Solution Specific Offerings
Log Management and Log Correlation
Calculating baseline activity for all collected information in real time and providing prioritized alerts of potential threats even before they occur. Also, analysing data for patterns that may indicate a larger threat.
Real-time intelligence and actionable threat forensics that communicate and learn from each other to combat advanced threats. Intelligent scanning boosts performance and productivity by avoiding scans on known, trusted processes while prioritizing those that appear suspicious.
- Zero-day malware prevention — Stops the majority of unknown malware from the internet, freeing up resources formerly used for endpoint clean-up.
- Full traffic visibility and control — Opens SSL encrypted traffic to uncover hidden threats, cloud application access, and data flow so controls can then be applied to reduce risk.
Adaptive security scanning enabling us to automatically detect and assess new devices and new vulnerabilities the moment they access your network.
Providing integrated policy scanning to help you benchmark your systems against popular standards.
- Protection against all database threat vectors to meet compliance requirements.
- Comprehensive threat protection — Protects even unpatched databases against zero-day threats by blocking attacks that exploit known vulnerabilities and terminating sessions that violate security policies.
KYC/Loan/Bonds Documents Long Term Authenticity Management
Long Term Authenticity Management of KYC Documents using Blockchain Signatures is possible as they never expire and verify the authenticity offline too.
On-Prem Hosted Secured Communicator
Secured Communication between higher management and employees on an on-prem deployed communicator enables highest security standards of no communication/shared data leaving the organization.
Securing Critical Transactions Databases From Tampering
Long Term Authenticity Management of critical databases on which records should never change and should be tamper evident.
Logs Security As Per Compliance
Managing all types of logs and its security, specially the integrity of them is paramount for any BFSI organization as per compliance and keeping them as digital evidences.
Securing Digital Identity
Securing your customer facing application such as websites and business critical applications which may be internal/external from zero-day attacks.
Automated Content Checking
A solution for checking the content on a physical document, to reduce overall time, improve efficiency and establish accuracy over manual efforts of a legal or a credit monitoring back office team for document processing.
Customer Consent Recording / GDPR Solution
To enable nonrepudiation, Blockchain can be the absolute solution by managing/protecting the consents and monitoring the data sharing within and beyond an organization.
Mobile Application Integration
Integration to mobile applications to prove absolute data at the source for back office processing.
Supply Chain Finance
Introducing Blockchain in a multiparty environment can help prove the occurrence of an event and hence help the overall supply chain finance departments to track and trace asset movements.
Blockchain Integration To Existing Applications
Due to its plug and play functionality integrating Blockchain to existing application is extremely easy and requires almost no efforts or certified Blockchain developers.
Reduce financial crimes and parse commercial loan agreements
Big Data improves the accuracy in detecting suspicious transactions. Banks have extended POC and pre-implementation phase. The ML algorithm can detect anomalies in transaction behavior by accessing different features such as products, customers, and risks.
360-degree view of each customer based on how everyone individually uses mobile or online banking, branch banking or other channels.The bank predicts the needs of their customers and understand them better. The team analyzed large volumes of data to identify their customer’s preferred means of communication, such as phone, email, or social media. This valuable information has increased the hit rate of their marketing campaigns four times.
Risk management analysis is a key area where banking sector can save themselves from any kind of fraud and unrecoverable risk. For this, the best thing is to take help of Big Data technologies like Hadoop. Gather the previous record of the customer like loan data, credit card history or their background data and analyze whether they can pay the kind of service they are looking for. The risks of algorithmic trading are managed through back testing strategies against historical data. Big data analysis can also support real-time alerting if a risk threshold is surpassed. Mostly, a call centre agent facilitates the customer’s request. However, the agents have few ways to determine whether the person they are speaking to on the phone is the actual customer, and this poses a serious threat to that customer’s information. Big data analysis helps to detect these fraudulent phone calls which can help a person identify information like the caller’s location. It is integrated with customer service offices, and the banking agents get alerts if the call is fraudulent so that they can pass the call to fraud specialists.
Enterprise Data Warehouse & Optimization
Offloading data processing workloads onto Hadoop to improve performance and reduce cycle times. Offloading high volume storage and processing onto Hadoop. Delivering ready-to-consume results to traditional data store. Big data warehouses are built on Hadoop and enable data consumption. Data is archived on Hadoop to reduce storage cost and meet the compliances around online data access.
Catch Stock Market Cheaters
Market surveillance depends on algorithms to identify patterns in trading data that might indicate manipulation and alert staff to investigate.
But the huge volumes of data can cause an enormous number of alerts, many of which are false alarms.To tackle this issue, a machine learning software is developed that can look beyond the patterns and understand which situations truly deserve to be mentioned as red flags. In other words, the machine learning software will learn which trading patterns lead to legal charges, to classify the right ones. Also,moving market surveillance system to cloud, gives it more computing power to analyze data quickly.
Compliance & Regulatory Requirements
Banking and financial services need to do regular compliance and audit for their data, finance, etc. They come under regulatory body which requires data privacy, security, etc. Big data analysis can help in analyzing the data and finding the situation where financial crisis or security issue can occur. This will help the banks and financial sector to save from any compliance and regulatory issues.
Customer behavior data points may include spending habits, geolocation, and recurring payments such as gym memberships or online services. In order to have a fully-functioning predictive analytics application for discerning and analyzing customer behavior, a bank must use their customer data to train a machine learning model. Predictive analytics can also be used in credit scoring applications for client banks and enterprise creditors to more accurately estimate the risk associated with a potential customer. Banks use trading insight found using prescriptive analytics to help their clients who buy and sell stocks make more informed decisions.
Streamline client payment processing
Intelligent Receivables (IR) is a well-suited solution for firms that manage lots of payments where the remittance information is either missing or received separately from the payment.