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11050_Peter_Zemsky_AI_Business_School_4_FSI_FINAL_V2

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>>Peter Zemsky: Simultaneously meeting the needs of regulators customers and share holders is the central challenge in the financial services industry. Even the biggest and the most trusted brands find themselves on the wrong side of regulators at times with significant financial and reputational consequences. Back in 2012, Europe's largest bank, HSBC paid a 1.9 billion dollars fine related to drug lords laundering 100s of millions of dollars through HSBC transactions. Even with the financial penalty paid, the reputational damage lingered including an entire episode of the 2018 Netflix show, Dirty Money devoted just to this scandal. As a result of this experience, HSBC invested heavily in its KYC, "Know Your Customer" capabilites. How our AI enhanced digital technologies helping HSBC meet critical regulatory requirements in a cost effective and user friendly way. KYC processes have proven increasingly critical for value creation. They reduced the risks of major fines and surfs to protect the bank's reputation, which is critical for customer trust, however, traditional solutions are far from perfect. First, they are costly and labor intensive. HSBC reportedly hired an additional 2000 staff for monitoring and investigation after the scandal. And second, these processes can put a heavy burden on legitimate customers by delaying their transactions and imposing additional paper work on them. In the middle east, one in five transactions were reportedly being delayed, such loss convenience can undermine that heavy investments banks make in their relationship development. Over time, HSBC increasingly turned to digital technologies to break these trade offs. As with most major banks, HSBC over this period was investing in the digital transformation of its organization and culture. In looking at their efforts, with KYC processes, what proves world. decisive from their digital transformation work, are their efforts to build bridges to starts ups in the thin tech world. For example, they created a tech advisory board to help them track the latest developments and created their own start up investment fund. Let's look at two of the partnerships HSBC pursued and how they contributed to a leap in value creation. The AI start up Quantexa helped them to process vast amounts of customer data, both internal and external in order to spot early patterns of suspicious behavior. The goal to build a real time assessment of every customer. AYASDI is an AI start up that provided them expertise to processes. automate large parts of their burdensome compliance These combined efforts yielded significant improvements in their value proposition. In the middle east for example, they were reportedly able to them instantaneously take 70% of the previously delayed transactions and clear Better predictions meant a significant reduction in the number of false alerts that needed to be investigated. Lowering costs and allowing the bank to expand the number of transactions they supported with the same workforce. The AYASDI cofounder was a member of the tech advisory board and HSBC was an earlier investor in Quantexa. Here are the initial takeaways from this case. First, AI is helpful in breaking the trade off between two trends. The one hand increasing demands from users for convenience and on the other increasing pressure for compliance from regulators. This does this by allowing you to leverage rapid low cost predictions in constructing your value propositions. In terms of executing on such advance strategies, we see that building partnering capabilities can be key as it allows banks to access expertise in the thriving thin tech center. What about value capture? Clearly, the lower costs and greater customer satisfaction contribute to a company's financial results. However, what about all of the banking customers not served by HSBC. With all of their corporate focus on this issue and their effective collaborations, they had emerged from the scandal as an industry leader in changing KYC processes. Now, the usual approach to maximize value capture is to leverage the use of your competitive advantage to grow market share. Interestingly, this is not the approach taken by HSBC in part because of the nature of the banking industry. Banking customers tend to be sticky and KYC is a small part of a bank's overall value proposition, hence the prospective HSBC leveraging their advantage to grow share was limited. Instead, they partnered with a third party, the outsourcing player EXL to sell their advanced KYC solution to other banks as a utility. In doing this, they show themselves to well understand the way AI technology is developing in the financial services industry and beyond. I will explain this point using the industry value chain, which is a helpful tool for visualizing some of the dynamics in an industry. The idea is to show the key activities that go into value creation in terms of banking key inputs are real estate for branches in offices and human talent as it is a service business. Of course, this is a simplification but it allows us to focus on the key changes. One of these changes is the emergence of an important new supplier to financial services providers of AI enabled digital solutions. It's striking to me that HSBC, a traditional player actually drove the creation of one such cutting edge solution. It did so as we saw through partnerships and indeed this is really the key to traditional companies that want to operate at the cutting edge of AI technology. Especially in financial services, there is a vibrant ecosystem to support such AI strategies. First, note that most of the code needed for machine learning is actually open source and publicly available on platforms like GitHub. Of course, you do need skilled data scientists to leverage these code libraries. With AI having such broad impacts across industries and functions data science profiles are in short supply. Here to though, there is external help, traditional IT and advisory companies are employing literally armies of data scientists and looking to deploy them to their traditional financial services clients. What about the heavy infrastructure in terms of processing power and data storage needed to support the AI strategies. There is intense investment by the leading cloud providers. A vibrant ecosystem indeed of course to leverage this ecosystem, you do need to develop an organization that has solid internal capabilities in AI and digital. Finally and toward highlighting that we are part of this ecosystem cut across industries in the economy like the big infrastructure providers. Increasingly, we are seeing the emergence of industry-specific applications and associated providers and this is especially true in financial services. Let me close the case by highlighting a few additional take aways for you as we just saw mapping shifts in the industry value chain is a really useful way for keeping track of the many new activities and players that AI is bringing in to the financial services industry. One important category will be specialized players providing AI solultions tailored for banks and financial services more generally. Thus, one needs not just capabilities in managing individual partnerships, but actually a broader ecosystem mentality in your organization. Now, skill full access to the increasingly vibrant AI ecosystem is not enough for value creation. Companies need to assure that they have the rich and well organized internal data sets that are the critical inputs. This is going to require continued and strategic investment in their digital transformation journeys of the company and it's processes.

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Posted by: csintl on Jun 18, 2019

11050_Peter_Zemsky_AI_Business_School_4_FSI_FINAL_V2

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