The digital ecosystem has its vulnerability and is battling with threats in a manner never seen before, particularly in the banking, financial services, and insurance (BFSI) sectors. As banking systems have moved online, so has fraud, with fraudsters developing their digital methods of stealing customers’ identities and gaining access to their accounts. There comes a need for risk monitoring mechanisms that can create a safer digital ecosystem for both banks and their customers.
The Reserve Bank of India (RBI) reported over 13,000 bank fraud cases across India, with a total value of ₹302 billion.
Risk Monitoring Challenges in the BFSI Industry
Identifying Synthetic Identities:
Artificially created identities pose a significant risk. Fraudsters manipulate data to create synthetic profiles, making detection challenging.
Prevent Account Takeover:
Unauthorized access to customer accounts threatens financial stability. Identity scan helps prevent account takeover by validating user identities during transactions.
Transaction Laundering Protection:
Concealing the origins of illicit funds is a persistent issue. Effective risk monitoring can flag suspicious transactions.
Customer Validation:
Fraudsters submit falsified documents during transactions. Identity scans verify the legitimacy of the submitted information.
What can the BFSI industry do to Monitor Risk with Identity Scan?
User information is mapped with the mFilterIt repository and open-web sources. This involves using a unique identifier as a mapping attribute and integrating data signals and public information (such as mobile numbers and email IDs) through APIs.
The result of this data gathering and mapping process is available to the banks. It is based on risk-scoring of attributes and identities linked to the user. The bank accesses the mFilterIt database using an API.
Data Enrichment for Risk Profiling
With advanced AI & ML driven technology, we can run a scan across web & mF repositories to pull out data, categorize, interlink, and enrich the data based on the inputs asked. The scanning capabilities can correlate the available public information from open sources and databases to identify a genuine profile from a fraudulent one. As per the risk scores based on a pre-defined rule engine, the report is shared with the brand to decide the next action steps depending on the risk scoring.
Enhance Efficiencies
Opens source intelligence helps validate the authenticity of customers and automate business processes such as credit card or loan application background verification. Check your loan disbursal and credit card approval decisions, data enrichment, validate with social attributes with database linkages across platforms, gather social proofs for tracing absconding defaulters, only relevant and latest, monitor & track social engagements to ensure they get the best of bank services and do not post negative reviews.
Protection from Financial Fraud
With transaction laundering protection solution banks can safeguard their reputation by identifying UPI frauds, impersonations, mule accounts, and fraudsters using their services to commit tax frauds and scams. Ai-ML-driven tech and OSINT help banks identify illicit activities that damage banks’ reputations and lead to trust erosion.
Benefits of Risk Monitoring with Identity Scan
Risk Profiling on Social Parameters:
mFilterIt‘s Identity fraud protection solution analyses user profile attributes. It uses AI-ML-driven risk assessment and open-source intelligence (OSINT) to analyze social profiles. This aids clients in comprehending the dangers connected to users.
Validate with repository, open and dark webs Scan:
Using AI and ML techniques, the program searches the internet and mFilterIt large database for customer profiling. It verifies the identity of customers while adhering to privacy laws and policies.
Prompt Action based on reports, alerts, and Insights:
Detailed reports with risk assessments and recommendations for next steps are sent to clients. Which helps them to take further action on their end.
For instance, major Indian banks improved card issuance and credit limit decisions, based on open-source intelligence. It reduced the possibilities of credit risk, up to approx. 14 %. This demonstrates how robust identity verification processes can provide effective results.
The BFSI sector must counter the digital threats with profile risk assessment and proactive monitoring and understand related risks increasingly affecting the BFSI industry and tarnishing its brand reputation.
Conclusion
The digital payment ecosystem is plagued with financial frauds that question the integrity of the BFSI industry. The mFilterIt Identity fraud protection solution, powered with AI-ML tech, proprietary Open-Source Intelligence (OSINT), data harvesters, and an extensive database repository enables brands to safeguard their brand integrity. Identity verification using social risk parameters creates a safer digital ecosystem where all stakeholders can make informed decisions based on reliable data.
Get in touch to learn more about the Identity Scan in BFSI
