Insurance & Mutual Funds

Solution Specific Offerings

Cybersecurity

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Cybersecurity
Ankios

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Ankios
Networking & Data Center

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Networking & Data Center

Use Cases

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.

Endpoint Protection

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.

Web Protection

  • 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.

VA

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.

DAM

  • 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.

Mobile Application Integration

Integration to mobile applications to prove absolute data at the source for the back office processing for eg:- capturing pictures/videos/location/meta data and Blockchain signing the same before sending them for claims or settlement processing.

Addressing Cyber Insurance

Institutions providing cyber insurance can provide Blockchain based products to their customer to enable absolute truth based data sharing between them. For example, sharing logs and data which is Blockchain signed helps cyber insurers be rest assured of the data for forensics.

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 and a receipt which is Blockchain signed can empower the customers and ensure auditability between them and AMCs.

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 And Brand Reputation

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 an underwriting back office team for document processing.

Customers 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.

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.

Customer 360

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

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

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.

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.

Predictive Analytics

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.

Coming soon

Coming soon

Success Stories

Which industry specific solution are you interested in?

Banking Services

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Banking Services
Insurance & Mutual Funds

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Insurance & Mutual Funds
Cooperative Banks

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Cooperative Banks
Financial Services Institution

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Financial Services Institution
Stock Exchanges & Brokerage Firms

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Stock Exchanges & Brokerage Firms
Manufacturing

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Manufacturing
IT-ITeS

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IT-ITeS
Retail

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Retail
Pharma & Health

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Pharma & Health
Travel & Transport

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Travel & Transport
Government

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Government
Smart Cities

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Smart Cities
Healthcare

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Healthcare
Public Transport

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Public Transport
Education

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Education

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