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The potential impact of machine learning and data analytics on financial services is undeniable, with proven applications in cybersecurity, automated trading, risk management and fraud, venture capital, and consumer engagement. Many technically advanced firms have been leveraging A.I. for years, long before the current hype cycle.

Our finance industry reports are released several times a year and report important updates on new applications of machine intelligence, traction and metrics of established technologies, and practical advice for implementing similar strategies at your own organization.

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Original Content

TOPBOTS writers are experts in enterprise A.I. applications, ranging from technology to marketing to operations. We offer original content based on industry news, academic research, domain expert opinions, internal projects, case studies, and trending data to keep you informed about the impact of machine intelligence on finance services.

Here are just a few examples of our coverage of A.I. in financial services.

The Most Successful Bot Company You’ve Never Heard Of

The world’s fastest supercomputers reside in China, not America. And, while the majority of the planet’s most valuable tech brands still carry Uncle Sam’s imprint, Chinese rivals tread not far behind. Alibaba, Tencent, Baidu, Xiaomi, and Huawei are just a few of the...

Can A.I. Defend Our Financial Institutions Against Hackers?

Could artificial intelligence defend us against thieves and barbarians at our digital gates? Or will machine learning be one more addition to cyber criminals’ ever-growing arsenals? The recent WannaCry ransomware attacks, which infected over 230,000 computers in 150...

12 Key Steps To Selling AI To Financial Services

Artificial intelligence will be the top profit driver of the future. Accenture and Business Insider both said so. So did Gartner and Forrester. Everyone - from tech titans to corner pizza parlors - have been sold on the benefits of automation and machine...

Banks Eager For Artificial Intelligence, But Slow To Adopt

Facebook, Google, Microsoft and Baidu spent at least $8.5 billion beefing up their AI talent. Amazon spends $228 million a year just to find people to run Alexa and related machine learning initiatives. Even small to medium businesses in every sector - from fast food...

Why Smart Taxation Needs Smart Machine Learning

Taxes do a lot of things. Used wisely, they can make life safer, healthier and worthwhile. Used unwisely, they can spark rebellions like the one we celebrate every July 4th. They stick around for a pretty long time, from the moment you’re old enough to work until the...

Unsupervised Investments: A Guide to AI Accelerators and Incubators

I. Rationale for the post The current startups landscape is incredibly messy, with all the venture capitalists, angels, incubators, accelerators, private equity funds, corporate venture capital, private companies, and research grants. There are plenty of ways to get...

Unsupervised Investments: A Guide to A.I. Investors

I. Investing in AI Investing in AI is not an easy job: AI technologies can be black boxes and unless you are able to dig into lines of code, they may be inscrutable. Simply looking at proof of concepts might not be enough to really understand the underlying stack...

Chatbots Go Cha-Ching: The Looming Impact of A.I. in Finance

From minting coins to dispensing greenbacks on ATMs, the love affair between money and machine goes a long way back. The pervasive influence of technology in how we create, exchange and store money treads a colorful history — replete with culture-shifting innovations...

Capital One Seals Tech Street Cred With Forays Into AI

From ATMs and mobile wallets to chatbots and robo-advisors, technology relentlessly transforms how we store, transfer and manage money. Capital One moves at the forefront of this transformation — one of the largest and among the first banking institutions in the U.S....

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