Nigerian fintech startup, Kredete, has officially launched its lending platform to deepen accessibility to formal credit, financial education, and innovative financial solutions. The launch event, which took place on the 16th of April 2023, at the Civic Centre, Victoria Island, hosted tech specialists and entrepreneurs, who convened to discuss the future of lending in Africa and Kredete's commitment to bridging the significant credit gap and financial exclusion faced by Nigerians who lack access to formal credit through traditional means. Kredete aims to revolutionize the sphere of lending in Nigeria and beyond by leveraging AI-driven technology and strategic partnerships with financial institutions to create a complete lending infrastructure that enables lenders to be more efficient and cost-effective while empowering users to access credit products suited to their needs. With AI, the pre-approval odds for users enhance by providing tailored loan options based on their credit history and financial profile, while for lenders, it becomes easier to assess risks, reduce non-performing loans, and make informed lending decisions. Kredete is also passionate about strengthening financial literacy in Nigeria and will achieve this by offering free credit scores, reports, and monitoring tools to help users understand their credit standing and make informed financial decisions.

It's been decades since algorithmic trading transformed Wall Street with its high-frequency trading, and years since the financial services industry began to integrate artificial intelligence in areas such as fraud detection, lending decisions and robo-advisory services. Yet the recent explosion of generative AI tools like ChatGPT – providing human-like text on seemingly any subject and any style so successfully it easily conquers the vaunted Turing Test – has opened the floodgates of possibilities. The advent of such a power language processor like ChatGPT – open source and available for public use – threatens to upend various parts of the financial services industry, spanning beyond areas such as chat bots and robo-advisors to even the workforce needed in something as skilled as coding. As artificial intelligence reaches a crucial tipping point – and AI bias lingers – whether the proper private and public controls are put in place ahead of the technology's dizzying progress becomes even more urgent yet challenging. In a recent Nvidia survey, 78 percent of financial services companies said they use at least one kind of artificial intelligence tool.

As regulators signal a tighter focus on AI and machine learning, banks need to be vigilant about their internal models, as well as the models used by vendors, an expert says. As regulators zero in on how lenders are using artificial intelligence and machine learning in their operations, banks need to make sure they can adequately explain and monitor the models they use -- particularly if they are partnering with a vendor, said Joe Sergienko, managing director at Berkeley Research Group. "Does the bank understand what's going on inside the model, and can they articulate that in a reasonable enough way? That's a tough hill to climb in AI and machine learning models," Sergienko said. The Consumer Financial Protection Bureau (CFPB) issued a warning in May for lenders that use AI or machine learning to underwrite loans or issue credit, telling companies they need to be prepared to explain to customers the specific reasons for denying an application for credit.

According to Grand View Research, the global artificial intelligence (AI) market was worth an estimated $62 billion in 2020 but could grow 40% annually through 2028. If you don't yet have AI stocks in your long-term portfolio, it might be time to start thinking about it. The market's recent sell-off of technology and high-growth companies has created a great buying opportunity for bold and patient investors. Here are three top AI stocks building moats around their algorithms and whose stocks are attractively priced today. Technology can change at a blistering pace, and nobody can know for sure that the winners of today will still hold their crown tomorrow, a year from now, or a decade from now.

Rohit Chopra has seized on nearly every public opportunity as director of the Consumer Financial Protection Bureau to admonish companies about the potential misuse of artificial intelligence in lending decisions. Chopra has said that algorithms can never "be free of bias" and may result in credit determinations that are unfair to consumers. He claims machine learning can be anti-competitive and could lead to "digital redlining" and "robo discrimination." The message for banks and fast-moving fintechs is loud and clear: Enforcement actions related to the use of AI are coming, as is potential guidance tied to what makes alternative data such as utility and rent payments risky when used in marketing, pricing and underwriting products, experts say. "The focus on artificial intelligence and machine learning is explicit," said Stephen Hayes, a partner at Relman Colfax PLLC and a former CFPB senior counsel.

Life sans credit is impossible to imagine. Since the cost of living is rising and income is stagnant, people are relying on borrowing to meet their unexpected expenses. It is hard to set aside money for a rainy day when the cash stream flowing in is very thin. With each passing year, the number of borrowers are rising and therefore hinging on credit score and repaying capacity for the loan approval have become more requisite than ever. Banks and other financial institutions need to consider numerous factors when it comes to signing off on loan.

Artificial Intelligence and its inherent bias may not be as judgmental as previously thought, at least in the case of home loans. It appears the use of algorithms for online mortgage lending can reduce discrimination against certain groups, including minorities, according to a recent study from the National Bureau of Economic Research. This could end up becoming the main tool in closing the racial wealth gap, especially as banks start using AI for lending decisions. The Breakdown You Need to Know: The study found that in person mortgage lenders typically reject minority applicants at a rate 6% higher than those with comparable economic backgrounds. However, when the application was online and involved an algorithm to make the decision, the acceptance and rejection rates were the same.

Machine learning is taking over more previously manual human tasks across all industries and the financial services sector is no exception. In fact, fintech is driving rapid change across the whole sector including invoice finance. The use of incredibly clever computer algorithms which can be programmed to learn as new data comes in is and will undoubtedly result in huge improvements in certain areas of invoice finance provision. Fintech is driving rapid change across the whole sector. However, human experience and judgement will remain a vital part of the process as even the most complex machines have their limitations.

What is driving the demand, how incumbents are responding, and how startups are already tackling explainability 2.0 Explainable AI helps a user understand the machine's decision-making process. Instead of discussing methods of explainable AI (e.g., LIME, SHAP, etc.), below are some dimensions to wrap our heads around the concept. What explainable AI means depends on the user, the object being explained, and the underlying data. It is such a broad and rapidly developing field that when discussing explainable AI in-depth, it is good to have a mental framework of how it fits these dimensions. Most examples in this article are products built for business decision makers analyzing tabular data.

Today, terms like Gen-Z and Millennials are the craze words for most businesses world over as they account for more than 60% of the demography. Unsurprisingly, everyone wants to understand what moves them emotionally, physically and financially. Moreover, their communication and consumption behavior is shifting trends and in many cases, causing trends to emerge. One of these trends is that of the Digital lending marketplace where one can avail any kind of loans at the click of a button! Notwithstanding the higher cost of capital, the enticing factors of this digital lending marketplace are bespoke lending products, convenient & quick disbursement and completely paperless transactions.