Providing Financial Services to the Average Person Through the AI Revolution - George…

revolution The 'fintech' revolution has given rise to a transformation from branch manager to robo-adviser. Almost every individual has, in some way or another, been touched by 'Fintech'. In my eyes, the main impetus has always been: "How can technology be used to make financial services available to the general public?" The move away from traditional personal banking in high street branches, coupled with the rise of online solutions, has spawned fintechs to satisfy customers' needs which were once met by bank managers. In spite of substantial progress made over the past ten years, it is still not easy to give consumers more power. Although neo banks, budgeting apps, and robo-advisers have increased convenience, many consumers still find it hard to understand the financial world. A great number of goods and services are restricted to solving just one customer difficulty. Such as "What is the simplest way for me to put my money into investments?" as well as "How can I prevent being charged exorbitant fees while paying for items overseas?". Consequently, the discerning customer is likely to hire a dozen different suppliers to satisfy their requirements for routine banking, budgeting, investments, credit, travel and so on. Nevertheless, even the most dedicated of shoppers still need to do the hard work of finding out which product, choice or action is correct. One could argue that the past decade has been a golden age for technological advancements in financial services: Open Banking's emergence, the shift to cloud-based services, the influx of challenger banks, and the necessity for modern core systems for banks. Are financial services truly beneficial for the typical person? No, not yet. But the necessary foundation has been established to achieve a total revolution: Artificial Intelligence. Ed and I had a vision of crafting a comprehensive and user-friendly view of the consumer in order to provide personalised value. From the beginning of creating Bud, we knew that having all your finances together in a single platform, coupled with the ability to link external financial services via API, would create the potential to develop a system that would understand your needs and provide the right financial product at the right time. This voyage ended up being incredibly labour-intensive with an abundance of technical barriers to conquer. We realised, however, that data quality would be the foundation of everything we did. Accurately enriching transaction data in order to secure a definite understanding of the customer was essential to furnishing any tailored value to either a company or consumer. Our interest in devising the most exceptional enrichment models began that way. What we were unable to do, and that was never a possibility, was to extract and translate the data universally and combine it into a new system effortlessly. But, fortunately, the modern age of AI delivers the solution. Present day technology can comprehend innumerable queries regarding finances; whether yours, your business's or consumers’ and supplies the data in an easy-to-grasp manner which can then be channelled to another area. It will form a sphere of financial services personalised to the highest degree. The potential of AI to revolutionize the financial sector has been largely untapped, given that most of the announcements from banks over the past year have largely been for operational use cases. Such use cases may facilitate a more efficient business operations, but they do not fully exploit what AI has to offer. To truly transform the financial industry, AI must be used with the proper financial data: transactions, investments, loans etc. It is important to approach this technology with caution, but by no means should it be avoided. Are hallucinations a concern? Is explainability an issue? Is data integrity a priority? Let's combine the first two tasks. Financial data can be quite chaotic and, without any type of processing, can be very difficult for the average person to understand, not to mention a computer. Attempting to utilize a general LLM (large language model) over billions of raw transactions to gain insight into your customer base is a costly, inefficient path to follow. Generic LLMs are not sufficient for managing, comprehending, and enriching a tremendous number of transactions. It is essential that the correct instruments are utilised for the right jobs. Streamlined financial models can effectively process an unlimited amount of transactions and compile precise information that a generic LLM can interpret and play back in all circumstances with security. The generic LLM does the ‘discover’ segment rather than the ‘figuring’ part of the task. By limiting the model to certain activities and obliging it to give back the data, it is deciphering the observations it gives, implying that you can eliminate confusion and offer unwavering explainability. I am providing a sample for you to consider. Here is an instance I am offering for you to think about. Output: How many of the individuals that I serve are gamblers? There are 245,769 customers in your user base that have been spending a consistent percentage (at least 5%) of their income on gambling over the previous six months. Would you like to reach out to this group of customers? Data accuracy is of utmost importance. The savings of time, money, and resources when one can administer queries with certainty are incalculable compared to the current state of businesses. Yet, such ease of analysis can only be achieved with trustworthy information; it may sound simple enough, but handling this type of query without prior processing of the raw data will be expensive, untrustworthy, and inconsistent. When the data is in a form that can be easily read and understood, with relevant conclusions ready for immediate interpretation, further queries can be joined together producing an abundance of possibilities. Maintaining data integrity should be top of mind for everyone working with financial data. Implementing an enterprise system such as Google's PaLM 2 allows for a secure enclosed environment to process and authorize the movement of data; this is more advantageous than a GPT4, as it facilitates analytics, interpretation of findings, and LLM in a single instance. A glimpse of the future… What does the perfect financial services landscape look like? I am sure that my opinion will be obsolete soon, yet, for now: As you are on the way to the airport, your financial app sends you a notification. Taking into consideration your recent flight purchases plus your usual patterns of expenditure, it is sure that you are heading abroad for the next week. The app suggests transferring £1,000 to a travel card as a means of covering your outgoings while you are away. This transfer might put some existing commitments in jeopardy due to the increase in utility bills recently. To counter this, it is suggested to move £200 from your Instant Saver Account into your Current Account. To avoid a drastic reduction in your savings, you can arrange for a Round-up Service to be set up, so that your Savings Account can gradually return to its original level within the next few months. It has looked over the details of your credit card, and has let you know that you have access to most airport lounges in the region. It inquires if you would like it to reserve a space in the lounge at your Uber trip's end destination. Everything that needs to be done can be accomplished with one affirmative answer. Your money can work to your advantage, not the other way around. What part does Bud play in this? The underlying layer of technology supplies both transaction and analytic models, which are founded on exacting data. Thanks to Bud's fintech, neobank and other banking customers, this technology is available via a license, resulting in data analytics taking just seconds as opposed to weeks to achieve. This enables their patrons to enjoy the outcomes. An article originally appearing at https://www.siliconroundabout.org.uk has been included in this resource.

Source: https://siliconroundabout.medium.com/how-the-ai-revolution-gives-financial-services-the-chance-to-work-for-the-average-person-george-29cf13bcd207?source=rss------fintech-5