“The number of individual regulatory changes banks must track on a global scale has more than tripled since 2011, while banks and other financial institutions have spent nearly $321 billion on compliance enforcement actions (from 2007 until 2016).1 As regulatory compliance becomes increasingly burdensome and costly to manage, every financial organization is feeling immense pressure to update resource-intensive manual compliance programs. Organizations need technology-driven solutions that leverage automation and can be easily integrated into existing processes and software.
Compliance.ai, a modern regulatory change management platform for financial services companies, has developed a strategic partnership with LogicManager, the leading enterprise risk management (ERM) software provider. With this partnership, LogicManager adds Compliance.ai’s comprehensive, customized and financially-focused regulatory content to its integrations library within their platform. This partnership will empower compliance teams to proactively manage regulatory changes.”
“In 2018, the business value of AI was estimated to be $41.1bn, which includes the cost savings and efficiencies of introducing AI technology compared to keeping existing infrastructures and processes.
North America is tipped to be the biggest market for AI in banking between 2018 and 2023. The business value of AI in this region will go from $14.7bn in 2018 to nearly $79bn by 2030.
‘Countries like China, Japan, South Korea, Hong Kong and Singapore are likely to drive the demand for AI within the banking sector over the next ten years,’ added Tait.
It’s not all good news: job losses and re-assignments will be common, IHS Markit estimates that by 2030, around 500,000 bank workers in the United Kingdom and 1.3m in the United States could be affected.”
“Money laundering accounts for up to 5% of global GDP – or $2tn (£1.5tn) – every year, says the United Nations Office on Drugs and Crime. So banks and law enforcement agencies are turning to artificial intelligence (AI) to help combat the growing problem. But will it work?
‘Estimates suggest that not even 1% of criminal funds flowing through the international financial system is confiscated,’ says Colin Bell, group head of financial crime risk at HSBC.
In the UK alone, financial crime Suspicious Activity Reports increased by 10% in 2018, according to the National Crime Agency.
Once the system has learned legitimate behaviour patterns it can then more easily spot dodgy activity and learn from that.”
“One recent report from the International Data Corp. found that the banking industry is the second biggest investor in AI technology worldwide behind retail.
‘The financial industry is uniquely ready to make a move in the space and bring that computational experience,’ says Jason Mars, CEO of Clinc, a startup that makes chatbots for financial institutions like Barclays and USAA.
These virtual assistants are expected to trim hundreds of millions of dollars in service expenses as the technology becomes one of the dominant forms of addressing customer issues.
A study from Juniper Research in February forecast that industrywide cost savings from chatbots could reach $7.3 billion by 2023, a 3,400 percent increase from the estimated $209 million they are expected to provide this year.
‘Banks have come to realize AI is not ready to work miracles yet,’ notes Forrester analyst Aurélie L’Hostis, who specializes in digital strategy for retail banks. ‘You really need to have a specific approach to drive your strategy. You can’t just launch a chatbot without knowing why you’re doing it.'”
If you’re involved in financial services you’re likely familiar with the name Jamie Dimon. If not, he’s the Chairman and CEO of JP Morgan Chase, and arguably one of the most influential leaders worldwide.
A quick Google search will return references to “America’s Most Important Banker,” “Savior of Wall Street.” “Last CEO Standing.”
With that context, I just stumbled upon Mr. Dimon’s shareholder letter dated April 4, 2019 and I wanted to share. He is clearly all-in on the benefits of artificial intelligence and machine learning.
Here’s the message verbatim. I’ve also included a link to the full letter. The AI commentary is on page 34.
“The power of artificial intelligence and machine learning is real.
These technologies already are helping us reduce risk and fraud, upgrade customer service, improve underwriting and enhance marketing across the firm. And this is just the beginning. As our management teams get better at understanding the power of AI and machine learning, these tools are rapidly being deployed across virtually everything we do. We can also use artificial intelligence to try to achieve certain desired outcomes, such as making mortgages even more available to minorities. A few examples will suffice:
• In the Corporate & Investment Bank, DeepX leverages machine learning to assist our equities algorithms globally to execute transactions across 1,300 stocks a day, and this total is rising as we roll out DeepX to new countries.
• Across our company, we will be deploying virtual assistants (robots driven by artifi- cial intelligence) to handle tasks such as maintaining internal help desks, tracking down errors and routing inquiries.
• In Consumer Marketing, we are better able to customize insights and offerings for individual customers, based on, for example, their ability to save or invest, their travel preferences or the availability of discounts on brands they like.
• Technological solutions help us do better underwriting, expediting the mortgage or automobile loan approval process, letting the customer accept the loan in a couple of clicks and then start shopping for a home or car.
• In our Consumer Operations, we are using AI and machine learning techniques for ATM cash management to optimize cash in devices, reduce the cost of reloads and schedule ATM maintenance.
• And our initial results from machine learning fraud applications are expected to drive approximately $150 million of annual benefits and countless efficiencies. For example, machine learning is helping to deliver a better customer experience while also prioritizing safety at the point of sale, where fraud losses have been reduced significantly, with automated decisions on transactions made in milliseconds.
We are now able to approve 1 million additional good customers (who would have been declined for potential fraud) and also decline approximately 1 million additional fraudsters (who would have been approved). Machine learning will also curtail check fraud losses by analyzing signatures, payee names and check features in real time.
• Over time, AI will also dramatically improve Anti-Money Laundering/Bank Secrecy Act protocols and processes as well as other complex compliance requirements.”
Wow!! That speaks volumes about where we’re headed with the potential for artificial intelligence and machine learning in banking and financial services.