Access Control System in Banking
Data is playing an increasingly important role in the banking industry. It is the key to developing intelligent interactions with customers regardless of the channel, tailored to meet the demand of individuals and families.
Data is also driving new technologies, such as artificial intelligence and bots, which are, in turn, helping to increase operational efficiency and reduce risk. The data is even enabling new banking models, such as peer-to-peer lending, crowdfunding, and the sharing economy.
The impact generated by the data is best illustrated by looking at developments in the consumer credit industry. Banks traditionally use credit was kostet sperrmüll scoring, which is based on a narrow range of scores that changes infrequently. This approach has two main restrictions. First, decision-making is slow as banks have an incomplete view of consumer financial health. Second, this generates ‘small files’, especially on Millennial consumers who do not have a financial history and are averse to debt. In many countries, consumer credit has been negative and used by banks essentially to blacklist people with late payments.
Real-time Checking Account
Today, banks are basing their lending and risk management decisions on integrated data. Information on debt amortization is being combined with Access Control System in banking near real-time checking account and transaction data to develop comprehensive risk assessment models. Rather than relying on the timeliness of payments or the percentage of available credit used, banks can Access Control System in banking risk patterns based on past behavior or possible future changes.
With ‘small file’ consumers, banks and credit bureaus are exploring new sources of data, such as history of bill paying and mobile phone use. Some cases, particularly with non-bank lenders, the nature of the consumer’s social media can also contribute to the assessment of the credit supply.
In addition, the data can be used to personalize sales and marketing interactions. In the same way that this can help banks form a detailed profile for the consumer credit offering, it can also be used to personalize sales messages and products for the benefit of increasingly service-demanding customers.
Working on data
Many times, volume, speed and variety of data types can technically exceed the capacity of traditional technologies, such as relational databases. For its part, unstructured data such as video, voice and text are especially unsuitable for old approaches to IT and the first generation of Big Data technologies.
To overcome those barriers, banks are embracing machine learning resources that train predictive models continuously based on data streams. Machine learning can help you identify subtle details for better results. For example, traditional regression or decision tree approaches can predict the highest odds of customer loss based on relevant variables. Machine learning goes beyond linear relationships to recognize interactions between much larger data sets.
Success will depend on cultural change. Due to the faster flow of data and the rapid change in expectations, a much more iterative approach to planning is necessary. In particular, the migration to agile development requires a significant change in product management style.
The challenge for banks
Inevitably, the central role of data brings new risks. People need to understand how to govern and organize an analytically oriented business. For example, many banks currently maintain data only on people whose credit applications are accept. By definition, keeping only this subset of data and not all that have applied for credit means that banks are at risk of having their marketing opportunities reduced.
However, the most serious risks can be external. Today, cyberthreats are damaging more than reputation and causing CEOs to resign, such as Target and Sony. Similarly, senior government and academic officials are also losing their jobs due to the data breach. The nature of threats has also changed with hackers now seeking physical effects or trying to undermine an organization’s credibility by subtly corrupting rather than stealing.
Solution for the future
To remain competitive, banks need the assurance that they have the best security technology at their disposal.
This includes authentication, for example, with the use of biometric technology that can confirm the identity of the consumer. That is based on understanding usage habits such as the typical way a person grips a phone, typing speed, and finger glide angles.
Separately, machine learning can apply to detect threats. For example, a cyber analytics model can continually consume large streams of data from network activity to define baselines and detect anomalies. These models can applying within an organization’s cybersecurity software and integrate with threat intelligence.
This ability to protect customers is based on constant innovation. And the ability to understand and anticipate the evolving nature of cyber threats around the world is critical for banks to ensure future success. With the right technology, they can ensure that their businesses will be safe tomorrow.
A non-return corridor
This device is basically make up of two lock doors, which open only in the direction of the flow of people, facilitating the passage of any person, regardless of their physical condition, and preventing any individual from entering against this flow. outside the facilities. Thanks to the sophisticate system for detecting directionality or improper return of pedestrians, if someone want to enter against the system, the alarm would be activate, closing and immediately locking the corresponding automatic door.
Manusa’s non-return corridor detection system not only detects pedestrians and the direction they are going; it is also capable of measuring the time that a pedestrian or a static object remains within the corridor. If the establish residence time is exceed, an alarm will sound and the entrance door will lock, remaining close until the system detects that the pedestrian or object has left the corridor through the exit door. This first alarm has a slight soun and disappears after the corridor is release, but if after 30 seconds from the detection of the object it is still present, a serious error alarm will sound until 30 seconds after the corridor is release.
Advantages:
One of the advantages of this anti-return aisle is that it can configuring in various modes: single, multiple or parallel, the self-supporting assembly being easy to install and low maintenance.
Another notable advantage is that the Toran de Manusa corridor can connecting to any local or remote external control or supervision system thanks to its multiple communication and integration possibilities:
- Intercom: allows communication from inside the corridor to the control center. This intercom can of great help in case the user is trap inside the corridor.
- Video surveillance: it is a Closed-Circuit Television or CCTV system integrated in the corridor that allows monitoring and supervision for greater security.
- Counting system: this system allows the counting of people through stereoscopic vision.
- LED display: it is integrated into the cover, allowing to offer visual messages to users.
The installation of anti-return corridors, automatic doors and other Manusa Access Control System in banking not only provide greater control and security to airports, it also facilitates access for people, helps to increase security at airports and improve comfort and the well-being of the users, making the entire trip a more pleasant experience.
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