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India organises Gov Tech-Thon 2020 to crowdsource tech innovation
ASTRI and partner launch new AR solution
Researchers from the SMART Infrastructure Facility at the University of Wollongong (UOW) are developing software that will allow existing closed-circuit television cameras to automatically identify and report suspicious or violent incidents.
The project was one of four winners of Transport for NSW’s Safety After Dark innovation challenge. Research into women’s safety revealed that girls and women do not always feel safe participating in our city at night, the brief stated.
While many factors contribute to this, transportation was identified as an area where improvement could be made. A team led by Dr Johan Barthelemy will develop artificial intelligence (AI) software that will automatically analyse real-time camera feeds and alert an operator when it detects a suspicious incident or an unsafe environment. The AI will be trained to detect incidents such as people fighting, a group of agitated persons, people following someone else, and arguments or other abnormal behaviour. It can also identify an unsafe environment, such as where there is a lack of lighting.
The system will then alert a human operator who can quickly react if there is an issue. The data and reports automatically generated by the software can then be used to help prevent the abuse and violence committed towards women after dark in public transportation. Helping him on the project will be a PhD student whose thesis looks at using computer vision across multiple cameras to understand traffic and pedestrian flow. The team is using open-source code that tries to estimate the poses of a human being and predict if there’s a fight.
The incident will then be reviewed by a human controller who will accept or reject the suggestion made by artificial intelligence. In this way, the program will become smarter, learning in a similar way to a human being. As far as the team knows, nothing like this has been attempted globally. The researchers are pushing the limits of technology.
The SMART Infrastructure Facility
One of the largest research institutions in the world dedicated to helping governments and businesses better plan for the future, SMART brings together experts from fields such as rail, infrastructure systems, transport, water, energy, economics and modelling and simulation, providing 30 state-of-the-art laboratories to facilitate this important research. When the $62 million SMART building opened in 2011 as Australia’s first multi-disciplinary applied infrastructure research and training facility, it represented a commitment by the Australian and NSW Governments to apply a more scientific approach to infrastructure planning.
Since opening, SMART has built an international profile working with government agencies in Australia and around the world and has developed a strong network of global collaborators. SMART brings together experts from fields such as rail, infrastructure systems, transport, water, energy, economics and modelling and simulation and provides 30 state-of-the-art laboratories to facilitate this important research.
SMART in collaboration with UOW is leading the digital revolution in the Illawarra with the creation of the Digital Living Lab, a smart city initiative using IoT technology. SMART and UOW have deployed a radio communication network across the region using LoRaWAN technology in a bid to improve the quality of life for people in the community.
NSW’s Safety After Dark challenge
Transport for NSW’s Safety After Dark initiative is focused on making women feel and be safer when travelling in the city. Research into women’s safety revealed that girls and women do not always feel safe participating in the city at night. While many factors contribute to this, transportation was identified as an area where improvements could be made.
Transport for NSW is collaborating with other government agencies, local councils and industry to work on solutions to make the city safer for women.
The Viettel AI Open Platform, an artificial intelligence (AI) platform, developed by the military-run telecoms group Viettel, was launched by the Ministry of Information and Communications (MIC) at a ceremony on 28 August.
The launch is part of a chain of events to introduce Made-in-Vietnam digital platforms to serve the national digital transformation program for 2025, with a vision to 2030 approved by Prime Minister Nguyen Xuan Phuc. According to the MIC Deputy, Nguyen Thanh Hung, the fourth industrial revolution is fundamentally changing production around the world on the back of breakthroughs in the internet and AI.
Many countries have recognised the inevitable development and significant transformational impact of AI in all aspects of life, which changes the balance of economic, military, and political power, he said, adding that AI is the heart of digital transformation.
The Viettel AI Open Platform provides platform technologies using AI to help automate, optimise and efficiently operate organisations and businesses via the world’s most advanced techniques. The platform is currently focusing on areas such as Vietnamese speech processing technology (Speech Processing), Vietnamese natural language processing technology (Natural Language Processing), and computer vision technology (Computer Vision).
The Director of the Viettel Cyberspace Centre, Nguyen Manh Quy, noted that to strengthen research cooperation to boost the national digital transformation program, Viettel is providing the platform free of charge to individuals, businesses and organisations that registered to use it during its application development phase.
In recent years, e-government platforms have developed rapidly. The number of provincial-level built-in and data sharing platforms has increased dramatically. In the past six months, the proportion of ministries and provinces that have this kind of platform increased by over three times; in February 2020, only 25 ministries, provinces had platforms, equivalent to 27%. The figure was 76 ministries July, or 82.6%. Currently, the rate of level-4 online public services is about 15.9%, doubling that of the same period last year. E-document exchanges between state agencies have reached a rate of about 88.5%, very close to the target of 90% by 2020.
Vietnamese enterprises have gradually mastered core technologies and developed technology platforms for digital transformation. MIC created an initiative to weekly launch Vietnamese platforms to honor and promote Vietnamese ICT products. So far, dozens of platforms have been launched.
The Prime Minister has PM requested ministries and localities to address shortcomings in the legal environment for building the e-government. He noted that the rate of online public services remains low, which is unlikely to reach 30% at the year’s end without new ways of implementation. Some ministries and provinces could only reach less than 10%, an alarming level.
The deployment of a national database that creates a foundation for the e-government has been slow, especially on land issues. The Minister urged MIC to map out a training project and a national digitalisation roadmap for localities, as well as complete a draft on the development strategy of the digital government for 2021-2025, with a vision to 2030, in the third quarter of this year.
In coping with the current crisis, the need for accurate and actionable information is paramount for an effective response – but there has never before been a scenario like the current COVID-19 pandemic. In case of a critical event, whether it is an active shooter, natural disaster or pandemic, access to information is vital.
One crucial lesson that emergency responders have learned from simulations is that information is often too fragmented to provide actionable intelligence: the larger the incident, the more complicated it is to collect and assess information and coordinate a response.
There are, however, many tools available to tame this complexity for more rapid and effective response and to minimise impact on responders. These generally address four stages of response management.
In the first, they gather data from various sources to help assess the context and severity of a critical event, calling upon analytical tools to digest and correlate data to help response teams understand what is happening now and what could or will happen later. A second stage locates assets, employees or vital equipment. In a third stage, these systems offer emergency responders and organisations the tools to act by informing people of actions to take, mass-scale notifications for people in affected areas and tools for collaboration between response teams. The final stage enables responders and others concerned to review and evaluate the critical event so that future response can be improved.
Incident response management platforms are often homegrown among responsible agencies and organisations, but technology providers exist to support efforts. Some of these technologies consolidate functionality for all four stages into a single system. Everbridge, for example, began with a focus on multi-modal text messaging after the tragic events of 9/11 and expanded into a platform used in 2012 to notify 10 million people after Hurricane Sandy, and in 2013 by the city of Boston after the Boston Marathon bombings.
As reported, Increasingly these platforms are embracing IoT systems and devices, given the expanded capability among a wide variety of endpoints that responders can use to connect directly with critical information, guidance and communication with those affected by an emergency. In particular, IoT can play an essential part in the information-gathering process. In a 2019 study, the European Telecommunications Standards Institute (ETSI) examined the possibilities of the use of IoT in emergency situations and identified a number of use cases such as emergency calling, mission-critical communications for situational awareness or to protect responder personnel, essential logistics support public warning systems and automated emergency response.
In smart buildings and smart cities, sensors can provide details about temperature, toxic gases and other hazardous conditions. Smart streetlights can analyse traffic congestion and plan evacuation routes through AI analytics. Body cameras can relay live intelligence from public safety workers to the Incident Command Center (ICS), while crisis teams can use IoT wearables to warn and guide civilians.
Artificial intelligence technology is used in several ways to diagnose, respond to or predict coronavirus spread. The radiology department of the Zhongnan Hospital of Wuhan University in Wuhan, China, has modified its AI-driven software to detect cancer in CT lung scans to detect COVID-19-related signs of pneumonia. This is to aid the overworked medics in triage, while in the United States, the Boston Children’s Hospital has created an AI-driven coronavirus map.
The Chinese search engine Baidu has made its Linearfold algorithm available to researchers and medical teams to fight the outbreak to assist in the analysis of the virus, while across the world researchers are turning to AI technology to predict its spread.
Even when everybody understands that it is vital to track data on people’s condition and location during the current times, but it has a definite privacy impact.
The privacy issues are relevant to technology providers, which also see a growing trend among companies that want to know which employee is in which location. In the case of the COVID-19 outbreak, employers may want to see which employee has been in close proximity to a person who has tested positive for the virus.
However, technology’s role in containing and mitigating the virus in the absence of a rapid and reliable diagnostic tool cannot be undermined. It lets governments respond and recover from the global pandemic which would have been a more herculean task than it already is.
Technology providers who are seeking to improve response, stewardship of sensitive data and transparency of processes moving forward must understand that establishing trust and confidence amongst people is of paramount importance.
Continuing its series of sessions with the financial sector industry across ASEAN, OpenGov Asia hosted its third OpenGovLive! Virtual Breakfast Insight with delegates from Thailand on 20 August 2020.
The event once again saw a 100% attendance and a great level of involvement from the audience on the topic of Powering Next-Generation Compliance with AI and Advanced Analytics.
Understanding the importance of compliance and risk management for the financial industry in these tough times and the urgency of deploying tech in this process was the major focus of the varied insights from delegates and speakers.
The session was opened by Mohit Sagar, Group Managing Director and Editor-in-Chief at OpenGov Asia.
Mohit shed light on the harsh reality of the times where everybody is masking data. Further, the danger from threat actors is becoming more and more sophisticated.
These cybercriminals are leveraging advanced technology with a destructive mindset and without any constraints of regulation or compliance.
Financial organisations cannot afford to lag behind in keeping up with the latest technological developments in the field if they want to protect themselves and simultaneously outdo adversaries to survive.
On the issue of compliance, Mohit felt that it had to be seen as a part of the big picture and not seen in isolation. Compliance must be part of a robust framework that necessitates using AI and Analytics to derive desired and clean outcomes.
However, it is important to understand that technology can only augment existing human resources, not replace them.
He concluded by stressing the need for focused leadership and the need to collaborate with partners who champion the field of technology.
After Mohit, Nutapone Apiluktoyanunt, Managing Director, SAS Thailand shared his views on the topic with the audience.
Nutapone began by introducing the company and given a brief overview of the work globally. He spoke about how SAS used analytics to effectively share data around the pandemic with the public using free dashboards.
He shared that their objective as an organisation is to improve lives by making better decisions and they do it by providing a wide range of tech-driven solutions to their customers.
Nutapone then went into detail about other the incredible projects done by SAS in the financial sector industry. These initiatives support areas like digital transformation, customer experience, risk management and fraud & security management.
Making it relatable for the audience, he delved deeper into fraud & security management solutions. Elaborating the myriad of ways in which it can help financial organisations including monitoring, conduct assurance, financial intel and compliance, market and trade surveillance.
He concluded by highlighting SAS’s strength as leaders in the field; not only do they only have solutions for payment fraud and anti-money laundering but are champions in data and analytics.
After Nutapone’s presentation, Ahmed Drissi, Anti-money laundering lead- APAC for SAS shared more details into the SAS money laundering Solution.
Ahmed began by talking about the challenges in using the traditional AML solutions; key among these is their inability to cope with the high volume of online transactions. Ahmed then explained how their solutions can help overcome these challenges.
He spoke about other stakeholders in the industries, like regulators, who also recognise the benefits of using AI and ML in anti-money laundering initiatives. These stakeholders are now whole-heartedly encouraging the use of these technologies in the field.
He supported this by sharing examples of financial regulatory authorities in the USA, UK, and Singapore have started recommending the use of AI and ML in the context of anti-money laundering.
Ahmed went on to share a visual graphic representation of the three phases of AI and ML adoption cycle as done by large global and regional banks. The three phases are Innovation, Adoption and Maturity.
This phased approach was a key insight into how SAS helped organisations improve operational efficiency and reduce false positives.
He also enumerated various AI and ML use cases in AML that include: entity resolution, customer segmentation, post alert scoring, model detection, tuning and optimisation.
In concluding, he presented a bouquet of SAS offerings – Financial Crimes Analytics Solutions – that help monitor and prevent fraud incidence in the organisations.
After Ahmed, Viswanathan Namasivayam, advisor for Data Science Enterprise Architecture, Data and AI group at UnionBank Philippines shared his expert opinion on the topic.
Viswanathan started by pointing out the need for banks and financial institutions to make compliance simplified and robust in light of ever-increasing fraud and hacking incidents.
He highlighted the power of advanced tech like AI and ML. Its efficacy lies in its ability to go beyond a single representation of an individual or an entity rendering a better understanding of fraud risk.
He also emphasised the fact that using tech in regulation and security is non-negotiable and validated this stance with a recent case study from Germany.
To further underscore his point, he shared how supervisors and regulators of the industry are also implementing and encouraging the use of new tech.
He concluded by pointing at the significant paradigm shift in organisations’ approach in handling fraud incidences from initiating action after something irregular has been detected to taking actions to prevent the fraud risk.
Viswanathan was confident that this is was a big step for organisations on their journey towards having a robust risk and fraud management system.
After this powerful presentation, it was time for the polling question session to get all the delegates involved in the discussion.
On the first question regarding major challenges faced during AML investigation process, the Thai audience was split between High rates of false positives (41%) and Lack of data/insights around customers, accounts and entities (41%).
A senior delegate from a major bank shared that not only is the data insufficient, it also lacks accuracy, which makes the investigation very challenging. Furthermore, fraud investigation is not an isolated process, it requires analysing data not just during the time of the incident but also from the surrounding blocks of time. Thus, insufficiency and inaccuracy of data become significant challenges.
It was interesting to see that the response to this question in Thailand was along the same lines as it was in the Singapore session. There too, a majority of delegates voted for high rates of false positives (44%) while the rest of the responses saw an equally distributed portion of votes.
In regard to the next question about the areas that would benefit most from the use of AI and ML the audience was divided among all the available options but two of them accounted for over half the group: Alert triage and risk prioritisation (27%) and Automated disposition of alerts(27%).
A senior compliance officer from a public sector bank shared that she voted for Alert triage and risk prioritisation as in this area, AI can help automise a lot of procedures and processes making them speedier and more efficient. This makes overall work progress fast.
The response to this question in the Singapore session featured an almost equal distribution of responses over all the available options as opposed to a clear inclination towards anyone of them.
On the final question of the expected time to complete an investigation with regards to the enhanced due diligence process, a majority of the audience voted between 30-60 minutes (40%).
When asked for a reflection, another on of our delegate shared that using AI/ML can really help speed up the investigation process, but it also partly depends on how quickly can you get the information from your customer. If your case management system allows you to communicate directly with the customer and get the information embedded in the case, that can really speed up the process too.
It was interesting to observe that when the same question was asked to the Singapore delegates, many shared that they spend more than 24 hours to complete an investigation – pointing to an urgent need for AI/ML-driven solutions.
After the polling session, Ahmed concluded the session with closing remarks. He thanked all the delegates for their time and participation in the event. He said that adopting tech in regulation requires laser light focus – something that SAS champions. He encouraged delegates to engage and collaborate with them if they are working towards it.
The Hong Kong Science and Technology Parks Corporation (HKSTP) announced the launch of the city’s first Technology Validation Platform dedicated to providing businesses and end-users with critical physical and virtual testing to evaluate the performance of AI and Robotics (AIR) solutions for mass adoption in key industries.
The Technology Validation Platform is the first in Hong Kong to apply performance matrices, physical testing and virtual testing in one cohesive validation mechanism. It accelerates the adoption of AIR technologies in Hong Kong by bridging the trust gap between AIR technology providers and companies considering adoption.
A Performance Matrix covering business consideration, quality, safety, operation and technical specifications will be tailored to evaluate the solution performance, enabling solution seekers to find the best fit to meet their needs.
Ground-breaking digital twin testing capability
The platform also provides a direct and seamless path from concept to proven ready-to-adopt products. Tech developers and corporates can bring test solutions to evaluate different aspects of technology performance under numerous user scenarios. Examples include the testing of disinfection robots in hospitals and the simulation of AI algorithms to manage traffic flow in a public transport system. The platform will start the pilot phase in September this year and formally open in early 2021.
The CEO of HKSTP stated that Park is committed to fully harnessing Hong Kong’s world-class R&D talent and AIR innovation potential, which will fuel digital transformation of various industries such as health, finance, retail, logistics.
They are enabling this reality by pioneering a dedicated environment to test and validate cutting-edge technologies into market-ready applications. By delivering validation of various solutions, the Park will bridge the gap between AIR innovation and market adoption, eventually creating industry-wide benchmarks to support local standards development.
The validation testing will be conducted in a physical environment but also virtually via ground-breaking digital twin technology. After gathering performance data from physical hardware testing, companies can create a digital twin of the technology solution – be it a robot or an AI programme – and deploy this into virtual simulations to accurately reflect real-life conditions.
Enhanced infrastructure boosts AI development capability
In addition to the Technology Validation Platform, the development of world-class AIR technologies and innovations also requires optimised infrastructure. HKSTP will extend its services to AI PLUG members and Park companies. Infrastructure enhancements include extended hosting capacity for high-performance computing setup with high-speed connectivity.
Since the official launch of AI PLUG in January this year, more than 30 service partners have been providing technical, business, funding and training support to members across four key features –Tech Shop, AI Infrastructure, Corporate Innovation and AI Academy. With the extended hosting services and increased scalability, HKSTP aims to further strengthen support to the AIR community in Hong Kong.
HK Nurturing AI on Many Levels
In an earlier interview, Dr Andy Chun, Council Member and Convenor of the AI Specialist Group, Hong Kong Computer Society, stated that there is a reason for the increased focus and interest around AI. This is because, as a technology, AI is maturing rapidly.
“We now have a much better understanding of what problems AI can solve and how to implement AI solutions, as well as more readily available AI tools and platforms at a lower cost,” he said.
Citizens’ expectations have also changed.; the government’s online services are expected to be on par with that of commercial corporations in terms of ease-of-use and intelligence.
It is apparent that Hong Kong’s business environment and ideal location is conducive to the development of revolutionary AI technologies, and this will be spurred on by the new HKSTP Technology Validation Platform.
This year’s floods in the eastern state of Bihar affected over 8.1 million people in July. According to the Bihar Disaster Management Department (BDMD), the ongoing floods inundated 16 districts across the state and hit 1,310 village councils. For better crisis management, the Bihar government started deploying an artificial intelligence-based early warning system and a mathematical modelling system.
According to a news report, the technologies have helped various districts in the state carry out the evacuation of people and set up relief camps. The systems have also helped reduce the death toll. Bihar Water Resources Minister, Sanjay Kumar Jha, told reporters that the government has taken preventive steps to minimise damage from floods using the latest technology. It has been able to alert the district magistrates of north Bihar about heavy rains 72 hours in advance.
The use of the early warning system has led to fewer flood-related deaths as people can be better prepared. The district administrations and residents are getting adequate time to move to safer places, carrying out their maximum belongings and livestock. This year, Bihar started using the services of its Flood Management Improvement Support Centre (FMISC). The centre has a newly-established mathematical modelling centre (MMC) under the centre of excellence for water resources, research, and development.
The centre has developed a flood forecast model with a 72-hour lead time for rivers like Gandak, Bagmati-Adhwara, Kamala, Kosi, and Mahananda, which originate in Nepal. The centre also assesses the Ganga starting between Buxar and Kahalgaon. With mathematical modelling, AI, a personal locator beacon, and machine learning (ML), the centre assesses precipitation, humidity, temperature, and the last seven days’ hydrological data and three days’ forecasted hydrological data to provide a weather forecast, the report noted.
Earlier this month, the India Meteorological Department (IMD) announced its plan to use AI in weather forecasting, especially for issuing nowcasts, which can help improve 3-6 hours prediction of extreme weather events. IMD Director-General Mrutunjay Mohapatra explained that AI and ML are not as prevalent as in other fields and are relatively new in weather forecasting. Therefore, IMD has invited research groups to study how to use AI to improve weather forecasting. The Ministry of Earth Sciences is evaluating their proposals.
IMD uses different tools like radars and satellite imagery, to issue nowcasts, which provide information on extreme weather events occurring in the next 3-6 hours. IMD issues forecasts for extreme weather events like thunderstorms and dust storms. Unlike cyclones, predictions of thunderstorms, which also bring lightning, squall, and heavy rains, are more difficult as the extreme weather events develop and dissipate in a very short period.
Last month, over 160 people died due to lightning alone in Uttar Pradesh and Bihar. The IMD wants to better the nowcast predictions through AI and ML, which will help understanding past weather models and speed up decision-making. Technology to accurately predict and anticipate a crisis is not just necessary for governments but businesses as well. According to critical event management experts, Everbridge, when an external risk threatens operations or a supply chain, the more time there is to anticipate the threat, the more options are available to mitigate or even avoid the disruption.
For businesses, having an integrated picture of external threats and events overlaid with an organisation’s people, assets, and supply routes, along with other contextual information to enable a timely assessment and operational response is mandatory in today’s global economy.
In continuation of the Virtual Breakfast Insight series in collaboration with SAS, OpenGov Asia delivered another enlightening event on 18 August 2020: Powering Next Generation Fraud Prevention and security intelligence through Advanced analytics and AI.
The audience for this event comprised of delegates from the financial sector industry based in the Philippines with full house attendance.
The session was opened by a welcome address and round of introductions by Mohit Sagar, Group Managing director and Editor-in-Chief at OpenGov Asia.
Mohit also spoke about increased cyber risk and fraud that arose during the pandemic and with the new norm of working.
Being aware of the increased vulnerability of the user in cyberspace the bad actors are always on the lookout to capitalise on this situation.
He emphasised the importance of fraud prevention and the need to integrate technology in that process.
Gone are the days when human eyeballing used to suffice, as the bad actors in cyberspace are becoming more and more sophisticated. He concluded his presentation by advising the delegates to collaborate with partners who champion cyber risk and fraud prevention.
Making it inevitable for users and organisations to keep themselves up-to-date with the technology solutions available in the area and deploying them.
In the same vein, he warned the audience about the challenges of creating a risk management system of their own during these times.
After Mohit, Ryan Guadalquiver, Country Manager, SAS Philippines delivered are thought-provoking introductory address.
Ryan began by emphasising how digital adoption by individuals and organisations has gone up tremendously since the pandemic hit the world.
People’s engagement with e-commerce and e-banking has gone up spectacularly; this, however, has also increased the risk of financial fraud dramatically.
This is because the online security systems have not undergone updates to tackle the huge volumes of online transactions.
Therefore, it is critical for organisations to use analytics, not just for managing their digital interactions, but for preventing the risk of fraud by embedding it in all their compliance protocols and in their working.
He shared in detail how SAS offerings, with its singular focus on analytics, can help with that. To further make it relevant for the audience, he enumerated the specific areas in SAS’s banking value chain – retail and private banking, customer experience, capital markets & investments and wealth and Insurance.
He concluded by delving specifically into the fraud and security intelligence solution and how it could help the delegates.
After Ryan, Ahmed Drissi, the anti-money laundering lead (APAC) for SAS spoke about AI and ML in the context of anti-money laundering.
He began by talking about the challenges in using traditional AML solutions as they are not up to date with the high volume of online transactions. He then explained how their solutions can help overcome these challenges.
Ahmed shared that other stakeholders in the industries like regulators also recognise the benefits of using AI and ML in anti-money laundering initiatives and are encouraging it now.
He supported this by sharing examples of financial regulatory authorities in the USA, UK, and Singapore have started recommending the use of AI and ML in the context of anti-money laundering.
He further went on to share a graphic representation of the three phases of AI and ML adoption cycle as done by large global and regional banks. The three phases are Innovation, Adoption and Maturity.
This representation helped explain how the solution helped organisations improve operational efficiency and reduce false positives. He finally put out the SAS offering or the Financial Crimes Analytics solution that helps monitor and prevent fraud incidence in organisations.
He also enumerated various AI and ML use cases in AML that include entity resolution, customer segmentation, post alert scoring, model detection, tuning and optimisation.
After Ahmed, Dr. David Hardoon, Senior Advisor – Data and Artificial Intelligence, Union Bank highlighted the power of using advanced tech like AI and ML. Its efficacy lies in its ability to go beyond a single representation of an individual or an entity rendering a better understanding of fraud risk.
He emphasised the fact that using tech in regulation and security is something non-negotiable and validated it with a recent case study from Germany.
To further stress his point, he shared how the supervisors and the regulators of the industry are also implementing and encouraging the use of new tech.
He concluded by pointing at the significant paradigm shift in organisations’ approach in handling fraud incidences from initiating action after something irregular has been detected to taking actions to prevent the fraud risk.
David highlighted that this is a big step for organisation on their journey towards having a robust risk and fraud management system.
After David’s powerful session, the session moved to a more interactive time with the polling questions for the delegates.
On the first question of challenges faced during the AML investigation process, the participants gave a very mixed response with almost 31% choosing high rates of false positives.
A technology head from a major bank shared that for their organisation time was is the biggest challenge. They need more time in not just deploying the tech, but also in upskilling their workforce.
On the next question of where you are on your current AML journey, a majority of the audience voted for “we are looking for a technology that can complement our existing AML journey” (57%).
On this, another senior delegate shared that he voted for the above-mentioned option because they are always looking to improve as a bank and are open to adopting new technologies. They are still looking for a technology that best compliments their existing AML solution.
On the final question of does your organisation have a real-time fraud detection, prevention, and monitoring solution that is working together with an AML solution, more than half of the participants (54%) voted for having a fraud system but separate from the AML solution.
One of the delegates reflected that their organisation currently has a fraud system and an AML system but they are both separate from each other. However, he also shared that they are in the process of stitching it together on a singular platform in the near future.
After the polling session, Ahmed once again took over to conclude the session with closing remarks. He thanked all the delegates for their time and participation in the event. He also said that adopting tech in regulation requires a laser light focus and that is something SAS champions. Ahmed encouraged delegates to engage and collaborate with them if they are working towards it.
The National Institution for Transforming India (NITI Aayog) in collaboration with the National Association of Software and Service Companies (NASSCOM) has launched the ATL AI Step-Up Module for students, which will drive artificial intelligence (AI) education and innovation across the country. The initiative was launched after the AI project, ATL AI Modules by the Atal Innovation Mission.
According to a press release, this module is the next step in bringing AI to Indian classrooms. The AI Step-up Module provides a comprehensive set of learn-it-yourself advanced modules to those who want to expand their knowledge base after becoming familiar with the basics of the AI technology, through the AI base module.
With this new launch, through hands-on projects and activities, the step-up module encourages a deeper understanding of AI, which can be applied in the real world. The module is designed in an attractive graphical manner that is comprehensible for all students belonging to rural and urban areas, the release noted. Furthermore, the step-up module needs no previous knowledge and introduces the concepts to students from the basics using interactive tools and activities to keep their attention undivided.
Speaking on the importance of introducing AI to school students, the CEO of NITI Aayog, Amitabh Kant, said that the AI step-up module is the future of this country as it targets the youth, which is path-breaking. He urged young India to take this opportunity positively and explore the module to create valuable solutions that would pave way for the country to become Atmanirbhar Bharat.
During the virtual launch, the Mission Director of Atal Innovation Mission, R. Ramanan, said that this first-ever industry-government-academia initiative has received many responses from students by the introduction of the base module. Now, AIM, NITI Aayog, and NASSCOM are proud to launch its step-up module. Inputs from leading academic organisations including Institutes of Information Technology (IITs) have contributed to the development of these modules.
The base module was specifically designed considering students as young as 12 years old, with no background in AI education to ignite curiosity on AI in their young minds and to contribute to the ecosystem of innovation. The step-up module has been designed and presented to involve young students across the country to induce inclusive learning and to empower youngsters of the country to create AI integrated innovations, he added.
The NASSCOM President, Debjani Ghosh, explained that the rapid advancement of technology, such as AI and robotics, has penetrated all industries, including education. As the world transforms with innovation, it is hearting to see how the youth of the country are acquiring great fondness towards the digital method of studying and adopting AI in it. She added that by introducing digital literacy, coding, and computational thinking, these modules can empower young people to meaningfully interact with AI-based technologies and bolster learning. Skills such as logical thinking, critical thinking and problem-solving skills are going to be the most important skills for success in professional life in the coming decade.
The module is a directed step by the government of India to a workforce that is aware of AI and can work with advanced technologies.
OpenGovLive! Virtual Breakfast Insight
Powering Smarter and Resilient Government with Advanced Analytics and AI