The banking sector has witnessed multiple paradigm shifts, traditionally occurring in parallel with emergent technology trends. Technologies that were previously at the forefront of banking transformations are now standard issue by modern banks, with the most notable examples taken for granted by millions of customers on a daily basis.
The advent of credit cards and magnetic strip technology arrived during the 1960’s and reached mass adoption during the 1970’s. At the same time, the first ATM was installed in 1967 in London, easing customers’ access to their funds, and simplifying back office processes.
However, the most major transformation to date was the introduction of online banking. By 2006, over 80% of banks had adopted online banking, revolutionizing customer banking access and providing significant cost savings for banks.
But the biggest revolution in banking technology is happening right now–the emergence of artificial intelligence (AI) and big data.
During 2019, the combined power of these two technologies is expected to transform three major areas of banking operations. We examine which parts of the banking value chain those changes are most likely to impact.
Marketing and Sales
Big data sets offer unique opportunities for banks, but processing such an enormity of data is not without its difficulties.
The most significant development in this field is AI-driven predictive analytics, developed from prediction sciences. Predictive analytics processes customers’ data via AI and machine learning, to identify data which offers insight into future events.
Advancements in predictive analytics are expected to be a boon for banking marketing departments, which hire big data scientists to manually clean, analyze and draw predictions from big data sets. This process is costly. So costly, that by 2020 big data analysis will cost $203 billion, with banking accounting for over 13% based on previous years.
In addition to expensive salaries and scarcity, data scientists may also take months to gather useable results. That’s where AI-based models come in. Data science firms are entering the market, offering AI-powered solutions with greater efficiency than traditional data scientists, offering answers in minutes rather than months.
One such predictions platform, Endor, is based on “Social Physics” theory from MIT, a novel research area focused on prediction of mass human behavior. Using field-tested models, Endor allows banks to ask their platform direct questions, aimed at predicting customers’ behavior–such as “Out of all active card holders in the last 6 months, who is likely to stop using our card next month?”.
AI has the potential to redefine many of the tools and methods we use for analysis, learning, and interpreting the world around us, said Yaniv Altshuler, founder and CEO of Endor.
“The technology is already gaining traction in the business community where experts predict that it will be a driving force over the next decade. From a mathematical point of view, it is likely that commercial AI machines will be exposed to vastly more information than any professional trader can possible digest, giving a clear ‘win’ to AI and ML models on the ‘data’ aspect.”, adds Altshuler.
AI-powered predictive analytics provides significant cost and time savings for marketing departments, and boosts customer loyalty, by only contacting customers who are most likely to be receptive to new services.
Risk Management and Fraud Prevention
In the fight against fraud, few technology solutions hold as much potential as AI-driven big data. As online banking customers become more savvy, 80% of customers agree that fraud protection measures are a priority when choosing a banking service.
Banks can utilize AI and machine learning to track how customers use their accounts. In a recent high profile case, AI technology revealed fraudsters accessing a victim’s bank account, by identifying that they were using the scroll bar to navigate the site–while the victim accessed their account through their laptop and only used a trackpad.
As extreme as this example is, it’s a testament to the power of AI-based fraud detection techniques, which are able to store and process huge data sets, tailored to individual customer behaviors.
Risk management will likewise benefit from AI learning. It’s estimated that banks could realize a 25-50% fall in credit decision times, alongside a 10% reduction in credit losses, with AI-based models.
Featurespace, a provider of AI behavioral analytics for risk management, detects and blocks banking fraud attacks in real-time. Their proprietary platform, called ARIC, can result in a 70% reduction in declined transactions, but with a 50% improvement in operational efficiency; simultaneously preventing fraud while approving genuine new customers.
By removing the potential for human error while approving a loan, banks can avoid fraudulent borrowers, or those with poor credit scores, vastly increasing their revenues and improving customer service.
AI Chat Bots and Robot Operators
Existing within the realms of science fiction just a few decades ago, modern AI-driven chat bots and operators are increasing their capacity for meaningful contributions to customer service, operating as the public face of online banking.
Although their ancestors were a source of frustration, modern robot phone operators are utilizing AI emotional analytics to monitor customers’ voices, identifying and developing unique algorithms to changes in tone and negative responses. Not only is this data used to improve customer experience, but similarly, robot operators can flag potentially high-risk interactions.
Moreover, chat bots are important for online banking. In addition to cost savings compared to human equivalents, chat bots are also able to offer financial advice and 24/7 customer support.
Kasisto, the leading enterprise-ready AI platform for conversational chat bot banking, resolves 82% of all conversations with real customers without the need for human assistance. The AI chat bot, called KAI, can assist customers in locating transactions, making payments, and onboarding new account holders.
In a recent survey, 65% of banking firms believed that customer service, including marketing and the use of chat bots, was the component of the banking value chain which would be most significantly impacted by AI.
Banking on AI and Big Data
With a multitude of benefits, it’s little wonder that financial providers are banking on AI solutions. With a surge in AI technology applications during the last five years, banks are optimizing their operations across the banking value chain using AI-based customer service, fraud protection and marketing.
Although the AI banking transformation may take many years to implement industry-wide, 2019 looks to be a landmark year for big data analysis and AI adoption in the financial sector.
Produced in association with StudioWorks
Nvidia forecasts sales above estimates as gaming chip sales surge
By Chavi Mehta and Stephen Nellis
(Reuters) – Nvidia Corp forecast better-than-expected fiscal first-quarter revenue on Wednesday, expecting strong demand for its graphics chips used in gaming PCs and artificial intelligence chips for data centers.
As people wait for COVID-19 vaccine rollouts around the world, stay-at-home orders have helped sustain the demand for chips used in personal computers, gaming devices and data center infrastructure that enables remote working.
The Santa Clara, California-based company’s gaming chips have also regained popularity for mining cryptocurrency, a trend Nvidia is trying to counter by throttling its gaming chips ability to mine for currencies and instead offering specialty chips for mining.
While Nvidia was long known for its gaming graphic chips, its aggressive push into artificial intelligence chips that handle tasks such as speech and image recognition in data centers has helped it become the most valuable semiconductor maker by market capitalization.
It has eclipsed rivals Intel Corp and Advanced Micro Devices.
Shares were up 3% at $597.50 in extended trading after the results.
On a conference call with investors, Chief Financial Officer Colette Kress said that a global chip crunch made it hard to keep the company’s flagship gaming chips introduced last fall in stock and that the chips would likely remain in tight supply through the fiscal first quarter.
The company also said it will make a change to its gaming chips starting with the RTX-3060s to make them less efficient for mining cryptocurrency. The company said it will instead introduce mining-specific chips.
“We would like GeForce GPUs (graphics processing units) to end up with gamers,” Kress said.
Kress said analysts have estimated that cryptocurrency mining contributed between $100 million and $300 million to Nvidia’s sales in the fiscal fourth quarter. The company expects the new mining chips to generate about $50 million revenue in its fiscal first quarter, Kress added.
The company expects first-quarter revenue of $5.30 billion, plus or minus 2%, above analysts’ average estimate of $4.51 billion.
Revenue in the quarter ended on Jan. 31 rose to $5 billion from $3.11 billion a year earlier. Analysts on average were expecting $4.82 billion, according to IBES data from Refinitiv.
Revenue in the company’s gaming segment was $2.5 billion, above analyst estimates of $2.36 billion, according to data from FactSet. Data center revenue was $1.9 billion, above estimates of $1.84 billion according to FactSet data.
(Reporting by Chavi Mehta in Bengaluru and Stephen Nellis in San Francisco; Editing by Maju Samuel and Will Dunham)
Running boom to help Puma recover after slow start
By Emma Thomasson
BERLIN (Reuters) – German sportswear company Puma expects the financial impact from coronavirus lockdowns to last well into the second quarter, but believes global growth in running should help to support a strong improvement after that.
“We clearly see a running boom in the whole world,” Chief Executive Bjorn Gulden told journalists, noting that yoga and other outdoor activities are also doing well. He expects the healthy living trend to continue even after the pandemic.
Gulden said his optimism is underlined by the fact that orders for 2021 are up almost 30% compared to a year ago, with bookings for running products particularly high.
However, there is still uncertainty about when lockdowns in Europe will end, with about half of the stores selling its products currently closed in its home region.
For the full year, Puma expects at least a moderate increase in sales in constant currency, with an upside potential, and a significant improvement for both its operating and net profit compared with 2020.
Shares in Puma were down 2.9% at 1100 GMT.
“The wording on outlook looks softer than we had anticipated, even by Puma’s cautious standards,” said Jefferies analyst James Grzinic.
Gulden noted that a shortage of shipping containers bringing products made in Asia would impact margins, with freight rates likely to double in the next 12 months.
Puma will put a stronger focus on the women’s market in future, Gulden said, creating shoes better modelled to female feet for running and soccer and capitalising on partnerships with celebrities like singer Dua Lipa and model Cara Delevingne.
Gulden admitted Puma had been slow in creating its own app, but it plans to launch one towards the end of the year, further supporting online sales, which grew by 63% in 2020.
Rival Nike in December raised its full-year sales forecast after demand for outdoor sportswear drove an 84% surge in online sales.
Gulden said he is hopeful that the Olympics will go ahead in Japan and the European soccer championship will also take place after both were postponed from 2020.
($1 = 0.8226 euros)
(Reporting by Emma Thomasson; Editing by Mark Potter and Keith Weir)
ExxonMobil to sell some UK, North Sea assets to HitecVision for over $1 billion
(Reuters) – Exxon Mobil Corp said on Wednesday it would sell its non-operating interest in its UK and North Sea exploration and production assets to private-equity fund HitecVision for more than $1 billion.
Exxon has been looking to sell its oil and gas assets since late 2019, seeking to free up cash to focus on a handful of mega-projects.
The deal includes ownership interests in 14 producing fields operated primarily by Shell as well as interests in the associated infrastructure. Exxon could also receive about $300 million in contingent payments based on a potential for increase in commodity prices.
Exxon’s share of production from these fields was about 38,000 barrels of oil equivalent per day in 2019, the company said.
Exxon said it would retain its non-operated share in upstream assets in the southern part of the North Sea as well as its interest in the Shell Esso gas and liquids (SEGAL) infrastructure, which supplies ethane to the company’s Fife ethylene plant.
HitecVision, in partnership with Eni, had bought Exxon’s Norwegian North Sea assets for $4.5 billion in 2019.
Initially, Exxon hoped to raise more than $2 billion from the sale, which was planned for late 2019. In June 2020 sources told Reuters that the portfolio was more likely to fetch $1 to $1.5 billion given the oil price weakness last year.
(Reporting by Arathy S Nair in Bengaluru; Editing by Anil D’Silva)
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