NTT DATA Luweave

Exhibitor Stage Presentation

Speaking Sessions

Date/Time	Tuesday 11/10/2022　11:15 a.m. - 11:45 a.m.
Venue	Exhibitor Stage
Theme	Digitalizing countermeasures against Trade-Based Money Laundering Case Study: How SMBC tackles TBML with cutting-edge technologies
Presentation Summary	Major regulators are increasingly focusing on trade-based money laundering (TBML) besides legacy transaction monitoring. Due to the inherent complexity of international trade transactions and the variety of TBML schemes, financial institutions need to address TBML from both technology and operational perspectives. We will present a case study on how SMBC has leveraged digital capabilities to mitigate TBML risks.

Are you ready for ESG driven world ?
-PCAF, evaluating carbon emissions in a financial institution-

Tuesday 11/10/2022
3:15 p.m. - 3:45 p.m.

Wednesday 12/10/2022
10:15 a.m. - 10:45 a.m.

Location: NTT DATA Luweave Booth (B97)

In every industry, companies are getting ESG-oriented. Financial institutions will play a significant role in realizing ESG driven world since financial institutions interact with corporates in all industries in various ways and have some impact on corporate behavior.

Some leading companies have started to measure their carbon emissions and set a solid target on when they achieve zero emissions on a standalone basis and even on a supply chain basis. Financial institutions are supposed to evaluate not only their own carbon emissions but also their investing and lending portfolio while there is a long way to go to achieve it.

In this session, we will discuss a practical approach to evaluating carbon emission in a financial institution with PCAF approach.

PCAF: The Partnership for Carbon Accounting Financials

How to machine-read human-readable data
-TBML use case-

Tuesday 11/10/2022　10:15 a.m. - 10:45 a.m.

Location: NTT DATA Luweave Booth (B97)

These days, many business processes are getting digitalized. It has benefited us significantly. Due to digitization, we have overcome time constraints and location constraints in many domains.

We, however, understand that many business processes remain in a traditional style based on papers and manual processing. As an IT company, we have been struggling against obstacles to digitalizing business processes.

One of the most significant issues is that a machine is not as intelligent as a human in reading data in many cases. Once a machine can read data appropriately, it can process data much more quickly and precisely than a human.

In this session, we show you what technical approach we are taking to overcome difficulties in machine-reading human-readable data for the “Trade-Based Money Laundering” case.

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