With the increasing technologies, crime in finance has become more sophisticated and complex. By combining machine learning, artificial intelligence and intelligent analytics in the fraud management platforms. Now the banks can be ahead of the challenges and decrease their fraud management costs. There are many trusted places like dharbor which helps a lot in doing fraud management.

Increasing Fraud

In today’s world, crime in finance against financial service institutes and banks is increasing rapidly. Till year 2020, worldwide the card fraud is expected to increase to $183.29 billion. Capital Market Firms and banks should improve their defenses and many false positives and many inefficient investigation processes move the operational costs. The advantages of fraud detection and loss prevention should be balanced with the experience of customer service as there can be complication in the fraud systems and slow service delivery.

Stay ahead of common purchase point

Banks can now protect themselves by protecting against frauds and having the flexibility for the management of new threats as they arise. There is a multi-faceted and comprehensive solution which is powered by Google Cloud Platform which helps clients in prevention, detection and analysis of fraud by using hybrid machine learning models and approach based on rules.

The CPP fraud analytics solution is based on machine learning algorithm and can help banks to decrease the false positive numbers as compared to other rule-based solutions.

Our finance institution can expect tangible results like

• Decreased false positives and fast fraud detection

• Improved efficiency of investigator by up to 70%

• A low total cost of ownership with a pay-use model

• Real time near fraud detection with monitoring of suspicious locations and accounts

We can help you address every aspect of Compliance and Financial Crime Fraud Management

• Finance intelligent units

• Anomaly Intelligence

• Cyber security

• Cyber analytics

• Fraud filtering

• Monitoring of fraud

• Customer identification

• Customer authentication

• Customer risk assessment

• KYC (enhanced due diligence/customer due diligence)

• Data privacy

• GDPR compliance

With the help of deep banking and capital market expertise attaining solution of Market Leading Next Generation

The business focused approach purchase existing client investments in reducing costs, ROI, fraud management and AML management processes with technology partners like SAS and Google cloud.

Transaction Data Analysis

There can be analysis of transactions using fraud scenarios which are hypothetical and data models to detect anomalies and suspicious transactions. With the use of fraud detection techniques like Benford’s Law and in consultation with audit teams, there is analysis of historical data. By the help of tools like advanced data selection queries, IDEA and macro based models can be created to analyze the given data set and to provide the client with easily usable set of functions for analysis of fraud. You can find all these in digital harbor which is known for its services in this area.

Post-investigative Implementation

Once we get to know the risks either through in-depth fraud investigation or study, there will be work with organization to fix problems and implement controls. Any successful fraud reveals many control weaknesses in finance processes. Controls should be of detective nature and preventive. We should have the ability to answer questions like, how do we make sure the fraud happens again and how will we know if something like this is taking place.