[et_pb_section fb_built=”1″ _builder_version=”4.5.1″ _module_preset=”default” background_image=”https://sigmacognition.ai/wp-content/uploads/2021/05/bg-sigma6.jpg” custom_padding=”60px||43px|||” animation_style=”slide” animation_direction=”top” background_last_edited=”on|phone” background_color_gradient_end_tablet=”rgba(0,42,71,0.44)” background_color_gradient_end_phone=”rgba(0,42,71,0.44)” background_color_gradient_overlays_image_tablet=”off” background_color_gradient_overlays_image_phone=”off” locked=”off”][et_pb_row use_custom_gutter=”on” gutter_width=”2″ make_equal=”on” module_class=”service-ti-sub” _builder_version=”4.5.1″ _module_preset=”default” width=”90%” width_tablet=”90%” width_phone=”90%” width_last_edited=”on|tablet” max_width=”1210px” max_width_tablet=”90%” max_width_phone=”90%” max_width_last_edited=”on|desktop” custom_padding=”0px||0px||true|”][et_pb_column type=”4_4″ _builder_version=”4.7.7″ _module_preset=”default”][et_pb_text _builder_version=”4.5.1″ _module_preset=”default” header_font=”Josefin Sans|700|||||||” header_text_align=”center” header_text_color=”#ffffff” header_font_size=”60px” header_line_height=”0.9em” header_2_font=”Alata|700|||||||” header_2_text_align=”center” header_2_text_color=”#ffffff” header_2_font_size=”40px” header_2_line_height=”1.5em” header_3_font=”Alata|600|||||||” header_3_text_align=”center” header_3_text_color=”#000000″ header_3_font_size=”54px” header_3_letter_spacing=”-1px” custom_margin=”30px||||false|false” header_3_font_size_tablet=”” header_3_font_size_phone=”35px” header_3_font_size_last_edited=”on|phone”]

Debt Collection

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The Challenge

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The Debt Collection department of the client had very limited resources and their effort was not always worth it. They were not able to foresee the results of their debt collection effort or the time spent on a single account.
However, they had a database with a long history of debt collection experiences together with the details of the actions taken and the results of the actions.

Sigma’s classifier learns from the historic and current data, so it can later estimate the probability of debt recovery for each debtor.

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The learning process takes less than 2 hours once the data is available. [/et_pb_blurb][/et_pb_column][et_pb_column type=”1_2″ _builder_version=”4.5.1″ _module_preset=”default” background_enable_color=”off” background_image=”https://sigmacognition.ai/wp-content/uploads/2021/03/C-2-Debt1.jpg” background_position=”bottom_right” custom_padding=”40px|25px|40px|25px|true|true” animation_style=”slide” link_option_url=”#” border_radii=”on|5px|5px|5px|5px” box_shadow_style=”preset1″ box_shadow_vertical=”0px” box_shadow_blur=”48px” box_shadow_color=”rgba(0,0,0,0)” box_shadow_color__hover_enabled=”on|desktop” box_shadow_color__hover=”rgba(162,162,162,0.5)”][et_pb_divider show_divider=”off” _builder_version=”4.5.1″ _module_preset=”default” height_tablet=”200px” height_phone=”200px” height_last_edited=”on|phone” locked=”off”][/et_pb_divider][/et_pb_column][/et_pb_row][et_pb_row column_structure=”1_2,1_2″ use_custom_gutter=”on” gutter_width=”2″ make_equal=”on” module_class=”ser-img-text” _builder_version=”4.5.1″ _module_preset=”default” width=”90%” width_tablet=”90%” width_phone=”90%” width_last_edited=”on|tablet” max_width=”1210px” max_width_tablet=”90%” max_width_phone=”90%” max_width_last_edited=”on|desktop” custom_padding=”0px||0px|||” locked=”off”][et_pb_column type=”1_2″ _builder_version=”4.5.1″ _module_preset=”default” background_enable_color=”off” background_image=”https://sigmacognition.ai/wp-content/uploads/2021/03/debt.jpg” custom_padding=”40px|25px|40px|25px|true|true” animation_style=”slide” link_option_url=”#” border_radii=”on|5px|5px|5px|5px” box_shadow_style=”preset1″ box_shadow_vertical=”0px” box_shadow_blur=”48px” box_shadow_color=”rgba(0,0,0,0)” box_shadow_color__hover_enabled=”on|desktop” box_shadow_color__hover=”rgba(162,162,162,0.5)”][et_pb_divider show_divider=”off” _builder_version=”4.5.1″ _module_preset=”default” height_tablet=”200px” height_phone=”200px” height_last_edited=”on|phone” locked=”off”][/et_pb_divider][/et_pb_column][et_pb_column type=”1_2″ _builder_version=”4.5.1″ _module_preset=”default” background_color=”#ffffff” custom_padding=”40px|25px|40px|25px|true|true” animation_style=”slide” link_option_url=”#” border_radii=”on|5px|5px|5px|5px” box_shadow_style=”preset1″ box_shadow_vertical=”0px” box_shadow_blur=”48px” box_shadow_color=”rgba(0,0,0,0)” box_shadow_color__hover_enabled=”on|desktop” box_shadow_color__hover=”rgba(162,162,162,0.5)”][et_pb_blurb title=”The Outcome” url=”#” content_max_width=”100%” _builder_version=”4.5.1″ _module_preset=”default” header_font=”Josefin Sans|700|||||||” header_text_align=”center” header_text_color=”#00223f” header_font_size=”20px” header_line_height=”1.5em” body_font=”Josefin Sans||||||||” body_text_align=”left” body_text_color=”#00223f” body_font_size=”18px” body_line_height=”1.5em” module_alignment=”center” animation=”off” border_width_right_image=”8px” border_color_right_image=”rgba(0,0,0,0)” header_text_color__hover_enabled=”on|desktop” header_text_color__hover=”#1273EB”]The accuracy of the prediction of debt recovery probability was 80%. These predictions allowed to focus the limited resources on those debtors from whom the debt was more likely to be recovered.
They also had very stable monthly results and increased the profitability of the department.[/et_pb_blurb][/et_pb_column][/et_pb_row][/et_pb_section][et_pb_section fb_built=”1″ _builder_version=”4.5.1″ _module_preset=”default” background_enable_color=”off” custom_padding=”40px||40px|||” locked=”off”][et_pb_row _builder_version=”4.5.1″ _module_preset=”default” custom_padding=”||0px|||” locked=”off”][et_pb_column type=”4_4″ _builder_version=”4.5.1″ _module_preset=”default”][et_pb_text _builder_version=”4.5.1″ _module_preset=”default” header_font=”Josefin Sans|700|||||||” header_text_align=”center” header_font_size=”20px” header_2_font=”Josefin Sans|700|||||||” header_2_text_align=”center” header_2_text_color=”#000000″ header_2_font_size=”35px” header_3_font=”Livvic|700|||||||” header_3_text_align=”center” header_3_text_color=”#ffffff” header_3_font_size=”36px” header_3_line_height=”1.3em” module_alignment=”center” custom_margin=”||21px|-31px|false|false” custom_margin_tablet=”-10px||||false|false” custom_margin_phone=”-10px||||false|false” custom_margin_last_edited=”on|phone” hover_enabled=”0″]

See More Uses Cases – Sigma Business Intelligence

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