While not historically associated with technological advances like other industries, the financial sector has come around to artificial intelligence for a variety of reasons. AI can quickly comb through massive amounts of data, making certain tasks that would previously have required extensive human labor. The result is something that any business can embrace – extensive cost savings, projected by Autonomous to be $1 trillion by 2030.
Fraud is extremely costly to banks – HSBC coughed up roughly $1.9 billion in 2012 following allegations of allowing cross-border money laundering from drug cartels, while ING paid $900 million in 2018 after admitting that criminals had used their accounts for similar purposes. AI could have helped detect the kind of behavior that would have been difficult for a human to pick up on in an ever-growing sea of transactions, creating valuable financial savings – not to mention a way to avoid a PR nightmare.
Additionally, AI can minimize false positive fraudulent transactions by automating decision-making about those transactions based on data, growing steadily more perceptive with the more information it analyzes. AI can mitigate human error that would have otherwise adverse effects on business – Amy Zirkle, a global payments expert with the Electronic Transaction Association, touted AI as a chance to be “two steps ahead” regarding security, allowing for “a healthy payments ecosystem, one that is viable, one that is sustainable, one that customers come to with trust and confidence.”
AI can also create the kind of personalized customer experience that engenders long-term loyalty (and increases profit). Its ability to aggregate data across banking systems, then intelligently derive insight from it allows for individually tailored, seamless experiences. Chuck Monroe of Wells Fargo Artificial Intelligence Enterprise Solutions explained to AZBigMedia that AI allows banks “to more efficiently analyze” the masses of data in their possession and “pull key insights, often in real-time, to deliver personalized guidance to customers in the moment, wherever they are.” This means banks can offer personal advice, anticipate customer needs, and “[offer] them something they value, to make their lives easier” – especially with customer service, where AI can ask big picture questions and free employees to handle situations better suited for human-to-human interaction.
By augmenting existing functions and processes with artificial intelligence, banks are becoming smarter and more efficient, making customers happy, and growing profits. Fraud, personalization, and customer support are just a few of the many areas that AI can help banks. The financial sector is learning to love AI, and both business and customer are better for it.
The Investment and Financial Industry Faces the Same A.I.-Driven Revolution
Hedge funds and large institutional investors have been using Artificial Intelligence to analyze large data sets for investment opportunities, and they have also unleashed A.I. on charts to discover patterns and trends. Not only can the A.I. scan thousands of individual securities and cryptocurrencies for patterns and trends, and it generate trade ideas based on what it finds. Hedge funds have had a leg-up on the retail investor for some time now.
Not anymore. Tickeron has launched a new investment platform, and it is designed to give retail investors access to sophisticated AI for a multitude of functions:
IYF broke above its upper Bollinger Band on October 04, 2024. This could be a sign that the stock is set to drop as the stock moves back below the upper band and toward the middle band. You may want to consider selling the stock or exploring put options. The A.I.dvisor looked at 38 similar instances where the stock broke above the upper band. In of the 38 cases the stock fell afterwards. This puts the odds of success at .
The 10-day RSI Indicator for IYF moved out of overbought territory on September 03, 2024. This could be a bearish sign for the stock. Traders may want to consider selling the stock or buying put options. Tickeron's A.I.dvisor looked at 47 similar instances where the indicator moved out of overbought territory. In of the 47 cases, the stock moved lower in the following days. This puts the odds of a move lower at .
The Stochastic Oscillator may be shifting from an upward trend to a downward trend. In of 72 cases where IYF's Stochastic Oscillator exited the overbought zone, the price fell further within the following month. The odds of a continued downward trend are .
The Moving Average Convergence Divergence Histogram (MACD) for IYF turned negative on September 25, 2024. This could be a sign that the stock is set to turn lower in the coming weeks. Traders may want to sell the stock or buy put options. Tickeron's A.I.dvisor looked at 43 similar instances when the indicator turned negative. In of the 43 cases the stock turned lower in the days that followed. This puts the odds of success at .
Following a 3-day decline, the stock is projected to fall further. Considering past instances where IYF declined for three days, the price rose further in of 62 cases within the following month. The odds of a continued downward trend are .
The Momentum Indicator moved above the 0 level on October 08, 2024. You may want to consider a long position or call options on IYF as a result. In of 80 past instances where the momentum indicator moved above 0, the stock continued to climb. The odds of a continued upward trend are .
Following a 3-day Advance, the price is estimated to grow further. Considering data from situations where IYF advanced for three days, in of 375 cases, the price rose further within the following month. The odds of a continued upward trend are .
The Aroon Indicator entered an Uptrend today. In of 357 cases where IYF Aroon's Indicator entered an Uptrend, the price rose further within the following month. The odds of a continued Uptrend are .
Tickeron has a negative outlook on this ticker and predicts a further decline by more than 1.00% within the next month with a likelihood of 66%.
The average fundamental analysis ratings, where 1 is best and 100 is worst, are as follows
Category Financial