:::

【2020 Application Example】 The Lawsnote compliance system uses AI technology to automate the compliance risk assessment (CRA) process and improve the compliance efficiency of companies

Trends in financial regulation

As the world pays greater attention to regulatory supervision, various fields are facing increasing compliance costs. If we were to ask what was the fastest growing field in 2020? I believe many people will think it is regulation!

The trend of strict supervision has been the most severe in the financial industry. Supervisory agencies In Taiwan, including the Financial Supervisory Commission, have imposed growingly strict supervision requirements on the financial industry, as well as heavier fines. In response to these supervisory measures, the financial industry gradually implemented new internal control and internal audit systems for compliance a few years ago, such as the assessment of regulatory risks, business units appointing compliance managers as the first line of defense, and compliance self-assessment system.

Current manual compliance process of compliance personnel

However, there is a plethora of financial-related laws and regulations, and business units have a large number of complex business manuals. Therefore, many compliance personnel of financial institutions must spend a lot of time on tedious and highly repetitive comparisons of internal and external regulations, in order to help companies avoid risks or fines due to not proposing response measures in their internal regulations when laws are amended.

Compliance staff spent a lot of time processing Changes in laws

▲Compliance personnel spend a lot of time dealing with regulatory changes

Lawsnote Compliance System Solution

As Taiwan's leading legal technology solutions provider, Lawsnote received many requests from corporate customers for a compliance system, and began to look into solutions for applying AI to compliance systems. It thus developed the Lawsnote RegTech compliance system for compliance personnel to automate parts of their work process, reducing the tedious and repetitive work of compliance personnel.

Lawsnote will adjust legal changes and internal regulations Automation

▲Lawsnote automates regulatory changes and internal regulatory adjustments

A Regulatory database, search, and notification of regulatory changes

As the basis of the RegTech system, the compliance process is triggered by "regulations", so it is necessary to have a "complete" and "real-time" regulatory database and regulatory update mechanism for specific fields.

However, regulations are not limited to "laws" enacted by the Legislative Yuan, but also include "administrative rules" and "legal orders" enacted by administrative agencies authorized by law, as well as "administrative interpretations" used to interpret regulations. These are all considered regulations that the compliance system must comply with.

There is currently no unified data source for these regulatory data. Except for the Laws & Regulations Database of the Republic of China (Taiwan), many regulations are scattered on independent webpages for regulations on the websites of different agencies, organizations, or associations, making the cost of collecting complete regulations very high.

Since laws and regulations will be amended, new administrative letters and interpretations will be issued or old ones abolished, updating regulatory changes is also a big problem. Even if complete laws and regulations are collected once, failure to continuously monitor changes in laws, regulations, and administrative letters and interpretations will also create a gap in compliance.

As a professional legal search engine, Lawsnote has a complete database of regulations and interpretations, and can send notices of regulatory changes required by various fields in response to the needs of compliance systems.

B1. Internal regulations database and search

Internal management by companies through regulations are called "internal regulations." General types of internal regulations include company internal regulations, standard operating procedures (SOPs), and business instruction manuals. Depending on the intensity of industry-specific supervision, the number and density of company internal regulations will vary depending on the industry.

In industries with high supervisory density, the number of internal regulations sometimes reaches thousands or even tens of thousands. With such a huge number of internal regulations, paper or simple filing systems can no longer meet the internal needs of enterprises. The process of searching for and complying with internal regulations might require a significant amount of time and personnel costs if an internal regulations database and search engine are not establish.

Lawsnote has Taiwan's most powerful legal information search engine, patent search technology, and uses AI to optimize its sorting algorithm. It can establish an "internal regulations database"for internal data, such as company internal regulations, SOPs, and instruction manuals, and applies search engine technology to the internal regulations database, achieving a fast, complete, and easy-to-use internal regulations database and search engine.

B2. <Regulations – Internal Regulations> Article-to-Article Linking Mechanism

When regulations are revised, the company's internal regulations must also be inspected and adjusted accordingly.

The company's internal regulation inspection procedures may be initiated by compliance personnel based on regulatory amendments, or may be initiated by the compliance officer of the business unit (the first line of defense), and then reviewed by compliance personnel (the second line of defense). However, regardless of which unit initiates it, the difficulty lies in finding the article of internal regulations that correspond to the amended article of the law to determine whether amendments are necessary.

Due to the large number of internal regulations, complicated terms, and the different forms of business involved, if internal regulations must be reviewed every time laws and regulations are revised, it will consume a huge amount of time. Therefore, compliance personnel usually rely heavily on experience and aim to minimize risk within limited time.

Moreover, due to the way internal regulations are written, often using different methods to significantly rewrite and break down laws and regulations, making comparison very difficult for programs. If the existing program is used to compare internal and external regulations, many internal regulations cannot be effectively determined.

After research and testing, Lawsnote designed 3 AI algorithms and 4 rule-base algorithms for cross-comparison, which can establish article-to-article links between thousands of regulations and company internal regulations, helping compliance personnel to immediately determine the necessity of revisions to internal regulations when regulations are revised, significantly saving review time and reducing compliance and internal control risks.

C. Internal control and internal audit self-assessment process for compliance

In order to ensure that the compliance officer of business units properly carry out the compliance process, some companies will implement mechanisms such as compliance self-assessment and compliance education, and require the compliance officer of business units to conduct self-assessment of internal control and internal audit processes and review existing risks.

Compliance personnel or auditors must summarize self-assessment results, or prepare a risk matrix to monitor compliance risks and track vulnerabilities.

The Lawsnote RegTech compliance system supports expanded workflow solutions, which can extend the workflow to the compliance self-assessment process, customize the integration of the current system and compliance system, and merge the organizational structure and SSO permission control mechanism to create a one-stop compliance system.

Three core modules of Lawsnote legal compliance system Group

▲Three core modules of the Lawsnote compliance system

Incorporates foreign regulations and is the number one compliance tool for companies

Lawsnote will continue to optimize regulatory text parsing and identification technology. In addition, we will also develop other legal technology application tools and become the number one compliance tool for enterprises with all-inclusive services. In addition to domestic regulations, Lawsnote will also incorporate foreign regulations into the system, so that multinational companies in Taiwan can access information on domestic and foreign regulations.

Lawsnote has always focused on AI applications, data mining, algorithm design, search engines, and workflow optimization in the legal field, and is committed to saving the time of legal professionals through technology.

Recommend Cases

【導入案例】AI嘛會煮咖啡 無人烘豆機靠AI 精準設點與培養忠實客群
AI Can Make Coffee! Autonomous Coffee Roasters Relying on AI for Precise Location Setting and Cultivating Loyal Customers

Have you had your morning coffee yet Over the past decade, Taiwan has gradually formed a coffee drinking culture With the advancement of AI technology, autonomous coffee roasters can now rely on AI for precise location setting while also cultivating a loyal customer base Let's see how this is done According to the International Coffee Organization ICO, Taiwanese consume approximately 285 billion cups of coffee annually, with the coffee market in Taiwan estimated at 80 billion TWD, growing about 20 each year In recent years, the 'drinking coffee' culture in Taiwan has become synonymous with popularity, with coffee being the most frequently chosen daily beverage by 65 of the population Coffee enthusiasts, particularly the more avid ones, are willing to pay more for coffee beans that suit their tastes An increasing number of unmanned drink kiosks have also begun to appear in the Taiwanese beverage market Unmanned coffee beverage shops face difficulties in expanding quickly, primarily due to two major issues one is the appropriateness of customer flow and machine placement locations which still rely on manual analysis the second is penetrating the market of mid to high-end coffee lovers accurately AI resolves two major challenges for autonomous coffee roasters suitable placement and cultivating a loyal customer base To tackle these issues and help autonomous coffee roasters quickly break into the market, Raysharp Electronics intends to implement AI for people flow counting analysis and unfamiliar face recognition These technologies aim to calculate the crowd size at potential roaster locations and classify consumers by gender and age for more precise market analysis They also provide multiple choices for the roasting of raw coffee beans, offering a more customized service tailored to the needs and tastes of professional coffee aficionados with a pack of 'high-quality roasted beans' Since 2018, the rise of unmanned stores has been mainly due to owners wanting to reduce persistently rising rent and personnel costs However, the initial assessment of store locations still requires hourly labor expenses for manual estimation of customer flow, leading to possible miscalculations of both on-site consumers and passerby traffic These inaccuracies may prevent precise real-time analysis of customer flow, or even misguided estimations of operational efficacy after a trial run, thus missing the optimal timing for loss-preventing location retraction Raysharp Electronics introduces autonomous coffee roasters equipped with AI-based people counting analysis and facial recognition Raysharp Electronics combines AI people counting analysis and facial recognition with the coffee trend known as 'black gold', addressing the preferences of numerous coffee connoisseurs in Taiwan who enjoy personally selecting coffee beans at bulk stores and frequenting high-quality grinding cafes or chain coffee shops A new concept for the first autonomous coffee roaster offering choices based on the origin, variety, and roasting methods of coffee beans has emerged AI coffee roasters enhance customer loyalty and materials management efficiency by 20 For the advanced development of autonomous coffee roasters, Raysharp Electronics engineers have equipped the AI NVIDIA development platform on the basis of TCNNFacenet Through AI, tens of thousands of images related to gender and age are used for sample training, allowing even first-time coffee roasting customers to be easily classified using unfamiliar face recognition This gains consumer trust, enhances willingness to use, and allows for recording purchase information and future product recommendations, leading to consumer purchase behavior analysis This information helps owners tailor future material preparation based on consumer preferences for different coffee beans, reducing raw material transportation and storage issues, and improving material management efficiency by 20 Moreover, by placing these autonomous coffee roasters in high-traffic areas, owners can use cameras to capture the crowd and assess whether the machine location has an adequate customer base, quickly analyzing whether to reposition the machines, and more easily targeting the best locations for middle and high-end coffee lovers The unmanned coffee roaster features a professional roasting mode interface, providing options based on the origin and variety of coffee beans, their roasting methods light, medium, deep, and related temperature, wind speed, and timing settings If improvement needs arise during the process, engineers can adjust firmware parameters and also assist in integration with the owner's ordering system Staff members briefly describe the operation of the autonomous coffee roaster 'Black Gold' penetrates deeper into coffee shops, science parks, and commercial buildings through AI This autonomous coffee roaster targets coffee connoisseurs and can be placed in middle to high-end coffee shops to roast more customized coffee beans than those available in bulk stores Upon completing a batch of coffee beans, it immediately provides them to professional technicians within the coffee shops for grinding and manual brewing The remaining roasted beans can also be taken home for brewing and enjoyment It also adds value to coffee shops by better understanding consumer preferences for coffee beans and launching more customer-attracting drink promotions and appropriate inventory management In addition to coffee shops, the autonomous coffee roaster can also utilize AI-based people counting analysis to precisely set up near scientific parks and commercial buildings, offering high-quality coffee beans for office brewing to internal employees with high coffee consumption needs Furthermore, implementing a physical membership system can initiate coffee bean purchase promotions or periodic payment incentives, thus attracting new clients and cultivating existing customer loyalty and retention The operation interface of the smart autonomous coffee roaster「Translated content is generated by ChatGPT and is for reference only Translation date:2024-05-19」

【導入案例】赫銳特科技VCSEL封裝元件瑕疵導入AOI檢測 提升產能效率20
HRT Technology Improves Production Efficiency by 20% Through AOI Detection of Defects in VCSEL Packaging

In 2017, the launch of the iPhone X made 3D sensor technology used in Face ID highly popular, which drove the development of VCSEL, a core component in the 3D sensor module In the detection of defects in incoming packaged VCSEL, the use of AI inference models can solve the industry's issue with low yield and improve reliability to 95 VCSEL technology currently can be used in many applications and various end consumer markets, including robots, mobile devices, surveillance, drones, and ARVR VCSELs are a good solution in applications that require high-speed modulation capabilities, such as cameras and biometrics VCSEL technology has a wide range ofnbsp applications, including in drones Pictured Zoyi Technology's Agricultural Drone VCSEL technology has a wide range of applications, AI technology assists in defect detection HRT Technology stated that the packaged VCSEL market is also facing strong price competition from competitors, and needs to further reduce costs and enhance product competitiveness One of the key problems is the replacement of glass lens with epoxy resin lens The production of traditional glass lenses has high yield, but the cost is higher than that of epoxy resin lenses Due to the cutting process of epoxy resin, the side wall of cutting lines can easily have rough edges, causing it to be oversized The release of stress caused by heat during the mounting process will directly cause the optical lens to break HRT Technology pointed out that the incoming inspection of VCSEL epoxy resin lenses is very important Under the constraints of packaging space, the space for fitting the package and optical lens is limited Moreover, the optical lenses will be confined to a metal frame If the dimensional tolerances are properly controlled, stress release due to heat during mounting can easily cause the optical lens to break, resulting in a yield loss of up to 10 in the VCSEL package reliability verification, resulting in an increase in production costs In order to solve the problems above, HRT Technology hopes to use AI to monitor the size and appearance defects of epoxy resin components in the VCSEL epoxy resin lens incoming stage, verifying whether their dimensions meet specifications, whether the cutting edges are smooth, and whether there are any defects in their appearance Since traditional incoming material inspection requires a rough visual inspection by humans to distinguish the quality The problem of image collection needs to be solved first to successfully collect image data Therefore, HRT Technology first developed an Automated Optical Inspection AOI device, which includes X, Y, Z three-axis motion, high-resolution cameras, and related control software to automatically record images After collecting the image data, opencv aligns the test image and a normal image to determine differences between the two images, and then pixel mapping is used to compare the pixel area to complete initial screening Manual labeling is carried out according to the image classification above, including samples that are normal, have defects in appearance, or have different shape characteristics, and then algorithm training and verification is carried out Residual neural network ResNet or other related algorithms are used for deep learning to identify the quality of lenses Implementation of AOI inspection improves production efficiency by 20 and above Comparing the differences before and after the implementation of AI image inspection, the incoming VCSEL lens inspection before implementation only involved manual inspection of the appearance The lens is packaged on the VCSEL package that has completed die bonding After passing the general light up test, the final reliability test high temperature reflow is performed Failed samples go into the rework process However, after the implementation of AOI inspection, it can screen defective lenses sooner and reduce the cost of subsequent materials input, it can also reduce the need for rework due to failure, improving yield to 95 and above in the reliability verification This is expected to help companies reduce production costs by 10 and increase production efficiency by 20 and above The difference before and after implementing AI image detection HRT Technology pointed out that this technology is an AI application developed based on tiny images It uses deep learning algorithms to identify defects in the images The trained network automatically classifies image data to predetermined categories Defect categories can be determined through reference images, so cumbersome programming is not required In the industrial machine vision environment, deep learning is mainly used for classification tasks in applications, such as inspection of industrial products or identification of parts In the future, with the development of IoT wearable devices and the trend of energy saving, the size of optoelectronic components will continue to shrink This technology can be applied to the detection of defects in the appearance of other tiny optoelectronic components in the future

這是一張圖片。 This is a picture.
[2023 Case Study] AI Steps into Philanthropy: Stylish Tech at Food Banks

Taiwan Food Bank AssociationHereinafter referred to as 'the Association'With the mission of providing food aid, poverty relief, reducing food waste, and building a hunger-free network, there are locations across Taiwan that gather donations from wholesalers, intermediaries, retailers, manufacturers, and even generous individuals These sites also rescue food that would otherwise be discarded, properly allocate and distribute it to needy households, thus aiding local vulnerable families55Food banks at various locations collect daily donations from wholesale stores, intermediaries, retailers, manufacturers, and even benevolent individuals from all over Taiwan These places also rescue about-to-be-discarded edible materials, properly sort them, and distribute to needy households, assisting local vulnerable populations However, each location requires significant human and volunteer resources to manage daily operations using traditional methods of communication with non-profit organizations and donors After receiving donations, these resources are then allocated to needy families or individuals There is a potential issue of uneven distribution of resources due to a lack of digitalization and integrated information management in these processes Warehouse and Transportation Centers and Mini Food Banks Distributing Resources to the Disadvantaged The location under validation by the Kaohsiung Charitable Organizations Association,Hereinafter referred to as 'Kaohsiung Charity' In109year6month24Officially inaugurated Taiwan's first 'Food Bank-Warehouse and Transportation Center' at a location measuring200square meters, enhancing the efficiency of food resource redistribution, proper storage, and management So far, nearly two hundred tons of vegetables and fruits have been saved, serving over a hundred organizations and benefiting over5thousand vulnerable households, and continues to serve19mini food banks, with planned completion across multiple districts in Kaohsiung, distributing food resources to over10ten thousand vulnerable families Kaohsiung Charity 'Food Bank-Warehouse and Transportation Center' in the Dasha Community Photo Source Kaohsiung Charitable Organizations Association Challenges in Labor and Food Resource Management Facing the needs of a large number of economically disadvantaged families, the management of the 'Food Bank-Warehouse and Transportation Center' is particularly critical During procurement, tasks such as sorting, purging, and bookkeeping must be performed, while during shipment, food resource needs suggested by social workers must be followed These activities rely on manual judgment and accumulated experience Many volunteers involved are elderly and have limited physical strength, making warehouse tasks physically demanding and recruitment challenging If a large batch of food resources arrives, space and manpower are consumed in sorting and inventory management, raising concerns about the effective use of resources and turnover rate This highlights the challenge of scaling up food bank services while lacking corresponding labor and material management systems At the same time, food bank resources come from various donations, thus they vary greatly in type, shelf life, standards, and quantity Volunteers at mini food banks, mostly also elderly, must handle multiple responsibilities such as case services, food resource management,resource allocation, and resource development Sometimes they must also explain and accept immediate, large quantities of specific resources, such as adults receiving baby formula 'Food Bank-Warehouse and Transportation Center' Resource Inventory Relies Entirely on Manual Labor Mini Food Bank Volunteers Handle Multiple Responsibilities Photo Source Taiwan Food Bank Association Reducing Scrap Resources60 Increasing Speed of Resource Transfer80 To enhance resource management and ensure effective use of materials, and to address personnel shortages, this field validation case has introduced 'Food Bank Warehouse Resource CollectionAITo advance resource management, ensure effective use of resources, and solve manpower shortages, this validation site has implemented an 'Automated Early Warning Needs Assessment System' for the food bank's warehouse resource gathering The first part involves building a classification model, setting up and collecting warehouse information at the site, andAItraining the model Past sitewarehouse information is collected and stored in a database, allowingAIfor preprocessing, classification, and other tasks At the same time, depending on the dependency conditions of the types of goods as features, algorithms are introduced for computation and modeling, and the data collected is used for retraining, ultimately validating the field and organizing data for the five most common types of goods into training and test datasets as required The second part involves constructing the classification model using AI techniques further use of reinforcement learning constructs the management mechanism for the food bank's warehouse, perfecting the classification of donated goodsRNNTechnical construction of classification models further use of reinforcement learning constructs food bank warehouse management mechanisms, making the classification of donated goods perfectlike white rice, instant drinks, noodles, instant noodles, and canned goodscan then be automatically assigned storage based on storage assignment principles AI Service System Process and Description Source Taiwan Food Bank Association AtAIUnder forecasts, it can optimize the speed of resource transfer and allocation, effectively and accurately match resource donations reducing the loss in the donation process, increase the accuracy of resource distribution, and improve the service rate—the successful donation rate—reducing the waste of resources due to incorrect items, and enabling instant monitoring of food resource stock, ensuring operators can respond quickly to needs, effectively providing resource assistance WithAIthe system's introduction and the establishment of data intelligence, it helps the operations of the warehouse and transportation center, allowing more time for the allocation of donated goods The introduction aims to accelerate the digital service rollout for social welfare organizations, thoroughly addressing the needs of the overall vulnerable segments of society Using the system for resource allocation and dispatching Photo Source Kaohsiung Charitable Organizations Association Following this field validation, it is possible to expand the system to other food bank service pointsAIThe system can also collaborate with more non-profit organizations, public welfare groups, and charitable organizations, expanding 'Food Bank Warehouse Resource CollectionAIAutomated Early Warning Demand Assessment System' application range such as medical supply distribution, helping more organizations manage and distribute more intelligently, reducing resource wastage, and enhancing social welfare 「Translated content is generated by ChatGPT and is for reference only Translation date:2024-12-12」