Leverage ML-based rule engines to streamline reporting, monitoring and compliance. Gain extra market insights from all the big data at your disposal
Focus on your business while AI- and NLP- powered chatbots have personalized conversations with your customers and team members.
Forecast market outcome and mitigate financial risks with neural networks, deep learning and big data financial services.
C360 Advanced feedback and scoring systems are twoof the new inventions of AI.They will assist students and professionals in improvingwriting skills
Detect cybersecurity at the outset with predictive security algorithms and real time anomaly detection.
Stop hoarding and start acting. Turn all your bigdata for financial services intooperational intelligence to drive your day-to-daydecisions
Enabling predictive analyticssoftware that wouldessentially predict which stocks willyield the highest return. The software would run throughthousands of stocks at onceand correlate certain data points among them to positivestock returns, thus freeing up achartist’s time for higher-value tasks.
Employees at banks and insurance firms could scanpaper documents into PDFs andupload them to the document digitization software.C360 machine vision algorithm couldthen run through the PDFs and “read” what they say,populating fields on a digitalversion of the document with the words in the PDF.
Implementing Document search and data mining approachesare broad functions thatcould help employees at banks, insurance firms, andcredit card companies in a varietyof ways.
Enabling of Underwriting approaches into Banks andinsurance firms could use a widevariety of machine learning approaches to gauge whetheror not an applicant is likely topay back their loan or to determine how much theirpremium should be
Capable of integrating AI-based credit scoring software into bank applications could be helpful for loan applicants that lack a credit history but otherwise behave in ways that indicate a high likelihood of paying back their loan or paying off their credit cards on time
Machine learning algorithms can be used to enhance network security significantly. Data scientists are always working on training systems to detect flags such as money laundering techniques, which can be prevented by financial monitoring.
Machine Learning algorithms are excellent at detecting transactional frauds by analyzing millions of data points that tend to go unnoticed by humans. Further, ML also reduces the number of false rejections and helps improve the precision of real-time approvals.
Using machine learning techniques, banks and financial institutions can significantly lower the risk levels by analyzing a massive volume of data sources..
The wave of technological change that has swept across the financial sector, and society at large, since the arrival of the internet, has changed things forever – and not just in good ways.
Big Data is foundational to the new generation of smart, self-teaching machines that are set to drive a seismic shift across every aspect of society, including banking and finance.
Another challenge facing the financial services industry is the wave of disruptive start-ups that have emerged, and keep emerging.
Having all this data flying around makes it easier for banks and other financial services organisations to work out what we want, and offer us products and services which accurately match our needs.