AML | December 28, 2017

The REG/SUM Event in Tokyo – Key Takeaways on the RegTech Landscape

BY Alex Baghdjian

Ayasdi was invited by the Nikkei to attend Japan’s first ever RegTech event in December 2017 called REG/SUM. The event had a great mix of start-ups from around the world, Venture Capital firms, major banks, members of Japan’s House of Representatives, and even the Japanese regulator (FSA). We were provided the opportunity to not only showcase our Intelligent AML approach, but were also invited to a closed room roundtable on AI with some of the strongest thought leaders in the industry. Below are some key takeaways from the event:

  1. Conversations between Regulators and banks and start-ups are key: the need for banks and start-ups to be in a regular dialogue with regulators was highlighted multiple times. The Japanese regulator explained how it takes time for regulators to catch up on the latest trends and then subsequently assign budgets and teams to tackle new issues. He called on the RegTech ecosystem and banks to help start dialogues early on and take the initiative to understand what additional risks they were bringing into the financial system. Another panelist mentioned “banks want to know what the regulator is seeing amongst vendors, while regulators want to know what RegTech companies know. At the end of the day, regulators don’t know what they don’t know. We need to move on from seeing the regulator as the enemy. The regulator is our friend. We have a common goal”.  We agree and have a continuous dialogue with regulators in both the US and the UK – ranging from the OCC, CFTC, and FINRA in the United States to the FSA in the United Kingdom as a result.
  2. Top banks will shift how they adopt AI in the future: Most banks are currently adopting AI through siloes in the organization with limited standardization across the bank. Clara Durodié from Cognitive Finance Group mentioned that one of their banking clients had a far too large number of disconnected projects which proliferate disjointed communication and knowledge sharing. She pointed out that over the next 2 years banks will shift how they adopt AI from a siloed approach beginning in the line of business to a complete top-down strategy from the C-Suite. This will favor platforms that support applications over point solutions.
  3. High expectations for RegTech: This was touched on by the leadership at one of Japan’s three superbanks. He said that they were spending $3-4bn on compliance every year and that compliance headcount has tripled! However, the real difficulty with compliance is that there is zero tolerance. So, there is a “high expectation for RegTech to make things more efficient”. He called AI a “catalyst for change in the existing process” and gave the example of how it could potentially reduce mistakes by freeing time for compliance personnel to double-check their work, hence reducing errors and risk. We’ve already seen strong results from RegTech innovations, such as HSBC’s ability to reduce their AML false positives by more than 20% by using Ayasdi’s technology.
  4. Banks want to adopt AI through applications: When discussing AI adoption in banks, it was unanimous amongst thought leaders that banks would primarily choose to adopt AI through applications. Though horizontal solutions and approaches provides benefits as well, AI-powered applications are how banks will make quick, tangible changes to their existing processes. This is a function of the talent gap that financial services firms are seeing with data scientists as well as the fact that applications simply impact a larger swath of the organization. At Ayasdi, we provide our clients an easy framework to develop applications with both Ayasdi Envision and our SDK.
  5. The decline in correspondent banking needs to be addressed: Banks have been reducing their risk by cutting off correspondent banking relationships, leading to heavy repercussions on society as highlighted by The Economist. The Japanese Bankers Association and Mitsubishi UFJ Financial Group (MUFG) discussed how reducing or breaking correspondent banking relationships effectively reduces one of the main goals of the financial services industry: financial inclusion. They highlighted that one way to tackle the difficulties associated with the correspondent banking business is through collaboration between banks, other industries, and regulators. From an Ayasdi perspective, our initial AML pilot at HSBC was around correspondent banking AML and essentially reducing the costs associated with the business, while maintaining the same level of risk mitigation. We are proud to say we are helping with solving the correspondent banking risk problem through our technology.
  6. Build RegTech solutions of off standards: This was stressed multiple times from the Bank of England’s Beju Shah, Head of Data Collection & Publication. He gave the example of the supply chain industry and how it made a push to standardize data across firms, leading to an increase in trade globally by 5x in 25 years. His recommendation for RegTech firms was to “work with established standards.”
  7. AI needs to be used for good: Like any new, growing technology, there is the opportunity to leverage it for both good and bad purposes. Though AI can be used to predict the ideal Care Path for a hospital patient or catch money launders, it can also unfortunately be used for malicious purposes. The REG/SUM conference collected pioneers in the AI space in one room who all agreed to make sure the technology be used to benefit the public. The transformation of the financial services industry through AI has only just begun. In the near future, AI will open the door for more financial inclusion and more effectively prevent criminals from accessing the financial system.
  8. Justification is the biggest problem for AI right now: Discussed by both banks and the regulator, the largest problem with AI right now is justification. Without understanding why an AI solution came up with the results it did, there won’t be full trust in the solution. Ayasdi’s Topological Data Analysis-based (TDA) Platform and solutions are able to provide that much needed justification needed by both banks and regulators. As our Chairman Gurjeet Singh mentions in a recent blog post “Justification is not simply a “feature” of AI – it is core to the success of the technology. The amount of work underway to move us beyond explainable AI/transparency is a testament to its importance. TDA gets us there today – without sacrificing performance. In the AI arms race, that is worth something.”
  9. Predictive Analytics is the future of RegTech: Lindsay Davis from CB Insights covered the four phases of RegTech – beginning with the “Manual” phase to final phase of “Predictive Analytics”. Ms. Davis broke up Predictive Analytics into four groups: Risk Identification, Compliance Intelligence, Identity Management, and Background Screening. She even introduced the novel concept of the “robo-regulator” – a regulator powered by AI that could flag illegal behavior and potentially replace the SEC’s 4,200 employees.

Granted, there is a lot to digest from the conference (always a good signal if your are looking for interesting events) but the key points can be summarized as follows: we are entering the AI age when it comes to regtech. Our ability to have it work will be a function of our capacity to openly communicate what the AI is doing – with regulators, internal model review boards and even customers. If we can do that, we can create a better financial system.

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