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【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

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Testing Seat Contact Components AI Intelligent Flaw Detection

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【解決方案】佐翼科技無人機導入高爾夫球場域 可節省一半人力
Droxo Tech Applies Drones in Golf Courses to Reduce Manpower by Half

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analysis and testing will be carried out in the current stage In the future, large-scale technology implementation and verification will be carried out to set an example for applying drones to golf courses Using AI drones to fertilize and spray pesticides can reduce the manpower required by half The traditional way of maintaining the turf in golf courses is to carry spray buckets or drive spraying vehicles to spray areas one by one "Domestic golf courses began to plant ultra-dwarf Bermuda grass in 2001 This grass species prefers a cool climate and is not suitable for Taiwan's hot and humid weather" Droxo Techrsquos CEO further pointed out that to prevent turf from pests and diseases, pesticide spraying is necessary For an 18-hole golf course, it is equivalent to spraying pesticides once a week, and the T-ground and fairways are sprayed every two months For golf courses, spraying pesticides is time-consuming and labor-intensive It is important to note that large-scale spraying will increase the risk of personnel poisoning and increase the amount of pesticide used Benefits of applying agricultural drones to golf courses According to Droxo Techrsquos research, golf course pests include Spodoptera litura, which comes out at night to look for food, so pesticide spraying must be carried out in the evening According to the traditional method, pesticide spraying requires two vehicles and three personnel for a total of 45 hours If AI drones are used for fertilizing and pesticide spraying, it only takes one operator to spray 08 hectares of land in 20 minutes, saving about two-thirds of the manpower and reducing operating costs by about 30 Using AI drones to fertilize and spray pesticides on golf courses can reduce the manpower required by half In addition to the significant benefits of using agricultural drones for golf course turf maintenance, Droxo Tech also specially introduced AI multispectral image recognition for NDVI Normalized Difference Vegetation Index analysis "The so-called multispectral is to direct light with different wavelengths on the turf, and the reflected images are collected for analysis" Droxo Tech CEO Liu continued to explain that each plant absorbs light with different wavelengths, so multispectral imaging can determine the growth status of grass species At the same time, combined with AI image recognition, the distribution of pests and diseases can be accurately detected, and the amount of pesticide used is determined on this basis Cross-domain collaboration to build a multi-source turf image databasenbsp Using AI multispectral image recognition technology, Droxo Tech will collect visible light, multispectral, thermal images, and hyperspectral images to establish a multi-source turf image database to fully understand the growth cycle of Bermuda grass Droxo Tech has accumulated rich experience in agricultural AI drone pesticide spraying , but there are still many problems that need to be overcome to implement AI solutions in golf courses For example, it is necessary to establish a new pesticide spraying model and test flight methods, especially the application of multispectral image recognition PoC is not difficult, but actual implementation requires more test evidence, repeated inferences, and collaboration with plant experts This part must rely on the cross-domain integration of legal entities such as the Institute for Information Technology III, gathering more fields for verification, and creating a paradigm before it can be more widely adopted by golf courses There are not many international cases on the application of AI drones in golf courses During the verification process, it is not yet known whether it can be quickly copied to the next golf course However, Droxo Tech CEO Liu believes that through cross-domain collaboration, clearly defining the problems and listing them one by one, supply and demand parties can reach a consensus, propose solutions to each problem, and seek cooperation with internal and external resources Only then will we be able to gradually achieve the goal of making golf courses smarter and smoothly assist the industry with transformation Zuoyi Technology's CEO, Liu Junlin 「Translated content is generated by ChatGPT and is for reference only Translation date:2024-05-19」

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[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」