Grassroots cryptocurrencies are a digital means for turning mutual trust into liquidity. Their coins are units of debt that can be issued digitally by anyone -- people, communities, corporations, banks, municipalities and governments -- and traded by anyone. The purpose of grassroots cryptocurrencies is to provide a foundation for a grassroots digital economy. With grassroots cryptocurrencies, local digital economies can emerge without initial capital or external credit (beyond the financing of smartphones), and gradually merge into one global digital economy. In this paper we introduce the principles that underlie grassroots cryptocurrencies; elaborate economic scenarios derived from these principles; specify the Grassroots Cryptocurrencies protocol formally via multiagent transition systems; provide it with an implementation by a grassroots dissemination protocol; and prove the implementation correct, fault-resilient and grassroots.

Artificial intelligence and machine learning have become vital to many aspects of financial services, from powering chatbots to improving fraud detection. But one area where AI has not gained as much traction, particularly with community financial institutions, is in sales and marketing. Its use has been steadily ramping up, though: SouthState Bank and Eglin Federal Credit Union are among those using AI to parse data in ways that have resulted in much greater impact for their marketing efforts. Rather than targeting people based on simple demographics like age or gender, they combine internal data with information available beyond their own databases to surface a much more telling -- read: predictive -- combination of details. The key benefit has been the ability to more accurately identify when customers are ready to buy a particular financial product and deliver the appropriate messaging to them.

Artificial intelligence (AI) and machine learning are no longer a secret weapon reserved for larger banks with deep pockets. Smaller financial institutions – including community banks and credit unions – are also finding opportunities to level the innovation playing field and implementing advanced solutions that can help FIs enhance customer experiences, stay a step ahead of fraudsters, and improve workflows. Read the report to learn more! We care about protecting your data.

Banking and financial services leaders see great opportunity to improve the bottom line thanks to artificial intelligence, particularly in the areas of process automation and fraud detection, according to a recent article for Forbes by AI developer Dmitry Matskevich. A July report from Capgemini's Digital Transformation Institute predicts the financial sector could add $512 billion to their global revenues by 2020, and increase costs savings by 10 to 25 percent, thanks to intelligent automation. "In 2017, financial firms quietly introduced a range of practical machines that think. Some banks added AI surveillance tools to thwart financial crime, while others deployed machine learning for tax planning," PwC reports. "Wealth managers can now offer automated investing advice across multiple channels, and many insurers now use automated underwriting tools in their daily decision-making."

Over the past couple years, the Digital Banking Report has done several research reports on the digital transformation of the banking industry. While the largest financial institutions appear to be keeping pace with consumer expectations, the majority of the industry is falling woefully behind. It doesn't need to be this way. The Digital Banking Report has been researching the financial services industry for more than two decades, tracking industry trends and making predictions about the future of retail banking. Recently, a startling trend has emerged that could have a dramatic impact on the industry worldwide.

On a surface level, community banking and artificial intelligence (AI) can seem like something of a mismatch in concept. Community banking is all about relationship-lending -- forging personal and lasting connections directly with a consumer, while AI -- particularly embodied by chatbots and voice assistants -- focuses primarily on digitally mediating that personal relationship. Tina Giorgio, president and CEO at ICBA Bancard, says that surface perspective misses the bigger AI picture and the scope of what AI can offer to community bankers and their customers across the country. According to Giorgio, AI is a "tremendous opportunity" for community banking. In fact, she says that it could be a game changer for community banks over the next five years. "There is tremendous potential with the advent of AI to help level the playing field in the financial services space," she said.

Artificial intelligence (AI) fintech start-up Clinc is making its chatbot Finie more widely available through a new partnership with Enacomm, writes Julie Muhn at Finovate (Banking Technology's sister company). Through the reseller agreement, Enacomm will distribute Finie to mid-tier banks, community banks, and credit unions. Clinc CEO Jason Mars describes Enacomm as the "right partner" as the company shares Clinc's "vision for modernising the consumer banking experience". "Teaming up with Enacomm will help us to empower a greater number of smaller financial institutions, like community banks and credit unions, with next-generation, voice-controlled AI technology that otherwise would be out of reach," he states. Clinc's Finie AI chatbot leverages machine learning and natural language to engage users in natural, human-like conversations about their finances without requiring them to learn commands or rules.