Creating a Sustainability Reporting Framework for Pace Zero’s Sustainability Linked Loans (SLLs) Borrowers

Venture capital X (VCX) is about to launch a new product: Sustainability-Linked Loan (SLL). These new sustainability-linked financial products represent an interesting opportunity both for lenders and borrowers. To incentivize borrowers to achieve predetermined sustainability objectives, VCX offers reduced interest rates on loans; however, these SLL are contingent on borrowers meeting predetermined sustainability targets.

Linear and non-linear replication factor models for Funds look-through

The Fundamental Review of the Trading Book (FRTB) is a set of regulations by the Basel committee, which is expected to be implemented by banks by 2022. The regulation targets market risk management in banking industry. The regulation targets market risk management in banking industry. According to FRTB, banks must decompose funds that can be looked through into their constituents and determines the relevant capital requirements as if the underlying position were held directly by the bank.

Applications of ML/AI in Asset Management - part 2

ML/AI is widely used and deployed in many industries. Its deployment in Asset Management industry (and
especially in Canadian pension fund sector) is significantly behind. Part of it is the fear of “black box” and what recommendation it gives. This sentiment is outdated as the recent advancements in ML/AI allow looking inside the “black box and thus focus on “white box” asset allocation recommendations.
Another reason is that asset management these days is the intersection of three disciplines: Financial
Economics, Statistics, and Computer Science.

Applications of ML/AI in Asset Management - part 1

ML/AI is widely used and deployed in many industries. Its deployment in Asset Management industry (and especially in Canadian pension fund sector) is significantly behind. Part of it is the fear of “black box” and what recommendation it gives. This sentiment is outdated as the recent advancements in ML/AI allow looking inside the “black box and thus focus on “white box” asset allocation recommendations.
Another reason is that asset management these days is the intersection of three disciplines: Financial Economics, Statistics, and Computer Science.

Developing a standardized, commercially viable and scalable Software-as-a-Service model which can be customized for customer retention, acquisition, and monetization using predefined adaptation strategies

Apps, mobile games, cloud based services have become ubiquitous and integral to our daily lives. These apps, although free to use, can be expensive to produce and make money either through ads or in-app or program purchases. Companies developing these services have to make software that are not only easy to use and attractive, but also integrate money making attributes without affecting user experience, thereby building a loyal user base.

An Alberta-based VAR Structural Model

International Financial Reporting Standards (IFRS) for loss allowances are changing, and financial institutions are proactively adapting existing methodologies and developing new ones to remain compliant. The main ingredient in the myriad of evaluations that banks are required to perform for compliance is risk assessment. The first goal of this research project is to review best practice risk models, with a special focus on modeling the evolution of changes in creditworthiness for industry sectors.

Evaluation of Machine Learning Methods for Portfolio Replication of VIX Futures

During the past two decades, the CBOE Volatility Index (VIX® Index), a key measure of investor sentiment and 30-day future volatility expectations, has generated much investor attention because of its unique and powerful features. The introduction of VIX futures in 2004, VIX options in 2006, and other volatility-related trading instruments provided traders and investors access to exchange-traded vehicles for taking long and short exposures to expected S&P 500 Index volatility for a particular time frame.

Persuasive technology - Guidance to Virtual Relationship Manager (VRM) for effective sales effort basis voice data mining

Voice of the Customer (VoC) is how companies hear and listen to customer feedback about their brand, products, and services. Voice of the Customer solutions convert gathered feedback into valuable data and insights at scale. Data-driven VoC analytics programs are proven to increase customer lifecycle value and lower customer churn. Companies in various industries including insurance, financial services, and healthcare are leveraging this technology to generate insights into customer needs.

Semi-Supervised Learning for NLP Text Classification

Insurance companies collect huge volumes of text on a daily basis and through multiple channels, which can be used for lots of different analyses, including identifying “cause of death”. It is difficult to overestimate the importance of an insurance company’s need to understand the facts and circumstances surrounding an insured individual’s death. These facts, including the manner and cause of death, along with other data about the decedent, are critical to an insurance company’s ability to measure mortality rates.

Building and Evaluating a Consolidated SIEM (Security Information and Event Management) Threat Identification

Businesses are collecting more and more data, but they do not have the manpower to properly analyse it. This project will implement a proof of concept for a system that uses machine learning to improve the detection of cyber threats. The machine learning algorithm will receive information from many different data sources, detect where there is suspicious activity, and alert a cyber analyst. By adding a machine learning algorithm to the arsenal of cyber analysts, the analysts will be able to cut down on the time it takes to react to the threats.

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