Just as leading financial executives were beginning to warm up to digital first strategy, Application Platform Interface (API) and Open Banking, IT service and solution providers have moved the needle further ahead to ‘Banking-as-a-Service (BaaS)’, ‘Platform-as-a-Service (PaaS)’ and ‘Infrastructure-as-a-Service (IaaS)’. Touting these as must haves to truly modernize legacy banking infrastructure since anything less than this is just blase.
For long, executives have been told that every company is a tech company, including those within Financial Services industry. Now this concept has been further expanded such that according to experts, every company is in the business of hardware, computing, storage, cybersecurity and AI, who just so happen to offer financial products.
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In recent times, many solution providers have claimed embedding AI in their Anti Money Laundering (AML) offerings. Upon conducting further research, it has become apparent that most enterprise level solution providers are supplementing existing AML solutions with predictive analytics, dashboard overview while very few are actually offering AI enabled real-time monitoring capability or agile solutions that respond to future anomalous behavior.
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In uncertain and precarious times, most enterprises split into one of these two camps.
Those wanting to capitalize on lurking opportunities at any cost (arbitrage) and those wanting to retain customers while carefully helping them navigate through uncertainty. Which approach businesses adopt, is strictly their prerogative as the ultimate objective of any business is to maximize profit for their shareholders, ideally by keeping interest of all stakeholders (such as customers) in mind.
In dire times, it is not uncommon for enterprises wanting to fend for themselves but also wanting to capitalize (even if unfairly, unethically) on imbalances in demand and supply. To combat exploitation, unfair opportunistic advantages, consumers look up to regulators and compliance officers.
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By now, just about everyone has read an article of some sort, warning us of imminent displacement, job loss as Robotic Process Automation (RPA), AI and IoT pervade just about every department, every company and every industry. Unfortunately, some of us and our peers will be displaced. They will have to acquire new set of skills via formal education channels.
But, for many, AI / IoT has already begun to and will (in the future), create stellar opportunities and allow a greater number of people to operate as engaged employees.
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Much is being said and written about ethical AI and governance of AI. But, many of these discussions offer a twenty thousand feet overview, sidestepping critical questions such as who or what in an organization should be providing oversight, what does that entail, what are some baseline expectations – how do you govern AI or for that matter, even make sure that it is ethical? How does one translate this model to Financial Services?
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Inadvertently, computer vision and machine vision are often used interchangeably; when in fact, they are two different albeit related concepts.
Computer vision is an algorithm that processes and interprets an image before issuing instructions for other components to act on it, while machine vision is an engineering based system, which uses a camera to see an image. Machine vision has been around for sometime but computer vision has modernized it, analogous to how some may say that, AI has modernized RPA.
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In Europe, PSD2 (Payment Security Directive) and FIDO (Fast Identity Online) Standard are boosting FinTech disruptors’ (third party applications, online banks, etc.) position and legitimizing their identity in banking, which has traditionally been dominated by a handful of incumbents. According to Business Insider, UK has three banks in the top ten largest banks in the Europe. PSD2 is a pan-European directive, intended to spark regional innovation, spur healthy competition between challenger and legacy banks, while specifying customer centricity as it’s core.
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