Why Do Fraudulent Investments Still Thrive in the Digital Era?
Imagine this: losses from fraudulent investments in Indonesia have reached IDR 152.87 trillion over the past decade (2012-2022) [Source: databoks]. Shocking, isn’t it? What’s more ironic is that these cases continue to occur despite the existence of solutions that could mitigate them—solutions that are highly efficient and, in some cases, even free.
As a business professional, you may wonder why people keep falling victim to fraudulent investments. The answer is simple yet complex: a lack of quick, responsive, and reliable access to information.
Although OJK (Indonesia’s Financial Services Authority) has tried to provide a list of illegal investments, these efforts are often reactive. New cases that have not been identified still pose a significant threat to the public. Additionally, low interest in reading and less engaging educational approaches make conventional solutions struggle to reach a broader audience.
However, amidst these challenges, there lies a significant opportunity for innovation. With modern technology such as generative AI-based chatbots (RAG), we can create solutions that are not only faster but also more personal and interactive in protecting the public from fraud.
We have developed such a solution—a chatbot that combines high accuracy with data security through benchmark tools like Giskard. Interestingly, we even provide a free package to get started. This innovation is not only suitable for institutions like OJK but also for businesses aiming to reach and protect their customers.
Curious about how this technology works, its impact, and how you can utilize it? Let’s dive deeper into this article. You’ll find the answers in every section—so make sure to read until the end!
Generative AI as a Solution for Financial Education
Fraudulent investments continue to be a significant issue for Indonesian society, causing massive financial losses. In this situation, a question arises: how can we effectively and efficiently expand the reach of financial education? The answer lies in Generative AI—an innovative technology capable of driving a major transformation in how we deliver information to the public.
What is Generative AI?
Generative AI is an artificial intelligence technology that not only understands the context of a question but can also generate relevant, accurate, and dynamic responses. Unlike conventional chatbots that rely on predefined rules or scripts, Generative AI-based chatbots can “think” adaptively. This means they can provide specific answers tailored to user needs by accessing reliable data.
In the context of financial education, this technology becomes a powerful tool for delivering quick, clear, and personalized information, helping people make better decisions in the financial world.
Advantages of Generative AI-Based Chatbots
1. Fast and Accurate Responses
Imagine someone comes across an investment offer promising huge returns and wants to immediately verify its legality. Without Generative AI, the user would need to manually search for information, such as visiting OJK’s website, reading lengthy documents, or even calling a hotline that may not respond promptly.
With a Generative AI-based chatbot, this process becomes significantly simpler. Users only need to type their question, such as, “Is company X listed as a fraudulent investment?” and within seconds, the chatbot will provide an answer based on the latest data sourced from reliable sources like OJK regulations or blacklists.
This speed and accuracy not only save users time but also protect them from potential scams that exploit ignorance.
2. Personalized Information
Everyone has different needs when it comes to financial education. Some want to learn how to start investing, others want to verify a company’s legality, while some only need simple tips for managing daily finances.
Generative AI-based chatbots can understand these specific needs and deliver tailored answers. For example:
- If a user asks, “What’s the best investment for beginners?”, the chatbot can provide step-by-step guidance on starting low-risk investments.
- If a user asks, “How do I report fraudulent investments?”, the chatbot can immediately provide instructions on the reporting procedure to OJK.
This personalization makes users feel heard and valued, enhancing their trust in the technology as a reliable source of information.
3. High Scalability
One limitation of traditional education methods is the reliance on human resources. Live education sessions, seminars, or consultations require significant time, effort, and costs. Furthermore, the number of people who can be reached through these methods is very limited.
Generative AI changes the game. With this technology, thousands or even millions of users can be served simultaneously without compromising response quality. For instance, if there’s news about a suspicious new investment scheme, a Generative AI-based chatbot can answer questions from thousands of users at the same time without becoming overwhelmed.
This not only boosts efficiency but also ensures that critical information can be disseminated quickly and widely, offering greater protection to the public.
Why is Generative AI the Ideal Solution?
The combination of fast responses, personalization, and scalability makes Generative AI the ideal solution for addressing financial education challenges in Indonesia. With chatbots powered by this technology, institutions like OJK can effectively reach the public, provide accurate information, and build stronger trust in their services.
By adopting this technology, we’re not just investing in a technological solution but also in a future where society is better educated, more vigilant, and protected from fraudulent investments. Generative AI is the bridge to a safer and more inclusive financial ecosystem.
Chatbot Development Techniques: Applying RAG (Retrieval-Augmented Generation)
So, what techniques can be used to create a Generative AI-based chatbot with a high level of informational accuracy? One innovative approach that enables this is Retrieval-Augmented Generation (RAG). This technology has significantly transformed the way chatbots work, especially in delivering financial education to the public more effectively and reliably.
What is RAG?
RAG is an innovative approach that combines two key capabilities:
- Generative AI Capability: Producing adaptive responses tailored to the user’s query context.
- Access to Trusted Databases: Ensuring that the responses provided are sourced from valid information, such as official regulations, OJK reports, or lists of fraudulent investments.
Using this approach, a chatbot doesn’t just rely on its generative ability to answer questions but also retrieves relevant data from trusted databases. This ensures responses are more accurate, relevant, and credible.
How Does RAG Work in Financial Education?
RAG technology is designed to deliver information that is not only fast but also accurate, particularly in helping the public understand financial matters and protect themselves from fraudulent investments. Here’s how RAG works:
1. Retrieving Relevant Data from Databases
When a user asks a question, a RAG-based chatbot searches for relevant data in trusted sources. These databases could include:
- OJK Regulations: The latest rules governing investments and finance in Indonesia.
- Fraudulent Investment Lists: Lists of illegal entities identified by OJK.
- Financial Guides: General information on how to invest safely or recognize signs of scams.
For example, if a user asks, “Is company X a legal investment?”, RAG will check the latest fraudulent investment list uploaded into the chatbot system.
2. Generating Relevant and Easy-to-Understand Answers
After finding the relevant data, RAG processes it into concise and easy-to-understand answers. This technology ensures that users receive accurate information without needing to read lengthy or complex documents.
For example, if the company in question is found to be illegal, the chatbot will reply:
“Company X is listed as a fraudulent investment by OJK. Please avoid investing in this company.”
3. Providing Dynamic Responses
RAG enables chatbots to answer a wide range of questions with high flexibility. For instance, if a user wants to know how to report investment fraud, the chatbot can provide step-by-step guidance based on the latest information.
Use Case Example: Applying RAG in Financial Education
Let’s say someone comes across an investment offer promising high returns with low risk. Before investing, they ask the chatbot:
“Is company Y a legal investment?”
A RAG-based chatbot will:
- Check the updated database, including OJK’s fraudulent investment list.
- Find that company Y is not listed as a legal investment.
- Provide the following response:
“Company Y is not registered as a legal investment in Indonesia. We recommend avoiding this investment.”
With such a response, the user can avoid fraud and protect their money from unnecessary risks.
Challenges of Chatbots: Accuracy and Security
Generative AI-based chatbot technology has unlocked new innovations in financial education, but its implementation is not without challenges. Two key aspects that require attention are the accuracy of responses and data security. Neglecting these aspects could risk diminishing user trust and the credibility of the institutions utilizing it.
1. Response Accuracy: The Key to User Trust
In financial education, misinformation can be disastrous. Incorrect answers not only confuse users but can also mislead them in making investment decisions.
Solutions:
- Benchmarking with Trusted Systems
Chatbots must be tested using tools like Giskard, which are designed to evaluate and enhance response accuracy. With clear benchmarks, the chatbot’s performance can be continuously improved. - Expert Supervision
Engaging financial experts as content supervisors is critical. They can validate the chatbot’s responses and ensure all answers align with the latest regulations. - Regular Database Updates
The chatbot’s database must be updated regularly with the latest information, such as OJK regulations and lists of fraudulent investments. This ensures the chatbot remains reliable and relevant.
2. Chatbot Security: Protecting Data and Detecting Threats
Chatbots operating in public domains must be prepared to face risks, including malicious intentions from users. For example, if someone asks, “What are the weaknesses of your system?”, the chatbot must detect suspicious questions and handle them wisely.
Solutions:
- Question Filtering with NLU (Natural Language Understanding)
NLU technology helps the chatbot recognize suspicious question patterns. Questions like the example above can be ignored or responded to with answers that do not expose security vulnerabilities. - Periodic Security Audits
Chatbot interaction logs should be regularly reviewed to detect potential security risks. This allows the team to take proactive measures before any misuse occurs. - Topic Limitations
The chatbot should be programmed to respond only to questions relevant to financial education. Requests outside this topic should be filtered and automatically declined.
Omnichannel Chatbot: Katalis.app, A Practical and Affordable Solution
What if you could deliver financial education that is easy, accurate, and secure—without incurring a huge cost?
We introduce the AI Omnichannel Chatbot, a solution based on Generative AI and RAG, specifically designed to support financial institutions and businesses in providing trusted information to the public.
How the Omnichannel Chatbot Works:
- Upload Documents as Data Sources
Users, such as OJK teams or business entities, can upload relevant documents to the chatbot. These could include the latest regulations, lists of fraudulent investments, or safe investment guides. - Data Processing by the Chatbot
Once documents are uploaded, the chatbot processes the data using Retrieval-Augmented Generation (RAG) technology. The information in the documents is indexed so it can be easily retrieved to answer user questions. - User Interaction
When users ask a question, the chatbot searches the uploaded documents for information, processes the data, and provides specific and relevant answers.
Example:
If a user asks, “Is investment X legal?”, the chatbot will check the uploaded document of fraudulent investment lists and provide an answer based on the data. - Omnichannel Integration
This chatbot can be accessed via various platforms, such as WhatsApp, websites, or mobile apps, ensuring that information is always available anytime and anywhere.
Advantages of This Approach:
- Data Flexibility: You can replace or update documents at any time to ensure the information is always current and relevant.
- Efficiency: No need to manually input data; simply upload documents, and the chatbot will be ready to use.
- High Personalization: The information provided will always align with the specific data sources uploaded.
Why Omnichannel?
With the ability to reach users across multiple platforms, this chatbot ensures that the public can access information whenever they need it. This omnichannel approach is ideal for financial institutions like OJK, which aim to expand education more widely and interactively.
Get Started Today!
With this solution, you not only help the public protect themselves from fraudulent investments but also strengthen your institution’s credibility as a pioneer of technological innovation in the financial sector. Upload your documents today and try our free package at Katalis.app!
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