worlds, it is important to note that the vast majority of the world’s money exists digitally. Besides, seeing as cryptocurrency use is still far from mainstream in many ways, metaverse users ultimately must reconcile their virtual lives with their real ones. Trade and commerce in the metaverse may overlap with real life just as online shopping does and the question is how fiat currencies and cryptocurrencies would be used within those spaces.

The metaverse may already be here, in bits and pieces. Nevertheless, if it succeeds in the ways laid down by its proponents, it would fundamentally change how people live, work and play.

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Artificial Intelligence

This New AI Can Tell The Kind Of Faces You Find Attractive

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AI researchers are constantly coming up with ways to make the technology serve us better. However, while these services are impressive they can be a tad creepy. A time when social media will be able to like pictures on our behalf, based on how our brain reacts to the picture sounds quite uncomfortable. 

Although Instagram isn’t working on an algorithm that tracks brain waves, researchers from the University of Helsinki and Copenhagen University are. This AI matchmaker can tell when you find someone attractive. It creates a database of this information and knows the kind of faces you find attractive or in more lucid terms, “your type”

Here’s how it works

According to Digital Trends, the researchers used a generative adversarial neural network. This network has over 200,000 pictures of celebrities. The AI then recreates original faces based on that database. A group of participants kitted with electroencephalography (EEG) caps were shown these images. Concentrating on which picture they found attractive, the cap read their brain waves to know how they felt about the picture. 

Michiel Spapé, one of the researchers, said, “By capturing the brain waves that occurred just after seeing a face, we estimated whether a face was seen as attractive or not. This information was then used to drive a search within the neural network model — a 512-dimensional ‘face-space’ — and triangulate a point that would match an individual participant’s point of attractivity.”

The AI uses machine learning to connect the dots as per what we are attracted to. Whatever pictures cause a spike in brain waves is stored, the machine analyzes them and looks for the faintest detail they have in common. Afterwards, it comes up with facial features we might not know we are attracted to. 

So, how do you measure attraction?

The researchers have found out that roughly 300 milliseconds after a participant sees an attractive image, the brain lights up. Well, a living brain lights up every time but this particular “lighting up” gives off a specific signal identified as a P300 wave. A P300 wave in itself, does not mean you’re attracted to something. It simply means you have spotted what you have been asked to look out for. The participants have been asked to look out for images they find attractive, as such, any discovery of a P300 wave at that time, means that they find the picture attractive. 

Great algorithm for dating apps?

An algorithm that can tell which facial features you find attractive will be great for dating apps. It will recommend to users, the kind of faces they will probably find attractive. 

However, one can argue that the laws of attraction aren’t that simple. Facial features are just a facet of what people find attractive. Nevertheless, there could be an integration of the detection of all the possible attraction facets. This would go a long way in cementing AI’s position as a major partaker in human lives- or love lives, as the case may be.

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Artificial Intelligence

Using AI To Grow Avocados And Improve Agricultural Productivity In South Africa

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Globally, South Africa maintains a spot as one of the major producers of avocado. In 2019, the nation secured approximately 1.1% international market share in the multi-billion dollar avocado export market. However, its annual production volume of between 80,000 and 120,000 tonnes is still many miles behind the annual production volume of 1.5 million tonnes by top avocado producer, Mexico. However, this figure could be significantly increased with precision agriculture, thereby, providing ample opportunity to boost the nation’s overall revenue from avocado export.

The right amount of irrigation is extremely critical for South African avocados to attain maximum growth. For a long time now, South African farmers have relied on traditional irrigation strategies that are largely hinged on their intuition and experience, which has hindered the attainment of the maximum productivity that could be reached in avocado production. Cracking the issue of irrigation could unlock an astonishing increase in South Africa’s annual avocado production volume.

Now, Israeli company, SupPlant, is using technology, particularly AI, to provide farmers with smarter and more efficient ways to improve agricultural productivity. They have been able to achieve this by developing an AI model that employs predictive algorithms to provide customized irrigation recommendations based on analyzing about 100 million data points. Their solution is now being used by South African farmers to grow avocados as the solution is particularly useful for South Africa’s avocado irrigation challenge.

To gather data, SupPlant’s solution involves the use of sensors. These sensors are located in 5 different parts of the plant (avocado, deep soil, shallow soil, leaf, stem/trunk). The sensors monitor plant stress, the exact water content in the soil, health data of the plant, the growth patterns of the plant and the fruit. Climatic data and data on the growth patterns of the plant are also monitored by the sensors. The combination of the data is uploaded to a cloud-based algorithm, at 30-minute intervals, which then makes predictions based on the input data from the sensors to provide farmers with irrigation recommendations.

However, the solution above does not solve all of the challenges that South African farmers face in avocado production. Another critical challenge for the farmers is associated with the weather. To overcome this hurdle for South African farmers, SupPlant integrates the use of top weather intelligence platform, ClimaCell, to monitor the weather in a particular plot of land. Today, with the use of SupPlant’s mobile app, South African farmers can monitor their farm plots and control irrigation on any plot from anywhere. The mobile app provides graphical information on historical and future irrigation plans, present and forecasted climatic data customized for each farm plot, growth patterns of the avocado plant, agronomic insights and recommendations for irrigation.

If, for instance, plant stress begins to increase, farmers will immediately get altered via the mobile app and receive data-driven amplified irrigation recommendations to prevent severe damages to the plant. With SupPlant’s solution in the hands of farmers, farmers will no longer need to engage intuitive and traditional irrigation and farming approaches.

In such a time as now, when the demand to produce more in smarter and more efficient ways is seemingly high, SupPlant’s solution evidently lies beyond South Africa’s avocado industry, as it also extends to other areas where precision agriculture could be harnessed to unlock massive agricultural productivity. With a technology like AI, the journey to smarter and more intelligent farming is just evolving.



















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