Team Mirsis
Description
**Team Background**: Mirsis is a leading IT consultancy company in tailored banking and financial services solutions in Istanbul, Turkey. The R&D arm of the company develops cutting edge projects, spanning financial analytics with machine learning forecast and categorization models and modern web/mobile interfaces.
**Solution Proposal**: A complete mobile robo advisor that is backed by a recommendation engine with “automatic goal generation” feature, “monetary value exchange” marketplace feature and an embedded leaderboard capability with a quiz contest educating about money management principles 101 (up to 402)
**Business Rationale**: Personal financial management is important for the economy, especially thinking the agenda of saving as the country, and the well being of the individuals. The household savings rate of Saudi Arabia, compared to China at around 37% (OECD) and Germany at around 12.4% (Deutsche Bundesbank), is close to just 2%. For every SAR 14,823 a household is making, he or she spends SAR 14,584, leaving only 2% of the income as SAR 239 in 2018 (GASTAT, KPMG). The certain need for change from wasting culture to saving culture should be addressed by an educational tool. As the females are saving more, there will be a special check with the segment.
Although the urban population rate in Saudi Arabia is high with 84.07%, the regional differences in financial services are a reality such as suburban areas with no financial service and vast space between urban areas. Regional customizations could require cross-banking data to be processed.
Additionally, the things with monetary value such as loyalty points, cashback amounts, and monthly subscriptions, or even farming products, are wasted through the consumption culture and this could be addressed with an exchange platform, supporting the circular economy.
In terms of the speed of service, weeks-long processes are unacceptable within an online community of people and even unreachable for remote and underserved parts of the country. The business needs to be anti-red-tape and fast, with the help of digital documentation and product variety. The ultimate aim is a multi-product supporting recommender, expanding the current portfolio of products with the cross-financial-industry products.
The types of red-tape transactions will be scrutinized to derive more value from the current banking and other monetary transaction sets.
**Technical Rationale**: To be able to sustain the most experiential bank goal, the advisor tool needs to educate while having fun in the meanwhile. Robo advisor theme will give the tool a character to interact with, such as “Did you know if you stopped going cinemas extensively you would save SAR 750 each month?” or “You spend 55% more than your peers for cinema, did you know that?”. Also, a quiz contest will educate about the money management concepts and give the user a chance to show the achievements in a leaderboard.
The tool will identify the gaps for the spending and saving cross behavior in the cross-banking data and suggest ways of saving more to reach the financial goals which the tool will generate from the amounts the platform identifies. The machine learning algorithms (DNN & LSTM RNN) will be ready to find more about the disparate classifications of the profiles by demographic data such as geography, age and behavioral data such as spending and saving, and then forecast the amounts of the slack amounts that could be saved, with the help of average expenditure compared to the specific expenditure of the user.
**Remarks**: Simulate, Have Fun, Save. Fast.
HG and TM
Team Members
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Team Lead