The rise of Big Data, coupled with the increasing need to interrogate larger market data sets and the requirement for deeper granularity of information to feed predictive models, forecasts and trading, represents the perfect opportunity to marry new technology and business needs. The introduction of Big Data technology is critical for the re-engineering of data warehouses to cope with the vast quantities of data now needing to be processed. With our Big Data solutions we aim to deliver tailored solutions to help the finance industry tackle specific issues such as increasing conversion rates and dealing with customer retention issues.
The roles both Business Intelligence and Big data play to help a company analyze the financial market is invaluable to any company or persons who choose to make use of it.
The main reason is that people and companies who get use of these technologies are able to give prepare and implement the instruction to collect any information for any period of time as long as there is a digital record of the information the algorithm can collect the information.
The process will then analyze the information and give the user an extremely accurate result of what the outcome of the data was and can give a prediction to the person or company and in terms of the financial market recommend where the company or person should invest and when the group should sell their shares.
There is no doubt that big data and business intelligence play an important role in influencing the financial market, and is the only legal way that persons and companies can gain while predicting where to invest and when to sell stocks, which helps add value to the financial market.
AI is set to transform investment banking. There is a lot of analysis going on in banks and financial companies. Unless the company is a start-up or under extreme time pressure, all significant management decisions are supported by lot of analysis. The analysts thus belong to the key staff, because they can see the business through numbers. (In case their analytic skill is accompanied by fair communication skill, they have a promising career perspective.)
Some of the most advanced analysis is done in the department of risk management. Companies that issue loans need a sophisticated approval process, which is managed by the underwriting team. The analysts in this team develop regression models that estimate the probability that the customer will default on his loan. They would use statistic software such as SAS or SPSS to find correlation between the payment morale of historic customers and data available about them at the time of approval decision, such as demographic information from the loan application form, credit bureau services and results of various telephonic or online verification. The popular technique used for this is the Logistic regression.
This area is also where big data can potentially be beneficial – there are tons of data publicly available about people on social networks. Mining this data for useful application requires lot of computational power and advanced techniques and there is a new market of 3rd party companies that provide this analytic service to financial companies. However, my experience so far was that these techniques are still in development and there is more talk than practical usage of the big data at the moment.
The risk analysts also cooperate with the department of finance to continuously evaluate the performance of the customer portfolio in order to estimate the risk costs (aka impairment losses), both for the management and regulatory purposes (e.g. Basel Accords compliance). The risk cost model may be based on roll rates or (more accurately) on Stochastic matrix (aka Markov model).
The risk department may also have a fraud prevention team whose analysts look for suspicious patterns in the data in order to detect individual or organized fraud attacks on the company. The fraudsters always come up with new creative ideas how to cheat the approval system so there is always something to improve in the fraud prevention and there is also opportunity to employ various software and technology (fingerprints, face recognition, ..).There is a need for a lot of analysis of efficiency of business processes in the company, especially when there are big groups of employees in question. This is the case of call centers – the customer care and telesales teams, that are typically part of the operations department, and especially the debt collection team, which belongs somewhere between the risk and operations. The analysts in these teams solve the problems of optimal staffing, optimal configuration of the campaigns (who to call, on which phone, how often), measure various performance statistics of the operators etc..Another “analytic brain” of the company is usually located in the customer relationship management department. The experts in this team develop equally complicated models as their risk team counterparts, in this case, trying to predict who of the old customers will most likely be interested about some of the new products available. No company wants to waste money spamming the people in vain. Again, the potential to use big data approach is there.
Specific area is financial analysis in department of finance, that puts together the budget, allocates the costs and models profitability on various levels of the business.
There is a need for analysts in order to monitor performance in sales team, aggregated on various level (salesman, office, team, city, region).
In established companies, all process innovations are tested and carefully evaluated before implementation using the champion / challenger approach. In other words, the process flow is separated into two qualitatively equal branches that form the test group and control group (e.g. select randomly 10% of new customers for new approval rules) and the two approaches are analytically compared after enough data is collected.
Finally, the advancement level of analytics in a company is critically dependent on the ability of the company to collect reliable and clean data and provide them to the analysts in proper form. Training and discipline of the front end staff in essential for that. Also, IT support and appropriate hardware is crucial to provide analysts with data warehouse, where the necessary data can be found and effectively processed. In ideal company, the analysts are provided with comprehensive data marts, OLAP cubes, management reports in OBI, etc., that shield them from technical details while providing all they need. In real practice, however, the IT development can’t keep the pace with all the new business initiatives. Therefore, the analysts need to do “some of the IT work” in order to detect where to find the necessary data and use SQL to pull the data from various stages of the database (or worse – several databases) that the company uses, then clean it up and put it into a structure that can be used to make the analysis and deliver the right message to the management.
There is a trend for mobility. Mobile users are getting bigger, mobile operations are getting bigger. Banks don’t go anywhere either. It is becoming more and more people who communicate with the bank via mobile only. We see it and understand that we need to work with this industry. And banks need to invest in innovative things, in high-tech things. Those who understand this will remain on the market, those who do not will loose customers after a while. We need to develop those areas for the future. These are electronic channels, mobile banks. These are products related to e-commerce, with translations, these are products related to electronic money.
The advantage is that we can grow the economy faster. Transactions are faster, they are more interconnected. For example, today humans may pay for a phone, mail by transfering money using computer or a smartphone. Indeed, I think that the revolution is taking place thanks to IT in financial instruments. The quality of people today ensures the quality of the product in the bank. IT allows to correct injustice against those people who have little opportunity, because they do not live in large cities. IT provides them with opportunities for education, for work, for operations that they do not have.
A further development of online banking is the trend towards mobile banking, with the use of devices such as smartphones and the development of specific applications – either a browser or a standalone application. There are two approaches to setting up this type of mobile banking:Wireless Application Protocol and Standalone Mobile Application. With our knowledge we can help banks choose the right mobile technology and approach, which might be critical in gaining long-term sustainable growth.
We believe that investment now in the right IT solutions will determine banks’ competitiveness for years to come. Whenever you feel you need developers with deep expertise in financial&banking and insurance industry – do not hesitate to contact Limestone Digital.
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