Challenges

We have a working SaaS solution that fetches data from various social channels, websites, deep web to do the following things:

1. Fetch Social Media Data, Posts
2. Extract the Data
3. Understand the Sentiment
4. Build real-time black list fraudsters data
5. Derive Insights on a monthly basis
6. Update the Risk Scoring Algorithm

This solution provides real-time updated black lists and Risk Scoring API where any fintech, payment app, the bank can integrate our solution to pre-empt digital frauds at the stage of onboarding, payment transaction, etc..,

Since the nature of the digital identities in the fraud industry has a pattern across industries, we scan the data from various industries like Marketplaces, Payment Apps, Government media handles, Others to understand the sentiment of each and every post and extract value from it.

Primary target

Which group does your product/service primarily target?

Description of Innovation

Critical Success Factors:

1. Fraud Identification - Upto 20% reduction in frauds
2. Ease of Implementation - Less than 48 hours
3. Faster Response Time - Less than 1 second
4. Quick Feedback Loop - Customer User Group

We are different from our competitors based on the following:

1. Cross-industry fraud social scanning
2. Custom built fraud analyzer
3. Custom built fraud data extraction modules
4. CUG Support
5. Technology built for scale TrustCheckr is a Cross-industry fraud insights platform. We do AI-based social scanning to understand the sentiment of the posts in real-time, extract key fraudsters info like name, email, IP etc..,

Results

First of all the common public will be the super beneficial segment using TrustCheckr solutions. There are lots of frauds, scams happening in today's digital world, this number is going to increase with the emphasis on digitization in the BFSI sector. Although the modus operandi changes based on the flavor of the season like COVID, Oxygen, etc.., At the core, phone number, email address, QR would remain the same. Hence the digital identity risk scoring system of TrustCheckr is going to change the game of identification of frauds in real-time in every changing digital world.

Another major benefit is cross-industry fraud data sets. The intent of the digital identity is very important especially for the lending industry. Since TrustCheckr focuses on the cross-industry fraud insight, there would be a direct effect of NPAs and reduction of NPAs and optimizing the funnel costs.

TrustCheckr publishes reports on new ways on how fraudsters are operating. This can be used for Awareness programs from RBI, Banks, Fintech, and the likes. One example report - https://techgraph.co/tech/trustcheckr-41-of-digital-fraud-accounted-in-eastern-india/

Lessons Learnt

Data Scanning Modules - Official APIs of social channels, public data crawlers
Data Extraction Modules - OCR, Data Categorization
Sentiment Analysis - NLP, Text Analysis, Image Sentiment, Fraud Sentiment
AI Algorithms to identify Opportunities, Threats, etc..,
Cloud - AWS, Others - NodeJS, React, Mongo, BigQuery, Python and more...

These above modules are very important to replicate the product.

The standards and regulations that TrustChekr follows in order to keep customer data secure, private, and safe from any damages and breaches. This applies to all the customer data, their data which is accessed and shared based on the search queries obtained by the API services and stored in the TrustCheckr premises.

The current TrustCheckr system has been data protected using the AES 192 encryption techniques for the “Data at Rest” and TLS for the “Data in Transit” The data which gets into the database is encrypted and any external sources cannot access using any techniques.

The data compliance issues like theft, loss of data, etc., are totally governed by the TrustCheckr system by ensuring data compliance and protection by using the data protection tools.

Data Legality

The data legality like important customer data records, contact info. Attorney information, law information, parties' information have been stored under the company's data security policies.

Purpose – The data is used only for the particular purpose or intent to use.
Consent – The data of the particular customer shall not be shared with others without the user/customer consent
Security – The collected data is highly secured